Dissertations / Theses on the topic 'Global environmental change – remote sensing'
To see the other types of publications on this topic, follow the link: Global environmental change – remote sensing.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 dissertations / theses for your research on the topic 'Global environmental change – remote sensing.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.
1
Miles, Luke G. "Global Digital Elevation Model Accuracy Assessment in the Himalaya, Nepal." TopSCHOLAR®, 2013. http://digitalcommons.wku.edu/theses/1313.
Full textAbstract:
Digital Elevation Models (DEMs) are digital representations of surface topography or terrain. Collection of DEM data can be done directly through surveying and taking ground control point (GCP) data in the field or indirectly with remote sensing using a variety of techniques. The accuracies of DEM data can be problematic, especially in rugged terrain or when differing data acquisition techniques are combined. For the present study, ground data were taken in various protected areas in the mountainous regions of Nepal. Elevation, slope, and aspect were measured at nearly 2000 locations. These ground data were imported into a Geographic Information System (GIS) and compared to DEMs created by NASA researchers using two data sources: the Shuttle Radar Topography Mission (STRM) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Slope and aspect were generated within a GIS and compared to the GCP ground reference data to evaluate the accuracy of the satellitederived DEMs, and to determine the utility of elevation and derived slope and aspect for research such as vegetation analysis and erosion management. The SRTM and ASTER DEMs each have benefits and drawbacks for various uses in environmental research, but generally the SRTM system was superior. Future research should focus on refining these methods to increase error discrimination.
2
Deer, Peter. "Change detection in remote sensing using supervised fuzzy classification." Title page, abstract and contents only, 1999. http://hdl.handle.net/2440/19340.
Full textAbstract:
Title page, contents and abstract only. The complete thesis in print form is available from the University Library.Thesis (Ph.D.)--University of Adelaide, Dept. of Geography and Dept. of Computer Science, 1999
3
Ayanlade, Ayansina. "Remote sensing of environmental change in the Niger Delta, Nigeria." Thesis, King's College London (University of London), 2015. http://kclpure.kcl.ac.uk/portal/en/theses/remote-sensing-of-environmental-change-in-the-niger-delta-nigeria(b649a1f9-8c35-45d5-94ab-3107e4c3b0aa).html.
Full textAbstract:
This study examines landuse change (LUC) in the Niger Delta of Nigeria, focusing on the drivers of change and the societal implications on the people in the Delta. This study applies both remote sensing and social research methods to evaluate the spatial and temporal change in landuse, population change, deforestation, and degradation within forest reserves; and the impacts of oil production and the effects of the changes on the Delta. A time series of Landsat TM images was used over the period from 1984 to 2011. The study evaluates a number of classification and post-classification change detection methods to examine LUC, while NDVI is used to monitor the degradation of forests. Accuracy assessment shows that Maximum Likelihood (ML) is the most accurate method, but results were still error prone. To improve classification accuracy, a Decision Tree Reclassification (DTR) method was developed that uses prior classifications and simple rules of those LUCs, which occur over time and those that do not. DTR improves the overall accuracy of the classification from 62% to 89%. The social methods used a mixed-method approach (questionnaires, interviews and focus group discussions). The methods were carefully selected and used to help explain the results of findings from remote sensing. The results are presented in two phases: (1) results of remote sensing showing the overall changes in the entire Niger Delta and specific case studies (2) results of social science survey showing the drivers of changes and their environmental and societal implications on the people in the Delta. The results show that nearly 9000 km2 forest has been lost in the Niger Delta region between 1984 and 2011, but the extent of deforestation varies from one forest type to another. Lowland rainforest is more exploited than freshwater swamp forest and mangrove forests, with approximately 40% of lowland rainforest areas lost. The urban areas expand by about 50% in lowland rainforest, but less urban expansion is noted in freshwater swamp forest (16%) and mangrove forest (38%). The study finds that assessing oil spill impacts using Landsat TM was not possible, but that oil production infrastructures (e.g. construction of canals) can be an important cause of deforestation in the Delta in exceptional cases. This is evident in the mangroves around Tsekelewu that are reduced from 200km2 in 1984 to 114km2 in 1987, because of the construction of artificial canals that have promoted regular inflow of seawater and the consequent destruction of freshwater mangroves. The results from social survey show also the drivers of LUC and deforestation in the Delta are probably multiphase including unenforced forest protection laws; corruption at all levels; pressure of immigration and increasing population; and indifference of local people to the state of the forest around them.
4
Wright, Graeme L. "Multiscale remote sensing for assessment of environmental change in the rural-urban fringe." Thesis, Curtin University, 2000. http://hdl.handle.net/20.500.11937/1110.
Full textAbstract:
The objective of this study was to investigate the application of multiscale satellite remote sensing data for assessment of land cover change in the rural-urban fringe. Inherent in this assessment process was the interpretation of multispectral data collected by several medium resolution satellite systems and evaluation of the quality of the resulting change information. Each dataset was acquired for a single date and classified at two levels of detail using standard classification algorithms. The optimum classification approach for each date was identified and the changes in land cover evaluated in several ways. The contribution of spatial and thematic errors and their propagation through the analysis process was investigated.Data for this research were acquired over an area approximately 4.5 km square located in the southern metropolitan area of Perth, Western Australia. At the time of the initial data acquisition in 1972 the area was predominantly rural and comprised mostly dense pine plantations, however by the final stages of data acquisition in 1991, the area was almost completely given over to urban residential land use. Changes were interpreted from classified Landsat Multispectral Scanner (MSS), Landsat Thematic Mapper (TM) and SPOT (System Pour l'Observation de la Terre) High Resolution Visible (HRV) multispectral data, and were compared to reference maps compiled from medium scale aerial photographs. The geometric properties of high resolution panchromatic IRS1-D data were also evaluated to test the geometric potential of high resolution satellite data.Supervised and unsupervised classification algorithms were used for derivation of land cover maps from each multispectral dataset at two levels of detail. Data were classified onto four general levels at the broadest (Level I) classification, and into nine levels at the finest (Level II) classification. The Kappa statistic and its variance were used to determine the optimum classification approach for each dataset and at each level of detail. No significant differences were observed between classification techniques at Level I, however at Level II the supervised classification approach produced significantly better results for the Landsat TM and SPOT HRV data. Classification at the more general Level I did not produce substantially higher classification rates compared to the same data at Level II. Additionally, higher spatial resolution data did not provide increased accuracy, however this was due mainly to a much greater complexity of land covers present at the time the higher resolution Landsat TM and SPOT HRV data were recorded.Land cover changes were assessed separately at Level I for all datasets, and also between Landsat TM and SPOT HRV data at Level II. Integrated multiscale assessment of land cover change was undertaken using classified Landsat MSS data at Level I and Landsat TM data at Level 11. This enabled the continuity of change to be established across classification levels and sensor systems, even though there were variations in the level of detail extracted from each image.The sources of spatial and thematic errors in the data were investigated and their effects on change assessment analysed. The evaluation of high resolution panchromatic satellite data emphasised the contribution to the analysis of spatial errors contained within the reference data. The multiscale data also indicated that combined propagation of spatial and thematic errors requires investigation using appropriate simulation modelling to establish the influence of data uncertainty on classification and change assessment results.This research provides useful results for demonstrating a process for the integration of information derived from remotely sensed data at different measurement scales. Availability of data from an increasing range of remote sensing platforms and uncertainty of long term data availability emphasises the need to develop flexible interpretation and analysis approaches. This research adds value to the existing data archive by demonstrating how historical data may be integrated regardless of the spectral and spatial characteristics of the sensors.
5
Wright, Graeme L. "Multiscale remote sensing for assessment of environmental change in the rural-urban fringe." Curtin University of Technology, School of Spatial Sciences, 2000. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=10384.
Full textAbstract:
The objective of this study was to investigate the application of multiscale satellite remote sensing data for assessment of land cover change in the rural-urban fringe. Inherent in this assessment process was the interpretation of multispectral data collected by several medium resolution satellite systems and evaluation of the quality of the resulting change information. Each dataset was acquired for a single date and classified at two levels of detail using standard classification algorithms. The optimum classification approach for each date was identified and the changes in land cover evaluated in several ways. The contribution of spatial and thematic errors and their propagation through the analysis process was investigated.Data for this research were acquired over an area approximately 4.5 km square located in the southern metropolitan area of Perth, Western Australia. At the time of the initial data acquisition in 1972 the area was predominantly rural and comprised mostly dense pine plantations, however by the final stages of data acquisition in 1991, the area was almost completely given over to urban residential land use. Changes were interpreted from classified Landsat Multispectral Scanner (MSS), Landsat Thematic Mapper (TM) and SPOT (System Pour l'Observation de la Terre) High Resolution Visible (HRV) multispectral data, and were compared to reference maps compiled from medium scale aerial photographs. The geometric properties of high resolution panchromatic IRS1-D data were also evaluated to test the geometric potential of high resolution satellite data.Supervised and unsupervised classification algorithms were used for derivation of land cover maps from each multispectral dataset at two levels of detail. Data were classified onto four general levels at the broadest (Level I) classification, and into nine levels at the finest (Level II) classification. The ++Kappa statistic and its variance were used to determine the optimum classification approach for each dataset and at each level of detail. No significant differences were observed between classification techniques at Level I, however at Level II the supervised classification approach produced significantly better results for the Landsat TM and SPOT HRV data. Classification at the more general Level I did not produce substantially higher classification rates compared to the same data at Level II. Additionally, higher spatial resolution data did not provide increased accuracy, however this was due mainly to a much greater complexity of land covers present at the time the higher resolution Landsat TM and SPOT HRV data were recorded.Land cover changes were assessed separately at Level I for all datasets, and also between Landsat TM and SPOT HRV data at Level II. Integrated multiscale assessment of land cover change was undertaken using classified Landsat MSS data at Level I and Landsat TM data at Level 11. This enabled the continuity of change to be established across classification levels and sensor systems, even though there were variations in the level of detail extracted from each image.The sources of spatial and thematic errors in the data were investigated and their effects on change assessment analysed. The evaluation of high resolution panchromatic satellite data emphasised the contribution to the analysis of spatial errors contained within the reference data. The multiscale data also indicated that combined propagation of spatial and thematic errors requires investigation using appropriate simulation modelling to establish the influence of data uncertainty on classification and change assessment results.This research provides useful results for demonstrating a process for the integration of information derived from remotely sensed data at different measurement ++
scales. Availability of data from an increasing range of remote sensing platforms and uncertainty of long term data availability emphasises the need to develop flexible interpretation and analysis approaches. This research adds value to the existing data archive by demonstrating how historical data may be integrated regardless of the spectral and spatial characteristics of the sensors.
6
Ly, Jennifer K. "Coastal change analysis of Lovells Island using high resolution ground based LiDAR imagery." Thesis, University of Massachusetts Boston, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1566549.
Full textAbstract:
Many methods have been employed to study coastline change. These methods range from historical map analysis to GPS surveys to modern airborne LiDAR and satellite imagery. These previously used methods can be time consuming, labor intensive, and expensive and have varying degrees of accuracy and temporal coverage. Additionally, it is often difficult to apply such techniques in direct response to an isolated event within an appropriate temporal framework. Here we utilize a new ground based Canopy Biomass LiDAR (CBL) system built at The University of Massachusetts Boston (in collaboration with the Rochester Institute of Technology) in order to identify and analyze coastal change on Lovells Island, Boston Harbor. Surveys of a bluff developing in an eroding drumlin and beach cusps on a high-energy cobble beach on Lovells Island were conducted in June, September and December of 2013. At each site for each survey, the CBL was set up and multiple scans of each feature were taken on a predetermined transect that was established parallel to the high-water mark at distances relative to the scale of the bluff and cusps. The scans from each feature were compiled, integrated and visualized using Meshlab. Results from our surveys indicate that the highly portable and easy to deploy CBL system produces images of exceptional clarity, with the capacity to resolve small-scale changes to coastal features and systems. The CBL, while still under development (and coastal surveying protocols with it are just being established), appears to be an ideal tool for analyzing coastal geological features and is anticipated to prove to be a useful tool for the observation and analysis of coastal change. Furthermore, there is significant potential for utilizing the low cost ultra-portable CBL in frequent deployments to develop small-scale erosion rate and sediment budget analyses.
7
Rufin, Philippe. "A global to regional scale assessment of dam-induced agricultural change by means of remote sensing." Doctoral thesis, Humboldt-Universität zu Berlin, 2019. http://dx.doi.org/10.18452/20125.
Full textAbstract:
Landwirtschaftliche Produktionssysteme basieren in vielen Weltregionen auf dem Einsatz von Bewässerung. Staudämme stellen einen Großteil der benötigten Wasserressourcen, jedoch wurden Zusammenhänge zwischen Staudämmen und Veränderungen im Landsystem bis heute kaum erforscht. Im Hinblick auf die steigende Nachfrage nach landwirtschaftlichen Erzeugnissen bedarf es eines besseren Verständnisses des Zusammenhangs zwischen Staudämmen, Bewässerung und landwirtschaftlichen Produktionssystemen. Daten und Methoden der Fernerkundung liefern synoptische und räumlich detaillierte Aufnahmen der Erdoberfläche mit großem Potential für die Untersuchung von landwirtschaftlichen Produktionssystemen. Das Hauptziel dieser Arbeit war es, das gegenwärtige Verständnis des Zusammenhangs von Bewässerungsstaudämmen und Landsystemen mit Mitteln der Fernerkundung zu verbessern. In dieser Arbeit wurden großflächige Beschreibungen globaler und regionaler Agrarsysteme generiert, welche nachdrücklich das Potential von Daten und Methoden aus der Fernerkundung hervorheben. Das hohe thematische, räumliche und zeitliche Detail der Ergebnisse erlaubte einzigartige Einblicke in die raumzeitlichen Dynamiken von Bewässerungsfeldwirtschaft. Die im Zuge dieser Arbeit entstandenen Ergebnisse, Methoden, und Datensätze tragen maßgeblich zum heutigen Wissensstand in Bezug auf den Zusammenhang zwischen Bewässerungsstaudämmen und Landnutzungsintensität bei und liefern wichtige Einblicke zur Verbesserung zukünftiger Produktionsstrukturen.A growing world population, and increasing demands for food, feed, fuel and fiber, substantially add pressure on the global land system. The construction of dams is a common strategy for boosting production outputs through irrigation. Reservoirs represent the most important source of irrigation water globally, but their effects on agricultural land systems are only poorly understood. Remote sensing emerges as a key tool for enabling spatially explicit assessments of dam-induced land system change due to its ability to provide spatially detailed, frequent, and synoptic observations of the land surface. The overall goal of this thesis was to assess the effects of irrigation dams on agricultural land systems on a global and regional scale, by making use of state-of-the art remote sensing data products and methods. A synthesis of the current scientific literature offered primary insights into dam-induced changes in agricultural systems, and raised the hypothesis that irrigation dams caused overall increases in agricultural land use intensity. On a global scale, satellite-based measurements of cropping frequency derived from MODIS-based map products attested to this finding, albeit a strong regional variability was apparent. Landsat-based time series methods were used on a national to regional scale, which further revealed strong spatio-temporal dynamics of irrigated agriculture. The results of this thesis add knowledge and spatially explicit insights on the effects of dams on agricultural land systems. The work further emphasizes the important role of remote sensing technologies in exploring future pathways of agricultural intensification.
8
Shipigina, Ekaterina. "Remote sensing methods for environmental monitoring of human impact on sub-Arctic ecosystems in Europe." Thesis, University of Cambridge, 2013. https://www.repository.cam.ac.uk/handle/1810/268066.
Full textAbstract:
The role and scale of human impact on the global environment is a question of special importance to the scientific community and the world as a whole. This impact has dramatically increased since the beginning of industrialisation, yet its understanding remains patchy. The sub-Arctic plays a central role in forming the global environment due to the vast territory of boreal forest and tundra. Severe climatic conditions make its ecosystems highly sensitive to any natural and human disturbances. In this context, the dynamics of boreal vegetation, and of the forest/tundra interface (the treeline), is the most representative indicator of environmental changes in the sub-Arctic. For some time now, monitoring land cover and vegetation changes using remote sensing techniques have been a powerful method for studying human impact on environment from landscape to global scales. It is particularly efficient when applied to the sub-Arctic ecosystems. Remote sensing gives access to accurate and specific information about distant and hard-to-reach areas across forest and tundra. Despite all the e orts, there is a lack of uniformity in studying human impact, a shortage of mapping of impact over large territories and a lack of understanding of the relation between human activity and environmental response. This dissertation develops a systematic approach to monitoring land cover and vegetation changes under human impact over northern Fennoscandia. The study area extends north and south of the treeline and covers around 400,000km2 reaching from Finnmark in Norway, through Norrbotten in Sweden, Lapland in Finland up to the Murmansk region in Russia. This is the most populated and industrially developed region of the whole sub-Arctic and, therefore, suffering most from human impact. This dissertation identifies industrial atmospheric pollution, reindeer herding, forest logging, forest fires and infrastructure development as the primary types of human impact close to the treeline. For each type characteristic hotspots are identified and human impact is analysed in the context of physical environment as well as cultural, economical and political development of the area. This dissertation presents an automated workflow enabling large-scale land cover mapping in northern Fennoscandia with high throughput. It starts with automated image pre-processing using image metadata and ends with automated mapping of classification results. A single classifier for multispectral Landsat data is trained on extensive field data collected across the whole region. Open source tools are used extensively to set up the processing scripts enabling rapid and reproducible analysis. Using the developed advanced remote sensing methodology land cover maps are constructed for all identified hotspots and types of human impact. Changes in vegetation are analysed using three or four historical land cover maps for each hotspot. More than 35 Landsat TM and ETM+ images covering the period from the 1980s until 2011 are processed in an automated manner. A strong correlation between the level of impact and the scale of vegetation change is confirmed and analysed. The structure and dynamics of the local treeline and the quality of environment are analysed and assessed in the context of changing levels of impact at each hotspot and regionally.
9
Zhu, Kefeng. "Application of Satellite Remote Sensing on Mountain Glacier and Coastal Zone Classification And Monitoring in South Asia." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1437652636.
Full text
10
Valdez-Zamudio, Diego 1953. "Land cover and land use change detection in northwestern Sonora, Mexico using geographic information system and remote sensing techniques." Thesis, The University of Arizona, 1994. http://hdl.handle.net/10150/278469.
Full textAbstract:
Remote sensing and geographic information system techniques have proved to be effective tools to detect, analyze, and evaluate land cover and land use changes over time. In this research project, changes in land cover and land use were detected in northwestern Sonora, Mexico between 1972 and 1992 using Landsat MSS imagery. About 40% of the entire land cover in the study area changed during that period of time. Of the six classes assigned to the imagery, cropland had the highest rate of change being modified into riparian areas by more than 60%, more than 20% into plains vegetation, and about 8% into bajadas with vegetation. From the two classification methods utilized in this study, the seeding pixels method yielded an over all accuracy over 96%, while the seeking polygons method generated overall accuracy values smaller than 82% probably to user's error.
11
Rodgers, William N. "Land Cover Change and its Impacts on a Flash Flood-Producing Rain Event in Eastern Kentucky." TopSCHOLAR®, 2014. http://digitalcommons.wku.edu/theses/1363.
Full textAbstract:
Eastern Kentucky is a 35-county region that is a part of the Cumberland Plateau of the Appalachian Mountains. With mountaintop removal and associated land cover change (LCC) (primarily deforestation), it is hypothesized that there would be changes in various atmospheric boundary layer parameters and precipitation. In this research, we have conducted sensitivity experiments of atmospheric response of a significant flash flood-producing rainfall event by modifying land cover and topography. These reflect recent LCC, including mountaintop removal (MTR). We have used the Weather Research and Forecasting (WRF) model for this purpose. The study found changes in amount, location, and timing of precipitation. LCC also modified various surface fluxes, moist static energy, planetary boundary layer height, and local-scale circulation wind circulation. The key findings were the modification in fluxes and precipitation totals. With respect to sensible heat flux (H), there was an increase to bare soil (post-MTR) in comparison to pre-MTR conditions (increased elevation with no altered land cover). Allowing for growth of vegetation, the grass simulation resulted in a decrease in H. H increased when permitting the growth of forest land cover (LC) but not to the degree of bare soil. In regards to latent heat flux (LE), there was a dramatic decrease transitioning from pre-MTR to post-MTR simulations. Then with the subsequent grass and forest simulations, there was an increase in LE comparable to the pre-MTR simulation. Under pre-MTR conditions, the total precipitation was at its highest level overall. Then with the simulated loss of vegetation and elevation, there was a dramatic decrease in precipitation. With the grass LC, the precipitation increased in all areas of interest. Then forest LC was simulated allowing overall slightly higher precipitation than grass.
12
Vogt, Nathan. "Mechanisms of land-cover change in Uganda longer-term analyses of the role of institutional arrangements /." [Bloomington, Ind.] : Indiana University, 2005. http://wwwlib.umi.com/dissertations/fullcit/3167802.
Full textAbstract:
Thesis (Ph.D.)--Indiana University, School of Public Environmental Affairs, 2005.Source: Dissertation Abstracts International, Volume: 66-04, Section: B, page: 1961. Adviser: J. C. Randolph. "Title from dissertation home page (viewed Nov. 22, 2006)."
13
Kareddula, Sharon. "MONITORING AND QUANTIFYING THE ENVIRONMENTAL CHANGE DETECTION OF LAKE KOLLERU AND THE SURROUNDING MANDALS USING REMOTE SENSING TECHNIQUES." OpenSIUC, 2011. https://opensiuc.lib.siu.edu/theses/744.
Full textAbstract:
Land Use and Land Cover (LULC) are significantly being altered globally. Lake Kolleru, one of the largest fresh water lakes in India, located in the state of Andhra Pradesh, is one example of a wetland ecosystem that requires constant monitoring. It is known for its ecological, biological and hydrological functions. In the past few years this lake had undergone many significant changes resulting in its deterioration due to anthropogenic activities in and around it. Attempts to impede its degradation have been made in the recent past due to which it is slowly recuperating. However, human encroachments in the lake have not completely stopped after various restoration projects. The present study focuses on monitoring and quantifying the changes that have occurred in and around Lake Kolleru to gain a historical perspective by temporal analysis as well as to understand the present status. Land Use Land Cover class categories were defined as "Aquapond", "Agriculture", "Barrenland or non-crop or young crop", "Water logged marshy area" and "Residential or built-up area". The overall image classification accuracies for the years 1988, 1993, 2000, 2004 and 2010 were 65.6%, 72%, 69.2%, 66.8%, and 73.2%, respectively. High classification accuracy was observed for certain individual categories of interest. Poor classification accuracy was observed in categories of Water logged marshy area and Residential or built-up area accounting for high commission error, because of similar spectral reflectance. The Land Use Land Cover dynamics show, that there were significant changes in the temporal periods 1988-1993, 1993-2000, 2000-2004 and 2004-2010. There was a drastic increase of 44% in Aquapond category from 1988 to 2004 followed by a decrease of 18.5% by 2010. Agriculture was observed as declining throughout all the temporal periods. Barren land category was observed as decreasing until 2004 with a slight increase by 2010. Decreases in Agriculture and Barrenland or non-crop or young crop were due to their conversion to Aquapond. Similar results were interpreted by the land transformation processes. Anthropogenic activities such as extensive agriculture and aquaculture are the major driving factors influencing changes in Land Use Land Cover and land degradation in the Lake Kolleru study area. The limitations of this study were unavailability of aerial photos and high resolution spectral images such as PAN images from the Indian Remote Sensors due to budget consideration. The other major limitation was the lack of ground- truth data with field observations.
14
DeWalt, Heather A. "Evaluating 25 Years of Environmental Change Using a Combined Remote Sensing Earth Trends Modeling Approach: A Northern California Case Study." Ohio University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1320356566.
Full text
15
Logsdon, Miles G. "Modeling land cover change under conditions of multi-scaled spatial data : an application of landscape ecology in environmental planning /." Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/10823.
Full text
16
Ek, Edgar. "Monitoring Land Use and Land Cover Changes in Belize, 1993-2003: A Digital Change Detection Approach." Ohio University / OhioLINK, 2004. http://www.ohiolink.edu/etd/view.cgi?ohiou1102520727.
Full text
17
Santos, Chandler H. "Linking In-Situ Data with Remote Sensing to Analyze Tropical Glacier Stability and Retreat in the Cordillera Blanca, Peru." TopSCHOLAR®, 2016. http://digitalcommons.wku.edu/theses/1629.
Full textAbstract:
Glaciers are a major source of freshwater around the world, but they are melting at an increased rate due to atmospheric warming resulting from anthropogenic climate change. In addition to temperature increases, light-absorbing particulates on glaciers also are contributing to glacial melt. This research examines how black carbon, released into the air through partial combustion of biofuels, is affecting the surface albedo of glaciers. I also delineate possible sources of black carbon in the Cordillera Blanca region of Peru. Ground data were collected each year from 2011 to 2013 during the local dry season. Effective black carbon (eBC) values were determined using the Light Absorption Heating Method and satellite-derived albedo values were retrieved from NASA’s MODIS MOD10A1 data. Effective black carbon (eBC) values and albedo levels were moderately correlated, showing that albedo decreases with an increase of black carbon, and that this impact can be measured using satellite instruments. Values of eBC did not correlate with spatial proximity to mines, but did correlate with proximity to Huaraz, which likely is the major source of light-absorbing particulates in the region. Further research would benefit from a more extensive source dataset and surface albedo measurements over different seasons.
18
Michalek, Jeffrey L., Thomas W. Wagner, Joseph J. Luczkovich, and Richard W. Stoffle. "Multispectral Change Vector Analysis for Monitoring Coastal Marine Environments." Photogrammetric Engineering & Remote Sensing, 1993. http://hdl.handle.net/10150/296670.
Full textAbstract:
Documenting temporal changes to coastal zones is an essential part of understanding and managing these environments. The exclusive use of traditional surveying tools may not be practical for monitoring large, remote, or rapidly changing areas. This paper investigates the utility of multispectral Landsat Thematic Mapper satellite data for documenting changes to a Caribbean coastal zone using the change vector analysis processing technique. The area of study was the coastal region near the village of Buen Hombre on the north coast of the Dominican Republic. The primary habitats of interest were the intertidal mangrove for ests, and the shallow water seagrasses, macroalgae, and coral reefs. The change vector analysis technique uses any number of spectral bands from multidate satellite data to produce change images that yield information about both the magnitude and direction of differences in pixel values (which are proportional to radiance). The final products
were created by appending color-coded change pixels onto a black-and-white base map. The advantages and limitations of the technique for coastal inventories are discussed.
19
Martin, Kevin Scott. "Comparing Twenty-Four Years of Forest Change in Two Communities of Mexico's Meseta Purépecha Using Multi-Spectral Satellite Imagery." PDXScholar, 2004. https://pdxscholar.library.pdx.edu/open_access_etds/2428.
Full textAbstract:
The Meseta Purepecha, a volcanic plateau in the Mexican state of Michoacan, is home to one of the most species-rich pine forests in the world. Recent increases in demand for forest products has put added pressure on these resources. Though existing research has suggested significant deforestation in the Meseta, there is little information identifying specific areas of decline. This study focuses on two indigenous communities in the Meseta-Pichataro and Sevina. Both communities have long relied on wood as an economic resource. However, the two communities have reacted differently to increased demand for forest resources. The purpose of this study is to identify the differences in the rate and extent of forest change between Pichataro and Sevina.
Three dates of Landsat satellite images - 1976, 1986, and 2000-were used to identify changes in the Meseta's forests. Supervised classification was used to classify the 2000 image into forested and non-forested areas. Change detection was performed on the 1976 through 2000 images to identify areas of forest clearing and forest regrowth. The 2000 image was then used as a reference for generating maps of historic forest extent based on the change detection results.
Results show that between 1986 and 2000, Sevina cleared approximately 16% of its forested land between while Pichataro experienced a net gain of 7%. In the same period, 93% of the deforestation in the combined study area occurred within the community boundary of Sevina, which manages only 35% of the study area forests. Sevina's remaining forests are also more isolated and fragmented than the forests of Pichataro. The differences between the two communities appear related to management practices. Sevina has relied on larger-scale timber harvesting to derive economic benefits from its forests. Pichataro has focused on local harvesting and value-added production.
20
Grosse, Guido. "Characterisation and evolution of periglacial landscapes in Northern Siberia during the Late Quaternary remote sensing and GIS studies /." Phd thesis, [S.l.] : [s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=976726386.
Full text
21
van, Schaik Florian. "Global satellite data as proxies for urbanization in flood prone areas." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-353425.
Full textAbstract:
Delta regions are typically characterized by their high population density, low elevation, and risk of flooding. Long term planning and preparation is needed to mitigate the adverse effects of floods. Disaster management planning and flood protection measures require information about urbanization patterns, but this information is lacking in many parts of the world. Global satellite data could potentially aid or replace local urbanization data in such data scarce areas. This master thesis assesses the suitability of two global satellite datasets to serve as proxies for urbanization in flood prone areas: the Global Human Settlement (data for 1975, 1990, 2000 and 2014) and stable Nighttime Lights data series (annual data, 1992-2013). The assessment is performed through comparison of spatial-temporal urbanization trends of the global datasets with a previous study performed in the Netherlands using detailed local data. These spatial-temporal trends involve the share or urban area that is situated in flood prone zones and the average inundation depth. Through analysis based on Geographic Information Systems it was found that the Global Human Settlement data series indicates a stable increase in the percentage of urban area in flood prone zones from 31.60% in 1975 to 36.54% in 2014. Potentially, this increase results from the flood protection measures installed between 1954 and 1997. The Nighttime Lights data series shows values of around 36% throughout its time period, with no clear increase or decrease. These values are on average 15-17% higher over the whole time series than the values found with the use of the local data. The Global Human Settlements dataset shows values for the average inundation depth from 1.47m in 1975 to 1.72m in 2014, similar to the local data. The increase could be explained by the fact that only areas with higher inundation depths are available for urbanization. The Nighttime Lights does not show a clear trend with values ranging from 1.52m to 1.70m and large annual variation. Overall, the suitability of the Global Human Settlement dataset is higher than the stable Nighttime Lights dataset for this study area as it shows values more similar to the local data and does not require prerequisite threshold analysis, which is the case for the Nighttime Lights data.
22
Wheelock-Davis, Emily J. "Elevation Changes in Greenland over Two Decades from Cross-Platform LIDAR Analysis." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1366223499.
Full text
23
Rufin, Philippe [Verfasser], Patrick [Gutachter] Hostert, Claudia [Gutachter] Künzer, and Volker [Gutachter] Radeloff. "A global to regional scale assessment of dam-induced agricultural change by means of remote sensing / Philippe Rufin ; Gutachter: Patrick Hostert, Claudia Künzer, Volker Radeloff." Berlin : Humboldt-Universität zu Berlin, 2019. http://d-nb.info/1191174360/34.
Full text
24
Muñoz, Gamboa Paola Sofía. "Assessing Management of Nicaragua’s Caribbean Region Protected Areas Using Remote Sensing: The Indio Maíz Biological Reserve." Ohio University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1628265519609002.
Full text
25
Shim, Changsub. "Constraining global biogenic emissions and exploring source contributions to tropospheric ozone modeling applications /." Diss., Available online, Georgia Institute of Technology, 2006, 2006. http://etd.gatech.edu/theses/available/etd-06222006-060856/.
Full textAbstract:
Thesis (Ph. D.)--Earth and Atmospheric Sciences, Georgia Institute of Technology, 2007.Wang Yuhang, Committee Chair ; Cunnold Derek, Committee Member ; Weber Rodney, Committee Member ; Nenes Athanasios, Committee Member ; Guillas Serge, Committee Member.
26
Tigges, Jan. "Assessing carbon in urban trees: benefits of using high-resolution remote sensing." Doctoral thesis, Humboldt-Universität zu Berlin, 2017. http://dx.doi.org/10.18452/18597.
Full textAbstract:
Vorliegende Arbeit zeigt die jüngsten Möglichkeiten hochauflösender Fernerkundung am Beispiel von Stadtbäumen in Berlin, Deutschland. Es wurden neuste methodische Ansätze eingesetzt, wie beispielsweise maschinelles Lernens und individuelle Baumdetektion. Sie erwiesen sich von großem Vorteil für die detaillierte Analyse urbaner Ökosystemdienstleistungen in einer heterogenen Umwelt. Neueste Fernerkundung von hoher zeitlicher Auflösung hat Möglichkeiten gezeigt, Veränderungen des Stadtwaldes präziser zu untersuchen. Diesbezüglich konnten Baumspezies klassifiziert werden auf Grundlage saisonaler Veränderungen, die mittels Fernerkundungsdaten aufgenommen wurden. Dies ist für den urbanen Bereich einmalig und über große Flächen noch nicht durchgeführt worden. Darüber hinaus haben diese Baumarten einzelnen Bäumen zugeordnet werden können, deren Abmessung fernerkundlich erfasst worden ist. Diese neu erzeugten Umweltinformationen einzelner Bäume können damit verbundene urbane Ökosystemdienstleistungen präzise aktualisieren. Zum Beispiel haben so Unsicherheiten in der Schätzung zur Kohlenstoffspeicherung städtischer Wälder reduziert werden können. Es ist zudem von Vorteil gewesen, den gegenwärtigen Mangel an räumlich expliziten dreidimensionalen Informationen über Stadtwälder anzusprechen. Allerdings ist die Rolle städtischen Wälder, das Treibhausgas CO2 langfristig auszugleichen, immer noch wenig untersucht. Gerade der Mangel an präzisen, konsistenten und aktuellen Details führt zu großen Unsicherheiten im Rahmen von Lebenszyklus-Analysen. Auf Grund des aktuellen Fortschritts in hochauflösender Fernerkundung könnten diese Unsicherheiten reduziert werden. Dazu werden Möglichkeiten ausgiebig kritisch bewertet und anhand einer Lebenszyklus-Analyse am Beispiel Berlin andiskutiert, inwieweit sie präzisere langfristige Prognosen zum Stadtwald als Kohlenstoffspeicher liefern.This work shows recent options for implementing high resolution remote sensing in assessing urban trees in Berlin, Germany. State-of-the-art methodological approaches like machine learning and individual tree detection proved to be highly advantageous for analyzing details of urban ecosystem services within a heterogeneous urban environment. Recent remote sensing of high temporal resolution offers new options for more precisely addressing urban forest dynamics. This successfully shows that tree species could be identified from seasonal changes of remotely sensed imagery, though this has not yet been applied across cities. Furthermore, these tree species results could be combined with remotely sensed individual tree dimensions. This newly generated data can be suggested to update spatially explicit information on related urban ecosystem services. For example, this could reduce the uncertainties of such estimates as urban forest carbon storage, and also address the present lack of spatially explicit three-dimensional information on urban forests. However, few studies have considered the local scale of urban forests to effectively evaluate their potential long-term carbon offset. The lack of precise, consistent and up-to-date forest details is challenging within the scope of life cycle assessments. This can cause high uncertainties in urban forest carbon offset. Although, recent progress in high resolution remote sensing is promising to reduce these uncertainties. For this purpose, remote sensing options are extensively reviewed and briefly discussed using an example of life cycle assessment for Berlin, which allow more precise long-term prognoses of urban forest carbon offset.
27
Wu, Jin. "How do Amazonian Tropical Forest Systems Photosynthesize under Seasonal Climatic Variability: Insights from Tropical Phenology." Diss., The University of Arizona, 2015. http://hdl.handle.net/10150/594653.
Full textAbstract:
Amazonian evergreen forests are of broad interest, attributable to their ecological, economic, aesthetic, and cultural importance. However, their fate under climate change remains uncertain, largely due to unclear mechanisms in regulating tropical photosynthetic metabolism. Understanding mechanistic controls on these dynamics across time scales (e.g. hours to years) is essential and a prerequisite for realistically predicting tropical forest responses to inter-annual and longer-term climate variation and change. Tropical forest photosynthesis can be conceptualized as being driven by two interacting causes: variation due to changes in environmental drivers (e.g. solar radiation, diffuse light fraction, and vapor pressure deficit) interacting with model parameters that govern photosynthetic behavior, and variation in photosynthetic capacity (PC) due to changes in the parameters themselves. In this thesis, I aim to reveal photosynthetic controls by addressing three fundamental but complementary questions: (1) What are the mechanisms by which the subtle tropical phenology exert controls on tropical photosynthetic seasonality? (2) How do the extrinsic and intrinsic controls regulate the photosynthesis processes at hourly to interannual time scales in an Amazonian evergreen forest? (3) Are there sufficiently consistent relations among leaf traits, ages, and spectra that allow a single model predict the leaf aging process of Amazonian evergreen trees? To address question 1, I firstly show that seasonal change in ecosystem-scale photosynthetic capacity (PC), rather than environmental drivers, is the primary driver of seasonality of gross primary productivity (GPP) at four Amazonian evergreen forests spanning gradients in rainfall seasonality, forest composition, and flux seasonality. Using novel near-surface camera-detected leaf phenology to drive a simple leaf-cohort canopy model at two of these sites, I further show that leaf ontogeny and demography explain the changes in ecosystem photosynthetic capacity. The coordination of new leaf growth and old leaf divestment (litterfall) during the dry season shifts canopy composition towards younger leaves with higher photosynthetic capacity, driving large seasonal increases (~27%) in ecosystem photosynthetic capacity. To address question 2, I used the 7-year eddy covariance (EC) measurements in an Amazonian tropical evergreen forest. I used a statistical model to partition the variability of 7-year EC-derived GPP into two main causes: variation due to changes in extrinsic environmental drivers and variation in intrinsic PC. The fitted model well predicts variability in EC-derived GPP at hourly (R²=0.71) to interannaul (R²=0.81) timescales. Attributing model predictions to causal factors at different timescales, I find that ~92% of the variability in modeled hourly GPP could be attributed to environmental driver variability, and ~5% to variability in PC. When aggregating the modeled GPP into the annual time-step, the attribution is reversed (only ~4% to environment and ~91% to PC). These results challenge conventional approaches for modeling evergreen forests, which neglect intrinsic controls on PC and assume that the primary photosynthetic control at both long and short timescales is due to changes in the hourly-to-diurnal environment on the physiological phenotype. This work thus highlights the importance of accounting for differential regulation of different components of GPP at different timescales, and of identifying the underlying feedbacks and adaptive mechanisms which regulate them. To address question 3, I explored the potential for a general spectrally based leaf age model across tropical sites and within the vertical canopy profiles using a phenological dataset of 1831 leaves collected at two lowland Amazonian forests in Peru (12 species) and Brazil (11 species). This work shows that a simple model (parameterized using only Peruvian canopy leaves) successfully predicts ages of canopy leaves from both Peru (R²=0.83) and Brazil (R²=0.77), but ages for Brazilian understory leaves with significantly different growth environment and leaf trait values have lower prediction accuracy (R²=0.48). Prediction accuracy for all Brazilian samples is improved when information on growth environment and leaf traits were added into the model (5% R² increase; R²=0.69), or when leaves from the full range of trait values are used to parameterize the model (15% R² increase; R²=0.79). This work shows that fundamental ecophysiological rules constrain leaf traits and spectra to develop consistently across species and growth environment, providing a basis for a general model associating leaf age with spectra in tropical forests. In sum, in this thesis, I (1) conceptualize photosynthesis as being driven by two interacting dynamics, extrinsic and intrinsic, (2) propose and validate a model for biological mechanisms that mediate seasonal dynamics of tropical forest photosynthesis, (3) assess and quantify the factors controlling tropical forest photosynthesis on timescales from hourly to interannual, and (4) develop a general model for monitoring leaf aging processes of tropical trees across sites and growth environments. The revealed mechanisms (and proposed models) in this thesis greatly improve our mechanistic understanding of the photosynthetic and phenological processes in tropical evergreen forests. Strategic incorporation of these mechanisms will improve ecological, evolutionary and earth system theories describing tropical forests structure and function, allowing more accurate representation of forest dynamics and feedbacks to climate in earth system models.
28
Hesping, Malena. "Remote sensing-based land cover classification and change detection using Sentinel-2 data and Random Forest : A case study of Rusinga Island, Kenya." Thesis, Linköpings universitet, Tema Miljöförändring, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166749.
Full textAbstract:
Healthy forests and soils are crucial for the very existence of mankind as they provide food, clean water and air, shade and protection against floods and storms. With their photosynthetic carbon storage ability, they mitigate climate change and fertilise and stabilise soils. Unfortunately, deforestation and the loss of fertile soils are the bleak reality and among the world’s most pressing challenges. Over the past decades Kenya has faced severe deforestation, but efforts are being undertaken to reverse deforestation, revegetate degraded land and combat erosion. Satellite remote sensing technology becomes increasingly useful for vegetation monitoring as the data quality improves and the costs decrease. This thesis explores the potential of free open access Sentinel-2 data for vegetation monitoring through Random Forest land cover classification and post-classification change detection on Rusinga Island, Kenya. Different single-date and multi-temporal predictor datasets differentiating respectively between five and four classes were examined to develop the most suitable model. The classification achieved acceptable results when assessed on an independent test dataset (overall accuracy of 90.06% with five classes and 96.89% with four classes), which should however be confirmed on the ground and could potentially be improved with better reference data. In this study, change detection could only be analysed over a time frame of two years, which is too short to produce meaningful results. Nevertheless, the method was proven conceptually and could be applied in the future to monitor land cover changes on Rusinga Island.
29
Grift, Jeroen. "Forest Change Mapping in Southwestern Madagascar using Landsat-5 TM Imagery, 1990 –2010." Thesis, Högskolan i Gävle, Samhällsbyggnad, GIS, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-22606.
Full textAbstract:
The main goal of this study was to map and measure forest change in the southwestern part of Madagascar near the city of Toliara in the period 1990-2010. Recent studies show that forest change in Madagascar on a regional scale does not only deal with forest loss, but also with forest growth However, it is unclear how the study area is dealing with these patterns. In order to select the right classification method, pixel-based classification was compared with object-based classification. The results of this study shows that the object-based classification method was the most suitable method for this landscape. However, the pixel-based approaches also resulted in accurate results. Furthermore, the study shows that in the period 1990–2010, 42% of the forest cover disappeared and was converted into bare soil and savannahs. Next to the change in forest, stable forest regions were fragmented. This has negative effects on the amount of suitable habitats for Malagasy fauna. Finally, the scaling structure in landscape patches was investigated. The study shows that the patch size distribution has long-tail properties and that these properties do not change in periods of deforestation.
30
Ndlovu, Nomzamo Bonisiwe. "Quantifying indigenous forest change in Dukuduku from 1960 to 2008 using GIS and remote sensing techniques to support sustainable forest management planning." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/85622.
Full textAbstract:
Thesis (MSc)--Stellenbosch University, 2013.ENGLISH ABSTRACT: This study aimed to understand how Dukuduku Forest in Kwa-Zulu Natal has changed from 1960 to 2008 and whether the change in political regimes, during and post apartheid eras might have contributed to changes in forest extent. To achieve the aims, the following analyses were made: - Qualitative and quantitative spatial analyses of forest change; - Analyses of the correspondence of change with political changes in the country; - Assessment of perception of people living in the Dukuduku forest area. The Dukuduku land cover was mapped from aerial photos using ArcGIS 9.3 to determine whether or not there has been a significant change in the area from 1960-2008, in response to resource use pressures and to come up with the strategic sustainable management plan from the results found. Five aerial photographs were used to determine the changes in land cover from the year: 1960, 1970, 1992, 2005 and 2008. The Land cover types were classified into four classes, Indigenous Forests, Plantation Forests, Water Bodies and Other (open areas, cultivated land, and all the human disturbed and transformed land). The percentage of cover per class was compared across the years to determine overall change in land cover and the rate of change per year was also calculated. The results from the study showed that: - Natural Forest increased by 11% (700 ha), at the rate of 20.56 hectares per year between 1960 and 1992, which is the apartheid era. Between 1992 and 2008, the democratic era, the forest decreased by 34.4% (2472.31ha), at the rate of 168 hectares per year. - The Dukuduku forest community gains resources (timber and grass for construction, art, firewood, medicinal plants, grazing of livestock and food) from the forest. The people are willing to contribute in protecting the forest only if the governing authorities would include them in decisions made, as the NFA demands Participatory Forest Management, but which does not currently exist in Dukuduku.
AFRIKAANSE OPSOMMING: Hierdie studie ondersoek die verandering van die Dukuduku woud in Kwa-Zulu Natal vanaf 1960 tot 2008, en vernaamlik of die verandering in politieke regimes tydens en in die postapartheid eras tot verandering bygedra het in die woud se vorm. Om hierdie doelwitte te breik is die volgende analises gedoen: - Kwalitatiewe en kwantitatiewe ruimtelike analises van woudverandering; - Analises van die korrelasie tussen hierdie fisiese omgewingsverandering en politieke verandering in die land; - Analise van die persepsie van mense wat in die Dukuduku woudgebied woon. Die Dukuduku gronddekking is gekarteer met behulp van lugfotos, waarvoor ArcGIS 9.3 gebruik is om te bepaal of daar noemenswaardige verandering in die gebied plaasgevind het van 1960 tot 2008, in reaksie op hulpbrongebruike, en om ‘n volhoubare bestuursplan gestel voor wat op die bevindinge gebaseer is. Vyf lugfotos is gebruik om verandering in gronddekking te bepaal vir die jare: 1960, 1970, 1992, 2005 en 2008. Die Gronddekking tipes is geklassifiseer in vier klasse naamlik Inheemse Woude, Plantasiebosse, Waterliggame en Ander (oop gebiede, landerye en al die mens-versteurde en getransfomeerde gebiede). Die persentasie van elke dekkingsklas is oor die jare vergelyk om die verandering in algehele grond-dekking te bepaal, en die tempo van verandering is ook bepaal, asook die tempo van verandering. Die resultate van die studie wys dat: - Die natuurlike woud toegeneem het met 11% (700 ha), teen ‘n tempo van 20.56 hektaar per jaar tussen 1960 en 1992, tgedurende die apartheidsera. Tussen 1992 en 2008, die demokratiese era, het die woude verminder met 34.4% (2472.31 ha), teen ‘n tempo van 168 hektaar per jaar. - Die gemeenskap wat in die Dukuduku woud woon verkry hulpbronne van die woud (hout en gras vir konstruksie, kuns, brandhout, medisinale plante, weiding vir vee, en voedsel). Die mense is gewillig om by te dra tot beskerming van die woud indien die owerhede hulle sou betrek in besluite wat geneem word, veral omdat die nasionale Wet op Bosse voorsiening maak vir Deelnemende Bosbestuur, wat tans nie by Dukuduku gebeur nie.
31
Grecchi, Rosana Cristina. "Land-use and environmental changes in the Cerrados of South-Eastern Mato Grosso - Brazil." Thèse, Université de Sherbrooke, 2011. http://savoirs.usherbrooke.ca/handle/11143/2833.
Full textAbstract:
The human-induced changes of the Earth's land surfaces have been unprecedented, with outcomes often indicating degradation and loss of environmental quality. Mato Grosso State in Brazil, location of the study area, underwent extensive land-use and land-cover changes in recent decades with the rates, patterns and consequences poorly documented until now. In this context, the aim of the present research is to propose a multidisciplinary approach for quantifying historical land-use and environmental changes in the southeast part of this State, where the Cerrado biome (Brazilian savannas) has been intensively converted into agricultural lands. The methodology includes three parts: remote sensing change detection, land vulnerability mapping, and identification of key environmental indicators. Land-use/cover information was extracted from a temporal remote sensing dataset using an object-oriented classification approach, and the changes quantified employing a post-classification method. In addition, the study area was assessed for its vulnerabilities, focusing mainly on erosion risks, wetlands, and areas with limited or no suitability for crops. Finally, key environmental indicators were identified from the preceding steps and analyzed within the Organisation for Economic Co-operation and Development (OECD) Pressure-State-Response (PSR) framework. The results provided an improved mapping of the Cerrados natural vegetation conversion into crops and pastures, and indicate that the Cerrado vegetation was intensively converted and also became more fragmented in the time frame studied. Between 1985 and 2005 the area lost approximately 6491 km 2 of Cerrados (42 %). Modeling based on the Universal Soil Loss Equation indicated significant increase in erosion risk from 1985 to 2005 mainly related to the increase in crop areas and the crops' encroachment into more fragile lands.The identification of environmental indicators rendered complex environmental information more generally accessible by structuring it within the PSR framework.The indicators captured key information about land-use and environmental changes in the area, showing that agricultural expansion is the major human activity exerting pressure on natural resources at a landscape scale, and that the pattern of change included high rates of crop expansion and the use of fragile environments such as wetlands and sandy erodable soils.
32
Klintenberg, Patrik. "More Water, Less Grass? : An assessment of resource degradation and stakeholders’ perceptions of environmental change in Ombuga Grassland, Northern Namibia." Doctoral thesis, Stockholm : Department of Physical Geography and Quaternary Geology, Stockholm University, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-6707.
Full text
33
Lange, Priscila Kienteca. "Putting marine microbes on the map : determining the global distribution of marine picophytoplankton using a combination of satellite and field data." Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:ae64c955-336e-46b2-bee1-db41fb4be1c9.
Full textAbstract:
Picophytoplanktonic cells (0.2-2 μm) are the dominant phytoplankters in the largest marine biomes on Earth: the subtropical gyres. The overaching aim of this thesis is to develop algorithms that use remote-sensing observables to map the distribution of the smallest and most abundant member of picophytoplankton, Prochlorococcus, and assess its contribution to the marine carbon cycle. To understand how the photoacclimatory status and growth of Prochlorococcus and its sister genera Synechococcus are influenced by light and nutrients, experiments were conducted in the South Atlantic Gyre (SAG). Results from the manipulation experiments show that, in the central region of the SAG, nutrient addition can induce marked changes in the optical properties of Prochlorococcus cells when subjected to saturating light levels, leading to a decrease in cell abundance, whereas at the gyre periphery no substantive changes in cell growth or optical characteristics were observed. Since light plays a central role in shaping the distribution of cyanobacteria, an empirical algorithm based on relationships between Prochlorococcus abundance and remotely-sensed observables was developed. The outputs were then used in a modified primary production model to predict the vertical distribution of carbon fixation by Prochlorococcus. The models estimate that ∼ 3.4 x 1027 Prochlorococcus cells in the global ocean fix 4.7 Gt C year-1. Most of the cell biomass and primary productivity is concentrated in the subtropical gyres and areas near the Equatorial Convergence, and 61% of the carbon fixation occurs in the upper water column (0-45 metres), where only 43% of the cells reside. However, in the gyres, carbon fixation is highest (62%) in deeper layers (45-200m), and both cell abundance and carbon fixation show marked seasonal patterns. The models developed in this study provide an unprecedented view of the vertical distribution of Prochlorococcus cells and their corresponding rates of carbon fixation in the global ocean.
34
Yoon, Yeosang. "Evaluation of the potential to estimate river discharge using measurements from the upcoming SWOT mission." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1376480417.
Full text
35
Guo, Qiandong. "A Comparative Study on Coastal Zone Changes and Anthropogenic Impacts between Tampa Bay, USA, and Xiangshan Harbor, China, during the Last 30 Years." Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7292.
Full textAbstract:
Currently, the U.S. and China are the two largest national economic entities in the world. However, it is noticeable that the two countries have considerably different strategies for economic development, environmental protection and land supply in coastal zones. In order to understand the coastline dynamics, land use land cover (LULC) changes and land management policies in the U.S. and China, a case study of the Tampa Bay (TB) watershed, Florida, U.S., and Xiangshan Harbor (XH), Zhejiang Province, China was conducted. The two areas possess similar humid subtropical climate and dense population, but experienced different anthropogenic impacts. TB sat at a developed stage with sound environmental laws, regulations and projects to preserve natural landscapes. XH was at a developing stage and focused more on an economic development in the last 30 years. Comparing the LULC change patterns and the major driving forces for the changes between the two study areas, governments and public could know what factors cause the land use conversion and how to preserve the natural landscapes. A new water index called the weighted normalized water index (WNDWI) was proposed to extract coastlines in TB and XH since current water indices could not classify turbid water bodies and shadow areas well. Two threshold methods (i.e., Otsu threshold method and multiple thresholds method) were implemented to find an optimal threshold to segment the water from the land. The experiments demonstrate that the WNDWI algorithm can achieve high accuracies to classify water from land with an optimal threshold in the two study sites. Coastlines in 1985, 1995, 2005 and 2015 in TB and XH were extracted and the changes were detected and highlighted. The results indicate that coastlines in TB were mostly stable, while those in XH had been undergoing intensive human interferences, indicating that XH was at a developing stage. Major anthropogenic impacts on XH coastlines are land reclamation and aquaculture, resulting in an impacted area of approximately 20.3 km2. The land cover maps of TB and XH in 1985 (1986), 1995, 2005 and 2015 were produced by classifying Landsat images using the random forest algorithm. The reflectance distributions of the land cover types indicate that it is difficult to classify agricultural land, rangeland, upland forest and wetland if using the optical bands only from a single Landsat image. Multi-seasonal image composites and the land surface temperature (LST) band were involved in image classification to achieve higher accuracies. The overall accuracies (OAs) of the land cover map of TB in 2015 and that of XH in 2005 were increased by 5.14% and 4.33% after adding the LST band. The OAs of the four years’ land cover maps of TB range from 81.14% to 83.43%, whereas those of XH vary from 84.67% to 87.67%. According to the experimental results, the total urban area increased by 11.8% in TB, while that in XH increased 138.9% during the last 30 years. Wetland in TB reduced by 8.3% while that in XH reduced 49.0%. The results of logistic regression analysis indicated that the density of wetland is a major driver for urban growth in TB with a strong negative impact while the relationship is opposite in XH. It is worth noting that XH has been undergoing a rapid urbanization and industrialization process with a vast amount of natural landscapes converted to urban areas, whereas TB has already passed the developing stage and issued environmental laws and programs to preserve natural landscapes from human exploitation. In terms of preserving natural landscapes and protecting the vulnerable coastal environment for our next generation, the coastal planning decision makers in XH should not only consider economic values and short-term benefits but also integrate values of ecological, social, and cultural and long-term benefits when making coastal management decisions.
36
Sena, Elisa Thomé. "Variabilidade espacial e temporal da forçante radiativa direta de aerossóis de queimadas e os efeitos da mudança de uso do solo na Amazônia." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/43/43134/tde-07102014-154346/.
Full textAbstract:
Medidas simultâneas dos sensores CERES (Clouds and the Earths radiant Energy System) e MODIS (Moderate Resolution Imaging Spectrometer), a bordo do satélite Terra, da NASA foram utilizadas para avaliar o impacto do desflorestamento no balanço radiativo em larga escala na Amazônia durante as estações secas de 2000 a 2009. Este impacto é decorrente da emissão de partículas de queimadas, mudanças nas características de superfície e na quantidade de vapor dágua na coluna atmosférica. A forçante radiativa direta de aerossóis de queimadas e a forçante radiativa de mudança de albedo de superfície, devida ao desflorestamento na Amazônia, foram calculadas a partir de duas diferentes metodologias. O primeiro método calcula a média da forçante para toda a estação seca, através da regressão da irradiância no topo da atmosfera (TOA) versus a profundidade óptica de aerossóis. O segundo método calcula a forçante diária a partir das irradiâncias medidas no TOA e da geometria de iluminação. Um código de transferência radiativa, em conjunto com o produto de funções de distribuição de refletância bidirecional (BRDF) do MODIS e medidas de propriedades ópticas de aerossóis de queimadas da rede AERONET, foram utilizados para expandir as forçantes radiativas instantâneas, calculadas no horário de passagem do satélite, em médias diárias. A média diária da forçante radiativa direta no TOA para o período estudado, foi de - 8,2 ± 2,1 W/m² e -5,2 ± 2,6 W/m², dependendo da metodologia utilizada. As distribuições espaciais da forçante radiativa direta de aerossóis sobre a região amazônica mostram que, para altas concentrações de aerossóis, a média diária da forçante radiativa no TOA pode alcançar até -30 W/m². Observamos também que a refletância da superfície influencia fortemente o efeito radiativo direto de aerossóis. O impacto dos aerossóis sobre diferentes tipos de superfície foi analisado, indicando que a forçante radiativa é sistematicamente mais negativa sobre floresta do que sobre cerrado. A média anual da forçante radiativa de mudança de albedo de superfície devida ao desflorestamento em Rondônia foi determinada, a partir das duas diferentes metodologias, em -7,4 ± 0,9 W/m² e -8,1 ± 1,0 W/m², respectivamente. As partículas de queimadas impactam o balanço radiativo por aproximadamente 2 a 3 meses por ano, enquanto o impacto do albedo de superfície pode ser observado ao longo de todo o ano. Esta diferença, devida à sazonalidade da estação de queimadas, indica que a média anual do impacto da mudança de albedo de superfície sobre o balanço radiativo amazônico é muito maior do que o impacto anual dos aerossóis de queimadas. A influência do desmatamento na quantidade de vapor dágua atmosférico e seu impacto no balanço radiativo foi analisada a partir de medidas de vapor dágua integrado na coluna atmosférica obtidas pelos radiômetros solares da AERONET. Estas medidas mostram que a quantidade de vapor dágua integrado na coluna atmosférica é 0,35 cm (cerca de 10% do total) menor sobre áreas desmatadas do que sobre áreas de florestas preservadas. O efeito desta redução na quantidade de vapor dágua atmosférico contribui para aumentar o fluxo radiativo de ondas curtas ascendente no TOA. Os altos valores de forçante obtidos neste trabalho indicam que o desflorestamento pode ter forte implicação para a convecção, desenvolvimento de nuvens e para a razão entre radiação direta e difusa.Simultaneous CERES (Clouds and the Earth\'s Radiant Energy System) and MODIS (Moderate Resolution Imaging Spectrometer) sensors retrievals were used to calculate the changes in radiation fluxes resulting from deforestation in the Amazon during the peak of the biomass burning seasons from 2000 to 2009. The energy balance of the region is modified by the emission of biomass burning aerosols, changes in surface properties and in the atmospheric water vapor column. The direct radiative forcing (RF) of biomass burning aerosols and the RF due to surface albedo changes, triggered by deforestation in the Amazonia, were calculated using two different methodologies. The first method calculates the average forcing for the whole dry season using a regression of fluxes in the top of the atmosphere (TOA) versus the aerosol optical depth. The second method calculates the daily forcing from the irradiances at the TOA and the illumination geometry. MODIS\'s bidirectional reflectance distribution functions (BRDF) product and biomass burning aerosol properties retrieved by AERONET were used in a radiative transfer code, to expand the instantaneous radiative forcing values, obtained during the satellite overpass, into 24-hour RF average. The mean direct RF of aerosols at the TOA during the biomass burning season for the 10-year period was -8.2 ± 2.1 W/m² and -5.2 ± 2.6 W/m², depending on the two methodologies applied. The spatial distributions of the direct radiative forcing of aerosols over the Amazon Basin show that for high concentrations of aerosols, the daily average of the RF at the TOA can reach up to -30 W/m². The surface reflectance strongly influences the direct RF of aerosols. The impact of aerosols over different surface types was analyzed, indicating that the RF is systematically more negative over forest than over cerrado areas. The mean annual land use change RF, due to deforestation, in Rondonia was determined as -7.4 ± 0.9 W/m² and -8.1 ± 1.0 W/m², using the two different methodologies. Biomass burning aerosols impact the radiative budget for approximately 2-3 months per year, whereas the surface albedo impact is observed throughout the year. Because of this difference, the estimated impact in the Amazonian annual radiative budget due to surface albedo change is much higher than the annual impact due to aerosol emissions. The influence of deforestation in the atmospheric water vapor content, and its impact in the radiative budget, was assessed using water vapor column measurements obtained by AERONET sunphotometers. It was observed that the column water vapor is on average smaller by about 0.35 cm (around 10% of the total column water vapor) over deforested areas compared to forested areas. The effect of reducing atmospheric water vapor column contributes to an increase in the upward shortwave radiative flux at the TOA. The large radiative forcing values obtained in this work indicate that deforestation have strong implications on convection, cloud development and the ratio of direct and diffuse radiation, which impacts the carbon uptake by the forest, therefore, changing the photosynthetic rate.
37
Spencer, David A. "A historical record of land cover change of the lesser prairie-chicken range in Kansas." Thesis, Kansas State University, 2014. http://hdl.handle.net/2097/18694.
Full textAbstract:
Master of ScienceDepartment of Geography
Melinda Daniels
The Lesser Prairie-Chicken (Tympanuchus pallidicinctus) is a prairie grouse of conservation concern in the Southern Great Plains. In response to declining population numbers and ongoing threats to its habitat, the Lesser Prairie-Chicken was listed as threatened under the Endangered Species Act in May 2014. In western Kansas, the Lesser Prairie-Chicken occupies the Sand Sagebrush Prairie, Mixed-grass Prairie, and Short-grass/CRP Mosaic Ecoregions. Since the beginning of the 20th century, the overall range and population has declined by 92% and 97% respectively. Much of this decline is attributed to the loss and fragmentation of native grasslands throughout the Lesser Prairie-Chicken range. Whereas much of the loss and degradation of native grassland have been attributed to anthropogenic activities such as conversion of grassland to cropland and energy exploration, federal legislation since the 1980s to convert cropland on highly erodible soils to perennial grasses through the U.S. Department of Agriculture (USDA) Conservation Reserve Program (CRP) may curtail or reverse these trends. My objective was to document changes in the areal extent and connectivity of grasslands in the identified Lesser Prairie-Chicken range in Kansas from the 1950s to 2013 using remotely sensed data. I hypothesized that the total amount of grassland decreased between the 1950’s and 2013 because of an increase in agricultural practices, but predicted an increase of grassland between 1985 and 2013 in response to the CRP. To document changes in grassland, land cover maps were generated through spectral classification of LANDSAT images and visual analysis of aerial photographs from the Army Map Service and USDA Farm Service Agency. Landscape composition and configuration were assessed using FRAGSTATS to compute a variety of landscape metrics measuring changes in the amount of grassland present as well as changes in the size and configuration of grassland patches. Since 1985, the amount of grassland in the Lesser Prairie-Chicken range in Kansas has increased by 210,9963.3 ha, a rise of 11.9%, while the mean patch size and area-weighted mean patch size of grassland increased 18.2% and 23.0% respectively, indicating grassland has become more connected during this time in response to the CRP. Prior to the implementation of CRP, the amount of grassland had been decreasing since 1950, as 66,722.0 ha of grassland was converted to croplands. The loss of grassland had a considerable effect on the patch size of grasslands, as mean patch size and area-weighted mean patch size decreased by 8.8% and 11.1% respectively. The primary driver of grassland loss between 1950 and 1985 was the emergence of center pivot irrigation, which had its greatest impact in western and southwestern parts of the range in Kansas. In particular, while the amount of grassland in Range 5, a region of the Lesser Prairie-Chicken range found in southwest Kansas, has increased overall since the 1950s by 4.7%, the area-weighted mean patch size has decreased by 53.0% in response to center pivot irrigation fragmenting the landscape. While the CRP has been successful in increasing and connecting grassland throughout the Lesser Prairie-Chicken range to offset the loss of grassland since the 1950s, continuation of the CRP faces an uncertain future in the face of rising commodity prices, energy development, and reduction in program scope leaving open the possibility that these areas that have created habitat for Lesser Prairie-Chickens could be lost. As time progresses, a reduction in the scope of the CRP would reduce the amount of habitat available to Lesser Prairie-Chickens, threatening the persistence of their population.
38
Wohlfart, Christian [Verfasser], Claudia [Gutachter] Künzer, Christopher [Gutachter] Conrad, and Roland [Gutachter] Baumhauer. "The Yellow River Basin in Transition - Multi-faceted Land Cover Change Analysis in the Yellow River Basin in the Context of Global Change Using Multi-sensor Remote Sensing Imagery / Christian Wohlfart ; Gutachter: Claudia Künzer, Christopher Conrad, Roland Baumhauer." Würzburg : Universität Würzburg, 2018. http://d-nb.info/1162444460/34.
Full text
39
Cai, Zipan. "Multitemporal Satellite Data for Monitoring Urbanization in Nanjing from 2001 to 2016." Thesis, KTH, Geoinformatik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-214036.
Full textAbstract:
Along with the increasing rate of urbanization takes place in the world, the population keeps shifting from rural to urban areas. China, as the country of the largest population, has the highest urban population growth in Asia, as well as the world. However, the urbanization in China, in turn, is leading to a lot of social issues which reshape the living environment and cultural fabric. A variety of these kinds of social issues emphasize the challenges regarding a healthy and sustainable urban growth particularly in the reasonable planning of urban land use and land cover features. Therefore, it is significant to establish a set of comprehensive urban sustainable development strategies to avoid detours in the urbanization process. Nowadays, faced with such as a series of the social phenomenon, the spatial and temporal technological means including Remote Sensing and Geographic Information System (GIS) can be used to help the city decision maker to make the right choices. The knowledge of land use and land cover changes in the rural and urban area assists in identifying urban growth rate and trend in both qualitative and quantitatively ways, which provides more basis for planning and designing a city in a more scientific and environmentally friendly way. This paper focuses on the urban sprawl analysis in Nanjing, Jiangsu, China that being analyzed by urban growth pattern monitoring during a study period. From 2001 to 2016, Nanjing Municipality has experienced a substantial increase in the urban area because of the growing population. In this paper, one optimal supervised classification with high accuracy which is Support Vector Machine (SVM) classifier was used to extract thematic features from multitemporal satellite data including Landsat 7 ETM+, Landsat 8, and Sentinel-2A MSI. It was interpreted to identify the existence of urban sprawl pattern based on the land use and land cover features in 2001, 2006, 2011, and 2016. Two different types of change detection analysis including post-classification comparison and change vector analysis (CVA) were performed to explore the detailed extent information of urban growth within the study region. A comparison study on these two change detection analysis methods was carried out by accuracy assessment. Based on the exploration of the change detection analysis combined with the current urban development actuality, some constructive recommendations and future research directions were given at last. By implementing the proposed methods, the urban land use and land cover changes were successfully captured. The results show there is a notable change in the urban or built-up land feature. Also, the urban area is increased by 610.98 km2 while the agricultural land area is decreased by 766.96 km2, which proved a land conversion among these land cover features in the study period. The urban area keeps growing in each particular study period while the growth rate value has a decreasing trend in the period of 2001 to 2016. Besides, both change detection techniques obtained the similar result of the distribution of urban expansion in the study area. According to the result images from two change detection methods, the expanded urban or built-up land in Nanjing distributes mainly in the surrounding area of the central city area, both side of Yangtze River, and Southwest area. The results of change detection accuracy assessment indicated the post-classification comparison has a higher overall accuracy 86.11% and a higher Kappa Coefficient 0.72 than CVA. The overall accuracy and Kappa Coefficient for CVA is 75.43% and 0.51 respectively. These results proved the strength of agreement between predicted and truth data is at ‘good’ level for post-classification comparison and ‘moderate’ for CVA. Also, the results further confirmed the expectation from previous studies that the empirical threshold determination of CVA always leads to relatively poor change detection accuracy. In general, the two change detection techniques are found to be effective and efficient in monitoring surface changes in the different class of land cover features within the study period. Nevertheless, they have their advantages and disadvantages on processing change detection analysis particularly for the topic of urban expansion.
40
Meyer, Cynthia A. "Evaluating Habitat Vulnerability and Sustainability of Urban Seagrass Resources to Sea Level Rise." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4918.
Full textAbstract:
The seagrass resource provides essential ecosystem functions for many marine species. This research evaluated the vulnerability and sustainability of the seagrass resource in an urbanized area to the effects of sea level rise. The assessment required analysis of information regarding the biogeography of the seagrass resource, and developing a method to model the spatial extent of the suitable habitat for seagrass, and applying the model to predict the implications of simulated sea level rise scenarios on the seagrass resource.
Examining the biogeography of the seagrass resource required the development of a seagrass monitoring and assessment field survey and a comprehensive seagrass resource map (SGRM). The mesoscale field survey was designed and conducted in St. Joseph Sound (STJS) and Clearwater Harbor North (CLWN), Pinellas County, Florida from 2006-2010 to determine the seagrass species composition and spatial distribution for the resource. The seagrass species found in the study area consisted of Syringodium filiforme Kützing (Syringodium), Thalassia testudinum Banks ex König (Thalassia), and Halodule wrightii Ascherson (Halodule). These seagrass species occurred in monospecific and mixed beds in all combinations throughout the study area. Spatially, Thalassia was the dominant nearshore in STJS and Halodule in CLWN. Syringodium was most frequently found in STJS in the mid to deep depths.
The SGRM was mapped from satellite remote sensing imagery with training information from the mesoscale field survey data. Landsat 5 Thematic Mapper (TM) and Earth Observing-1 Hyperion (HYP) were processed to map the seagrass resource in the study area in a nearshore shallow coastal area of Pinellas County, FL, USA. A maximum likelihood classification (MLC) was used to classify both TM and HYP imagery into three classes (seagrass estimated coverage) of the seagrass resource. The overall accuracy for the TM MLC map was 91% (kappa = 0.85) and the HYP was 95% (kappa = 0.92). Due to areas of cloud cover in the HYP image, it was necessary to composite the classification values from the TM MLC to accurately define these areas. The validation accuracy (n=72) of the composite seagrass resource map was 81% which was much more rigorous than the previous accuracy estimates. These results support the application of remote sensing methods to analyze the spatial extent of the seagrass resource.
The development of a spatial habitat suitability model (HSM) for the seagrass resource provided a management tool to better understand the relationship between seagrass, water quality, and other environmental factors. The motivation to develop the spatial HSM was to provide a spatial modeling tool to simulate changes in the water quality environment and evaluate the potential impact on the seagrass resource. High resolution bathymetry and field survey water quality data were used to fit general additive models (GAM) to the STJS (Adjusted R2= 0.72, n=134) and CLWN (Adjusted R2= 0.75, n=138) seagrass resource. The final GAMs included water quality variables including salinity, chlorophyll-a concentration, total suspended solids, turbidity, and light. The only significant variable was the light metric in STJS (p-value= 0.001) and CLWN (p-value= 0.006). The light metric was the logarithmic light attenuation calculated from the water quality field survey transmittance (660nm) data and the high resolution bathymetry. The overall accuracy (OA) of the predictive GAM rasters was higher in CLWN (95%, kappa =0.88) than in STJS (82%, kappa = 0.40). The increased prediction error in STJS was spatially correlated with the areas of lower density seagrass along the deep edge of the bed. While there may be a plethora of factors contributing to the decreased density of the seagrass, this may indicate these seagrass were already living at the edge of the suitable habitat.
Factors threatening the sustainability of the seagrass resource included those related to water quality and environmental changes. Knowledge of these relationships was essential to develop a predictive spatial HSM to simulate responses of the seagrass to changes in the water quality and the environment. Historically, environmental management strategies focused on water quality targets, but have not considered mitigation for climate change impacts, specifically sea level rise (SLR). This study utilized the HSM for the seagrass resource as a management tool to better understand the relationship between seagrass, water quality, and sea level rise scenarios.
Based on SLR scenarios for 1ft-6ft (0.305m-1.83m) from 2010 to 2100, the potential seagrass habitat loss and gain was analyzed. From the current 60 km2 of seagrass habitat in St. Joseph Sound (STJS) and Clearwater Harbor North (CLWN), the predicted seagrass habitat loss based on the HSM which focused on light availability for photosynthesis ranged from 14 km2 (SLR 1ft) to 26 km2 (SLR 2ft) to the entire 60 km2 (SLR 6ft). The potential seagrass habitat gain based on the coastal flooding model (NOAA, 2012) ranged from 4 km2 (SLR 1ft) to 19 km2 (SLR 6ft). However, based on the spatial distribution of the seagrass and the proximity of the seagrass to the new habitat, the potential viable habitat based on the mean seagrass growth rates (horizontal rhizome elongation) only ranged from 2 km2 (SLR 1ft) to 9 km2 (SLR 6ft). An additional complexity to the gain of seagrass habitat was the effect of the anthropogenically altered shorelines, seawalls, which covered 47% of the shoreline. These seawalls potentially could impede the inundation of the seawater and the seagrass colonization of these areas by creating a vertical boundary for seagrass growth.
The mitigation of the potential effects of SLR on the seagrass resource may require ecosystem level management. While management of water quality would continue to benefit the seagrass resource, additional management strategies would be necessary to mitigate for potential decrease in suitable seagrass habitat related to the effects of SLR. A discussion of potential management approaches suggested that the integration of coastal shoreline management strategies and seagrass resource management would be essential to insure the sustainability of the resource.
41
Thapa, Vivek. "Habitat Fragmentation by Land-Use Change: One-Horned Rhinoceros in Nepal and Red-Cockaded Woodpecker in Texas." Thesis, University of North Texas, 2010. https://digital.library.unt.edu/ark:/67531/metadc33207/.
Full textAbstract:
This research focuses on the spatial analysis of the habitat of two vulnerable species, the one-horn rhinoceros in the grasslands of southern Nepal, and the red-cockaded woodpecker in the Piney woods of southeast Texas, in the USA. A study sites relevant for biodiversity conservation was selected in each country: Chitwan National Park in Nepal, and areas near the Big Thicket National Preserve in Texas. Land-use differs in the two study areas: the first is still undergoing agrarian development while the second is in a technological phase and undergoing urbanization processes. Satellite remote sensing images were used to derive land-cover maps by supervised classification. These maps were then processed by Geographic Information Systems methods to apply habitat models based on basic resources (food and cover) and obtain habitat suitability maps. Several landscape metrics were computed to quantify the habitat characteristics especially the composition and configuration of suitable habitat patches. Sensitivity analyses were performed as the nominal values of some of the model parameters were arbitrary. Development potential probability models were used to hypothesize changes in land-use of the second study site. Various scenarios were employed to examine the impact of development on the habitat of red-cockaded woodpecker. The method derived in this study would prove beneficial to guide management and conservation of wildlife habitats.
42
Madron, Justin. "REFORESTATION OF RED SPRUCE (PICEA RUBENS) ON THE CHEAT MOUNTAIN RANGE, WEST VIRGINIA." VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/3113.
Full textAbstract:
The (Plethodon nettingi) Cheat Mountain Salamander is a rare and endangered species that relies heavily on (Picea rubens) Red Spruce for habitat. P. rubens communities on the Cheat Mountain range in West Virginia have been disturbed by fires and logging, and regeneration of P. rubens stands are central to the survival of the P. netting. A supervised and unsupervised landscape classification of three Landsat images over the past 26 years was conducted to analyze change in P. rubens communities on Cheat Mountain Range. Change detection results revealed that from 1986-2012 a 52% growth increase of P. rubens stands, 18% loss, and 29% stayed the same over the last 26 years. P. rubens stands are vital habitat to the rare and endangered P. netting and regrowth of P. rubens is vital in restoring the habitat of the salamander on the Cheat Mountain. The regrowth of P. rubens on the Cheat Mountain range is critical to the survival of the P. nettingi. Identifying critical forest as it relates to salamander habitat is essential for conservation efforts. Since not all P. rubens stands are of equal significance to the P. nettingi, it is important to identify and map those that adhere to their stringent habitat needs as defined by forest fragmentation, aspect, slope, and lithology. I used spatial analysis and remote sensing techniques to define critical forest characteristics by applying a forest fragmentation model utilizing morphological image analysis, northeast and southwest aspects, moderate slopes, and limestone lithology. Patches were ranked based on this quantitative model and key P. rubens stands identified using spatial statistics. The results could aid in prioritizing research areas as well as conservation planning in regards to P. rubens and the P. nettingi. In this study, the MaxEnt modeling framework was used to predict habitat suitability for P. rubens under current conditions and under two future climate change scenarios. P. rubens distribution data was acquired from the U.S Geological Survey. Both the IPCC A1B and A2 emission scenarios of the HadCM3 global circulation model were projected to years 2040-2069 and 2070-2099. Results showed that a substantial decline in the suitability of future P. rubens habitat on the Cheat Mountain is likely under both climate change scenarios, particularly at lower elevations. By the end of the century, P. rubens is likely to be extirpated from the Cheat Mountain Range. By the end of century, the A1B and A2 scenarios predict the average habitat suitability for P. rubens on Cheat Mountain will be 0.0002 and 0.00004 respectively. Conservation as well as species migration efforts for P. rubens should be focused on areas such as Cheat Mountain to preserve this vital habitat.
43
Hutchison, Sean Taylor. "Eastern Deciduous Forest Phenology and Vegetative Vigor Trends From 2000 to 2013, Mammoth Cave National Park, KY." TopSCHOLAR®, 2013. http://digitalcommons.wku.edu/theses/1312.
Full textAbstract:
Global climate change is predicted to affect environmental systems at the midlatitudes, but the scope, severity, and outcomes of these impacts are yet to be fully understood. This study focuses on the implications of short-term climate variability for forests in central Kentucky. Using a Normalized Difference Vegetation Index (NDVI) calculated from MODerate-Resolution Imaging Spectroradiometer (MODIS) instrument data, the photosynthetic activity of vegetation at Mammoth Cave National Park (MACA) is tracked from 2000 to 2013. Three methods were employed to examine the changes and climate influences in vegetation over the study period: 1) aggregating the NDVI of the Park by year and by summer months (June, July, and August) and examining how these productivity trends could be influenced by precipitation and temperature fluctuations, 2) examining the trend of the NDVI at selected dates throughout the study period to detect phenological shifts around leaf-out and leaf-off, and 3) using a generalized vegetation classification of MACA to clip the imagery based on areas of similar vegetation and then testing correlations between those subsets and teleconnections. The results from the aggregated NDVI show there is an insignificant negative trend. A negative relationship between summer forest productivity at MACA and temperature was found, though more data are needed to rigorously validate this result. Changes in phenology indicate forest productivity is decreasing earlier each year throughout the study period. Finally, the Multivariate ENSO Index and the Pacific Decadal Oscillation index are shown to have significant positive correlations with the summer productivity of MACA during the study period.
44
Wang, Mengqiu. "Spatial and Temporal Distributions of Pelagic Sargassum in the Intra-Americas Sea and Atlantic Ocean." Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7716.
Full textAbstract:
Pelagic Sargassum is one type of marine macroalgae that is known to be abundant in the Gulf of Mexico and Sargasso Sea. It is also known to serve as a critical habitat for many marine animals. In the past few years, large amounts of Sargassum have been reported in the Tropical Atlantic and Caribbean Sea (CS), causing significant environmental and economic problems. The goal of this study is to improve the understanding of Sargassum distributions, quantity, transport pathways, and bloom mechanisms in the CS and Tropic Atlantic through combining a variety of techniques including satellite remote sensing, field and laboratory measurements, and numerical modeling.
The first question is where and how much Sargassum is in the CS and Tropic Atlantic. Previous field observations revealed strong seasonal and spatial variations of Sargassum, yet these observations are all limited in their spatial and temporal coverage. Satellite observations offer an effective means to measure their distributions with synoptic coverage and high sampling frequency, yet it is technically challenging to extract and quantify the small Sargassum features in coarse-resolution satellite imagery. Chapter 2 focuses on Sargassum detection and quantification algorithm development using Moderate Resolution Imaging Spectroradiometer (MODIS) data (Appendix A). The algorithm is based on MODIS alternative floating algae index (AFAI), which examines the red-edge reflectance of floating vegetation. The algorithm includes three basic steps: 1) classification of Sargassum-containing pixels through correction of large-scale gradient, masking clouds and cloud shadows, and removal of ambiguous pixels; 2) linear unmixing of Sargassum-containing pixels; and, 3) statistical analysis of Sargassum area coverage in pre-defined grids at monthly, seasonal, and annual intervals. The algorithm is applied to MODIS observations between 2000 and 2015 over the Central West Atlantic (CWA) region (0 – 22oN, 38 – 63oW) to derive the spatial and temporal distribution patterns as well as the total areal coverage of Sargassum. Results indicate that the first widespread Sargassum distribution event occurred in 2011, consistent with previous findings from the Medium Resolution Imaging Spectrometer (MERIS). Since 2011, only 2013 showed minimal Sargassum coverage similar to the period of 2000 to 2010; all other years showed significantly more coverage. More alarmingly, the summer months of 2015 showed mean coverage of > 2000 km2, or about 4 times of the summer 2011 coverage and 20 times of the summer 2000 to 2010 coverage. Analysis of several environmental variables provided some hints on the reasons causing the inter-annual changes after 2010, yet further multi-disciplinary research (including in situ measurements) is required to understand such changes and long-term trends in Sargassum coverage.
To better understand the potential ecological and environmental impacts of Sargassum, field and laboratory experiments are conducted to link the Sargassum areal coverage observations to biomass per area (density) and measure the nutrient contents and pigment concentrations (Chapter 3, Appendix B). An AFAI-biomass density model is established to derive Sargassum biomass density from the spectral reflectance, with a relative uncertainty of ~ 12%. Monthly mean integrated Sargassum biomass in the CS and CWA reached > 4.4 million tons in July 2015. The average % C, % N, and % P per dry-weight, measured from samples collected in Gulf of Mexico and Florida Straits in summer 2017, are 27.16, 1.06, and 0.10, respectively. The mean chlorophyll-a concentration is ~ 0.05% of the dry-weight. With these parameters, the amounts of nutrients and pigments can be estimated directly from remotely-sensed Sargassum biomass. During bloom seasons, Sargassum carbon can account for ~ 18% of the total particulate organic carbon in the upper water column. This chapter provides the first quantitative assessment of the overall Sargassum biomass, nutrients, and pigment abundance from remote-sensing observations, thus helping to quantify their ecological roles and facilitate management decisions.
To investigate the Sargassum transport patterns and potential bloom sources, a Lagrangian particle tracking model is established to track the Sargassum transport driven by surface currents and winds (Chapter 4, Appendix C). The mean Sargassum distributions derived from MODIS observations are used to initiate and evaluate a Lagrangian particle tracking model that tracks Sargassum advection under surface currents and winds. Among the thirty-nine experiments, adding surface currents alone improves model performance (i.e., by reducing difference between modeled and observed Sargassum distributions) in 82% of the cases after tracking Sargassum for one month. Adding 1% wind forcing to the advection model also shows improved performance in 67% of the cases. Adding a time- and location-dependent Sargassum growth/mortality rate (i.e., change rate), derived from time-series of the MODIS-based Sargassum abundance and the corresponding environmental data via a Random Forest regression, leads to further improvement in model performance (i.e., by increasing the matchup percentage between modeled and observed Sargassum distributions) in 64% of the cases, although the modeled change rates only explain ~ 27% of the variance of the validation dataset, possibly due to uncertainties in such-derived change rates. The Sargassum transport model, with the mean currents, winds, and change rates acting as the forcing, is applied to track the mean Sargassum distributions forward and backward. The results demonstrate the model’s capacity of simulating the Sargassum distribution patterns, with emphasis on the role of biological terms in determining the large-scale distributions. These tracking experiments also suggest that Sargassum blooms in the CS are strongly connected to the Central Atlantic regions, and blooms in the Tropical Atlantic show relatively weak connections to the Atlantic regions further north.
Although it is straightforward to apply the transport model to predict Sargassum blooms, such long-term prediction could suffer from large error accumulations and unable to achieve satisfactory performance. Therefore historical Sargassum distributions derived from MODIS are used to provide an alternative way to realize the bloom prediction. Chapter 5 proposes such a prediction based on a hindcast of 2000–2016 observations from MODIS, which shows Sargassum abundance in the CS and the CWA, as well as connectivity between the two regions with time lags (Appendix D). This information is used to derive bloom and nonbloom probability matrices for each 1° square in the CS for the months of May–August, predicted from bloom conditions in a hotspot region in the CWA in February. A suite of standard statistical measures is used to gauge the prediction accuracy, among which the user’s accuracy and kappa statistics show high fidelity of the probability maps in predicting both blooms and nonblooms in the eastern CS with several months of lead time, with an overall accuracy often exceeding 80%. The bloom probability maps from this hindcast analysis will provide early warnings to better study Sargassum blooms and prepare for beaching events near the study region. This approach may also be extendable to many other regions around the world that face similar challenges and opportunities of macroalgal blooms and beaching events. Using this forecasting scheme, the summer blooms in the CS in 2017 were successfully predicted. Since February 2018, we have also generated monthly-updated 1-page Sargassum outlook bulletins to help these regions to better prepare for potential beaching events.
Currently, the mean Sargassum distribution statistics used in this study are derived from MODIS, which has been operating well beyond the designed mission life, arousing concerns as to whether the Sargassum observation statistics can be continued in the future. As a follow-on sensor, the Visible Infrared Imaging Radiometer Suite (VIIRS) has the appropriate spectral bands to detect and quantify floating macroalgae. Based on previous works on MODIS, Chapter 6 presents an improved procedure to extract floating algae pixels from VIIRS AFAI imagery, with image filtering used to suppress noise and adjusted thresholds used to mask sun glint, clouds, and cloud shadows. The overall extraction accuracy is about 85%. Simultaneous daily observations from MODIS and VIIRS over the CWA show consistent spatial patterns, but VIIRS estimations of the algae coverage (in km2) are consistently lower than MODIS (around – 19% mean relative difference or MRD), possibly due to lower sensitivity of the VIIRS near-infrared (NIR) bands than the corresponding MODIS bands. Similarly, at monthly scale VIIRS also shows lower coverage than MODIS, and their difference (around – 29% MRD) is larger than the difference between MODIS-Aqua and MODIS-Terra estimates (around – 14% MRD). Despite these differences, the spatial and temporal patterns between VIIRS and MODIS observed algae distributions match very well at all spatial and temporal scales. These results suggest that VIIRS can provide continuous and consistent observations of floating algae distributions and abundance from MODIS as long as their differences are accounted for, thus assuring continuity in the future.
In summary, this study has worked on four connected topics regarding Sargassum distributions, biomass and nutrients, transport pathways, and bloom predictions through combined efforts in satellite remote sensing, field and laboratory measurements, physical modelling, and statistical analyses. To my best knowledge, this is the first comprehensive and multi-disciplinary study to investigate pelagic Sargassum at synoptic scale in the Intra-Americas Sea (IAS) and Atlantic Ocean. Although several questions remain to be answered (e.g., “What cause the inter-annual variations of Sargassum blooms?” and “Where are the bloom origins?”), the outcomes of this study (remote sensing algorithms, Sargassum distribution and abundance maps, established bio-physical model, and a bloom forecast model) are expected to make significant contributions in both scientific research (including new critical baseline data) and management decision support.
45
Alaibakhsh, Masoomeh. "Digital change detection and separation of anthropogenic and natural impacts on ecohydrological conditions in the Pilbara region, WA." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2017. https://ro.ecu.edu.au/theses/1951.
Full textAbstract:
A deficiency in crucial digital data, such as vegetation cover, in remote regions is a challenging issue for sustainable water management and planning, especially for areas undergoing rapid development, such as mining in the Pilbara, Western Australia. This is particularly relevant to Inflow and Groundwater Dependent Vegetation (IGDVs) (riparian vegetation and groundwater dependent vegetation) which provide important ecological services and, as such, require regional protection. However, such invaluable assets experience changes over time due to either human activities such as land development or natural phenomena such as climate change or fire events.
The main objectives of this research was to 1) advance an approach to delineate inflow dependent ecosystems at a local scale; 2) adopt it to map the assets at regional scale using remotely sensed data (Landsat 5 TM imagery due to its appropriate temporal and spatial resolution for historical studies, 1986-2011), ground-truth data and available information such as reports, digital layer and climate data; 3) develop a method for identification and quantitative assessment of IGDVs changes and attribution of the changes to particular impacts or stressors, and 4) apply the developed change detection method to investigate and evaluate impacts of an adopted water resource management options on inflow dependent assets in the Pilbara.
Outcomes of the research exposed that the proposed delineation method allowed production of accurate inflow dependent ecosystems maps for the Pilbara bioregion. The change detection method was also effective in detecting various spatial and temporal scales of changes and separating anthropogenic and natural impacts. It was further discovered that climate has had significant impacts on the assets of the area.
The finding and information produced from this research is capable to aid government, industry and communities to consider the environmental, social, cultural and economic aspects of the sustainable use, development and management of land and water resources in arid and semiarid Pilbara, WA and areas with similar ecohydrological conditions. Four papers were prepared from the research, two are published and two are under review.
46
Mlotha, McArd Joseph. "Analysis of Land Use/Land Cover Change Impacts Upon Ecosystem Services in Montane Tropical Forest of Rwanda: Forest Carbon Assessment and REDD+ Preparedness." Antioch University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=antioch1527773591460797.
Full text
47
Wigmore, Oliver Henry Wigmore. "Assessing Spatiotemporal Variability in Glacial Watershed Hydrology: Integrating Unmanned Aerial Vehicles and Field Hydrology, Cordillera Blanca, Peru." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1471854919.
Full text
48
Falk, Matthew Gregory. "Incorporating uncertainty in environmental models informed by imagery." Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/33235/1/Matthew_Falk_Thesis.pdf.
Full textAbstract:
In this thesis, the issue of incorporating uncertainty for environmental modelling informed by imagery is explored by considering uncertainty in deterministic modelling, measurement uncertainty and uncertainty in image composition. Incorporating uncertainty in deterministic modelling is extended for use with imagery using the Bayesian melding approach. In the application presented, slope steepness is shown to be the main contributor to total uncertainty in the Revised Universal Soil Loss Equation. A spatial sampling procedure is also proposed to assist in implementing Bayesian melding given the increased data size with models informed by imagery. Measurement error models are another approach to incorporating uncertainty when data is informed by imagery. These models for measurement uncertainty, considered in a Bayesian conditional independence framework, are applied to ecological data generated from imagery. The models are shown to be appropriate and useful in certain situations. Measurement uncertainty is also considered in the context of change detection when two images are not co-registered. An approach for detecting change in two successive images is proposed that is not affected by registration. The procedure uses the Kolmogorov-Smirnov test on homogeneous segments of an image to detect change, with the homogeneous segments determined using a Bayesian mixture model of pixel values. Using the mixture model to segment an image also allows for uncertainty in the composition of an image. This thesis concludes by comparing several different Bayesian image segmentation approaches that allow for uncertainty regarding the allocation of pixels to different ground components. Each segmentation approach is applied to a data set of chlorophyll values and shown to have different benefits and drawbacks depending on the aims of the analysis.
49
Moore, Alahna. "Using Digital Mapping Techniques to Rapidly Document Vulnerable Historical Landscapes in Coastal Louisiana: Holt Cemetery Case Study." ScholarWorks@UNO, 2018. https://scholarworks.uno.edu/td/2477.
Full textAbstract:
This thesis outlines a technique for rapid documentation of historic sites in volatile cultural landscapes. Using Holt Cemetery as an exemplary case study, a workflow was developed incorporating RTK terrain survey, UAS aerial imagery, photogrammetry, GIS, and smartphone data collection in order to create a multifaceted database of the material and spatial conditions, as well as the patterns of use, that exist at the cemetery.
The purpose of this research is to create a framework for improving the speed of data creation and increasing the accessibility of information regarding threatened cultural resources. It is intended that these processes can be scaled and adapted for use at any site, and that the products generated can be utilized by researchers, resource management professionals, and preservationists. In utilizing expedited methods, this thesis specifically advocates for documentation of sites that exist in coastal environments and are facing imminent destruction due to environmental degradation.
50
"Patch to Landscape and Back Again: Three Case Studies of Land System Architecture Change and Environmental Consequences from the Local to Global Scale." Doctoral diss., 2020. http://hdl.handle.net/2286/R.I.57273.
Full textAbstract:
abstract: Humans have modified land systems for centuries in pursuit of a wide range of social and ecological benefits. Recent decades have seen an increase in the magnitude and scale of land system modification (e.g., the Anthropocene) but also a growing recognition and interest in generating land systems that balance environmental and human well-being. This dissertation focused on three case studies operating at distinctive spatial scales in which broad socio-economic or political-institutional drivers affected land systems, with consequences for the environmental conditions of that system. Employing a land system architecture (LSA) framework and using landscape metrics to quantify landscape composition and configuration from satellite imagery, each case linked these drivers to changes in LSA and environmental outcomes.
The first paper of this dissertation found that divergent design intentions lead to unique trajectories for LSA, the urban heat island effect, and bird community at two urban riparian sites in the Phoenix metropolitan area. The second paper examined institutional shifts that occurred during Cuba’s “special period in time of peace” and found that the resulting land tenure changes both modified and maintained the LSA of the country, changing cropland but preserving forest land. The third paper found that globalized forces may be contributing to the homogenizing urban form of large, populous cities in China, India, and the United States—especially for the ten largest cities in each country—with implications for surface urban heat island intensity. Expanding knowledge on social drivers of land system and environmental change provides insights on designing landscapes that optimize for a range of social and ecological trade-offs.Dissertation/Thesis
Doctoral Dissertation Geography 2020