Teses / dissertações sobre o tema "Environmental management – remote sensing"

Thesis (MA)--Stellenbosch University, 2002.
ENGLISH ABSTRACT: The unique and often fragile environment of the coastal zone is placed under increasing pressure by human development. It is expected that three quarters of the world's population will be living within 60km of the coast by the year 2020. Thorough planning and management are required to prevent coastal degradation. In South Africa, coastal management efforts are being promoted through the implementation of a White Paper for sustainable coastal development. A Coastal Decision Support System (CDSS) was developed to empower local authorities to demarcate and manage sensitive coastal areas by giving them access to relevant botanical and physical information. Land cover/use information for the CDSS was previously mapped manually from hardcopy aerial photography. This method was found to be time-consuming and costly. This study investigated the potential for digital satellite imagery as primary source of data for populating the land cover/use information of the CDSS. A methodology was designed utilising semi-supervised isodata clustering for extracting relevant information for a study area covering 40x20km of coast along the southern coastal sector of South Africa. Digital mapping of SPOT 4 multispectral satellite data was used successfully to map land cover/use information such as wetlands, coastal lakes, dune vegetation, urban areas, forest plantations, natural forest and agricultural areas. A cost comparison was also made between the digital mapping method from satellite imagery used in this research project and the manual mapping from aerial photography. Digital mapping from satellite imagery was found to be more cost-effective in terms of both data and human resource costs. The method outlined and discussed in the research project should provide sufficient guidance for future application of the techniques in populating the CDSS with land cover/use information.
AFRIKAANSE OPSOMMING: Die unieke en dikwels sensitiewe landskap in die kussone is onder aansienlike druk weens ontwikkeling deur mense. Daar word verwag dat 'n derde van die wêreldbevolking teen die jaar 2020 binne 60km van die kus woonagtig sal wees. Dit sal deeglike beplanning en bestuur verg om die agteruigang van hierdie gebied te bekamp. Kussonebestuur word in Suid Afrika aangemoedig deur die implementering van 'n Witskrif vir volhoubare kussone-ontwikkeling. 'n Kusgebied-besluitnemingsondersteuningstelsel (KBOS) is ontwikkel in 'n poging om plaaslike owerhede te bemagtig om sensitiewe kusgebiede af te baken en te bestuur. Die KBOS verleen plaaslike owerhede toegang tot toepaslike inligting oor botaniese en fisiese o~standighede. Grondbedekkinginligting vir die KBOS is in die verlede vanaf hardekopie lugfoto's gekarteer. Hierdie metode is tydrowend en duur. Die potensiaal van digitale satellietbeelde as hoof databron om grondbedekkinginligting vir die KBOS te voorsien is in hierdie studie ondersoek. 'n Metode word in die tesis uiteengesit om 'semi-supervised isodata clustering' te gebruik om die nodige inligting uit die data te onttrek. Die studiegebied sluit 'n area van 40x20km langs die suid kus van Suid Afrika in. Digitale kartering vanaf SPOT 4 multispektrale satellietdata is suksesvol gebruik om grondbedekkingsinligting soos vleilande, kusmere, duin-plantegroei, stedelike gebiede, bosbou, natuurlike bos en landbougebiede te karteer. 'n Kostevergelyking is gedoen tussen die digitale karteringsmetode vanaf satellietbeelde in vergeleke met handkartering vanaf lugfotografie. Die digitale karteringsmetode blyk meer koste-effektief te wees beide in terme van die datakoste sowel as die koste verbonde aan mannekrag. Die omskrywing van die metode in die tesis behoort as goeie riglyn te dien vir die toepassing van die tegniek om grondbedekkinginligting voor te berei vir die KBOS.

Lake Atitlan in Guatemala is a vital source of drinking water. The deteriorating conditions of water quality in this lake threaten human and ecological health as well as the local and national economy. Given the sporadic and limited measurements available, it is impossible to determine the changing conditions of water quality. The goal of this thesis is to use Hyperion satellite images to measure water quality parameters in Lake Atitlan. For this purpose in situ measurements and satellite-derived reflectance data were analyzed to generate an algorithm that estimated Chlorophyll concentrations. This research provides for the first time a quantitative application of hyperspectral satellite remote sensing for water quality monitoring in Guatemala. This approach is readily transferable to other countries in Central America that face similar issues in the management of their water resources.

Vegetation has been identified as an essential component of healthy urban environments, and the benefits of urban vegetation range widely from influences on the physical conditions of the city to the social well-being of the people who reside in these areas. As a result, ongoing research is important to understand the dynamic spatial components of urban vegetation to help urban planners and scholars manage this valuable resource. Advanced remote sensing technologies, such as high spatial resolution sensors and laser scanning devices, are useful tools for examining urban environments since they can capture detailed information regarding the material and structural composition of the urban surface. By providing a complete coverage of urban environments remote sensing technologies enable new possibilities to quantify the contributions of urban vegetation for a wealth of active processes in urban areas. The studies in this thesis examine several remote sensing devices to demonstrate the influence of urban vegetation on both physical and social aspects of urban environments. Three studies comprise the body of this work. They present new geographic techniques using remote sensing for: 1) the detailed classification of urban vegetation conditions; 2) quantifying the contribution of trees to solar radiation available for building rooftops; and 3) examining socioeconomic disparities related to urban green-space.

Agricultural drought is a creeping disaster that overshadows the vegetative cover in general and cropland specifically in Iraq, a country that was well known for its agricultural production and fertile soil. In the recent years, the arable lands in Iraq experienced increasing land degradation that led to desertification, economic losses, food insecurity, and deteriorating environment. Remote sensing is employed in this study and four different indices are utilized, each of which is derived from MODIS satellite mission products. Agricultural drought maps are produced from 2003 to 2015 after masking the vegetation cover. Year 2008 was found the most severe drought year during the study period, where drought covered 37% of the vegetated land. This part of the study demonstrated the capability of remote sensing in fulfilling the need of an early warning system for agricultural drought over such a data-scarce region.

This study also aims to monitor hydrological drought. The Gravity Recovery and Climate Experiment (GRACE) satellite-derived monthly Terrestrial Water Storage (TWS) is the hydrological drought indicator, that is used to calculate the deficit. Severity of drought events are calculated by integrating monthly water deficit over the drought period. In addition, drought recovery time is assessed depending on the estimated deficit. Major drought events are classified into several levels of severity by applying a drought monograph approach. The results demonstrated that GRACE TWS is a reliable indicator for drought assessment over Iraq, and provides useful information for decision makers which can be utilized in developing drought adaptation and mitigation strategies.

Local participation in environmental decision making processes is a recognized need if the goals of sustainable development are to be met. Spatial information is an important part of environmental decision making, but so far, technical barriers have prevented effective public participation in spatial data management and analysis. These barriers need to be overcome if participants are to take part in a decision making process in a manner that is both fair and competent. The study was undertaken to quantify land cover change in a particular region and, through this exercise, to determine what the practical barriers to public participation in decision making might be. The work was conducted in the Windermere Valley, British Columbia. Community questions about local environmental change were determined from a local newspaper and discussions with Environmental Non-Governmental Organizations (ENGO's). Using satellite imagery and other geospatial data, community questions about local environmental change were answered through the detection of land cover change for the period 1974--1991. The processes of acquiring the data and completing the analysis were evaluated with the criteria of fairness and competence. The products of the change detection analysis were evaluated based on how well they answered community questions. Suggestions are presented on what tools and resources ENGO's would require to complete a similar study to answer questions about the environment.

[ES] Las playas son espacios costeros que desarrollan numerosas funciones ambientales. Éstas proporcionan importantes beneficios a la sociedad y a las comunidades costeras, entre las que destacan la función ecológica, el suministro de protección para los territorios costeros y el hecho de que constituyen un recurso básico de la industria turística. De forma ligada al cambio climático, así como a acciones humanas que alteran el dinamismo natural de la costa, las playas están experimentando procesos erosivos cada vez más dañinos que afectan a su integridad física y al mantenimiento de sus funciones. La gestión de las playas en muchas ocasiones no se encuentra adaptada a las particularidades de los diferentes segmentos costeros. La toma de decisiones no se sustenta en información suficiente sobre las características, el dinamismo y el estado actual de las playas, dando lugar a soluciones cortoplacistas o ineficaces. Las características geomorfológicas son esenciales en el desarrollo de sus funciones al condicionar sus dimensiones físicas y su comportamiento frente a la acción del mar. Por ello, su caracterización de forma detallada y actualizada es necesaria para llevar a cabo acciones eficientes, permitiendo virar hacia una gestión costera más ecosistémica y sostenible. Las técnicas de teledetección presentan una gran capacidad para la adquisición de datos de la superficie terrestre. En concreto, los satélites Sentinel-2 y Landsat (5, 7 y 8) permiten disponer de forma gratuita imágenes de resolución media con cobertura mundial y alta frecuencia de revisitado. Los algoritmos de extracción de la línea de costa desarrollados recientemente por el Grupo de Cartografia GeoAmbiental y Teledetección (CGAT - UPV) permiten definir sobre estas imágenes la posición de la línea de costa, constituyendo datos potencialmente útiles para describir la morfología de las playas y su dinamismo. Universalizar su aplicación requiere su testeo y validación en diferentes tipos de costa. Para ello, el proceso de extracción ha sido adaptado para su explotación en entornos mareales, y las líneas de costa resultantes han sido evaluadas ante diferentes condiciones oceanográficas ofreciendo una precisión cercana a los 5 m RECM (raíz del error cuadrático medio). Teniendo en cuenta las necesidades de información para la gestión existentes, a partir de estas líneas de costa se propone derivar indicadores que permitan caracterizar la geomorfología de las playas y monitorizar sus cambios. Para ello, las metodologías propuestas aseguran una gestión eficiente de grandes volúmenes de líneas de costa, siendo así capaces de caracterizar las playas cubriendo grandes territorios y periodos de tiempo. Así se derivan el ancho de playa y el tamaño de los granos de sedimento como indicadores objetivos y fácilmente comprensibles de la geomorfología de la playa. La modelización espacio-temporal del estado y los cambios de la línea de costa y de la anchura posibilita monitorizar la respuesta de las playas a temporales y a actuaciones antrópicas, permitiendo analizar los cambios ocurridos cada pocos días hasta cubrir décadas. Su cobertura espacial junto a la integración con otras bases de datos cartográficas permite caracterizar la influencia de la geomorfología de la playa en el desempeño de sus funciones, permitiendo un análisis holístico de la costa a escala regional. Las metodologías desarrolladas en esta tesis y los indicadores derivados desde la teledetección brindan apoyo para dotar de criterios y priorizar las acciones de los gestores. Se contribuye así a llenar el espacio existente entre la disponibilidad de técnicas para obtener información remota y su aplicación en los procesos de toma de decisiones sobre la costa.
[CAT] Les platges són espais costaners que desenvolupen nombroses funcions ambientals. Aquestes proporcionen importants beneficis a la societat i comunitats costaneres, entre les quals destaquen la funció ecològica, el subministrament de protecció per als territoris costaners i el fet que constitueixen un recurs bàsic de la indústria turística. De forma lligada al canvi climàtic, així com a accions humanes que alteren el dinamisme natural de la costa, les platges estan experimentant processos erosius cada vegada més nocius que afecten la seua integritat física i al manteniment de les seues funcions. La gestió de les platges en moltes ocasions no es troba adaptada a les particularitats dels diferents segments costaners. La presa de decisions no es sustenta en informació suficient sobre les característiques, el dinamisme i l'estat actual de les platges, donant lloc a solucions curtterministes o ineficaces. Les característiques geomorfològiques són essencials en el desenvolupament de les seues funcions en condicionar les seues dimensions físiques i el seu comportament enfront de l'acció de la mar. Per això, la seua caracterització de manera detallada i actualitzada és necessària per a dur a terme accions eficients, permetent virar cap a una gestió costanera més ecosistèmica i sostenible. Les tècniques de teledetecció presenten una gran capacitat per a l'adquisició de dades de la superfície terrestre. En concret, els satèl·lits Sentinel-2 i Landsat (5, 7 i 8) permeten disposar de manera gratuïta d'imatges de resolució mitjana amb cobertura mundial i alta freqüència de captura d'informació a un mateix punt. Els algorismes d'extracció de la línia de costa desenvolupats recentment pel Grup de Cartografia Geo-Ambiental i Teledetecció (CGAT - UPV) permeten definir sobre aquestes imatges la posició de la línia de costa, constituint dades potencialment útils per descriure la morfologia de les platges i el seu dinamisme. Universalitzar la seua aplicació requereix el seu testatge i validació en diferents tipus de costa. Per a això, el procés d'extracció ha sigut adaptat per a la seua explotació en entorns mareals, i les línies de costa resultants han sigut avaluades davant diferents condicions oceanogràfiques oferint una precisió pròxima als 5 m RMSE (arrel de l'error quadràtic mitjà). Tenint en compte les necessitats d'informació per a la gestió existents, a partir d'aquestes línies de costa es proposa derivar indicadors que permeten caracteritzar la geomorfologia de les platges i monitorar els seus canvis. Per a això, les metodologies proposades asseguren una gestió eficient de grans volums de línies de costa, sent així capaces de caracteritzar les platges cobrint grans territoris i períodes de temps. Així es deriven l'ample de platja i la grandària dels grans de sediment com a indicadors objectius i fàcilment comprensibles de la geomorfologia de la platja. La modelització espai-temporal de l'estat i els canvis de la línia de costa i de l'amplària possibilita monitorar la resposta de les platges a temporals i a actuacions antròpiques, permetent analitzar els canvis ocorreguts cada pocs dies fins a cobrir dècades. La seua cobertura espacial al costat de la integració amb altres bases de dades cartogràfiques permet caracteritzar la influència de la geomorfologia de la platja en l'acompliment de les seues funcions, permetent una anàlisi holística de la costa a escala regional. Les metodologies desenvolupades en aquesta tesi i els indicadors derivats des de la teledetecció brinden suport per a dotar de criteris i prioritzar les accions dels gestors. Es contribueix així a omplir l'espai existent entre la disponibilitat de tècniques per a obtenir informació remota i la seua aplicació en els processos de presa de decisions sobre la costa.
[EN] Beaches are coastal spaces that perform numerous environmental functions. They provide important benefits to society and coastal communities, including the ecological function, the provision of protection for coastal territories, and constitute a basic resource for the tourism industry. Due to climate change and human actions that alter the natural dynamism of the coast, beaches are experiencing increasingly harmful erosive processes that affect their physical integrity and the maintenance of their ecological functions. Beach management is often not adapted to the particularities of the different coastal segments. Decision-making is not based on sufficient information about characteristics, dynamism, and current state of beaches, resulting in short or ineffective solutions. Geomorphological characteristics are essential in the development of beach functions as they condition their physical dimensions and their behavior in response to the action of the sea. Therefore, their detailed and updated characterization is necessary to carry out efficient actions, allowing a more ecosystemic and sustainable coastal management. Remote sensing techniques have a great capacity for acquiring data from the land surface. In particular, Sentinel-2 and Landsat (5, 7, and 8) satellites freely provide medium resolution images with global coverage and high-revisit frequency. The algorithms for extracting the water/land interface recently developed by the Geo-Environmental Cartography and Remote Sensing Group (CGAT - UPV) allow defining the position of the shoreline on these images, constituting potentially useful data to describe beach morphology and dynamics. Universalizing their application requires testing and validation at different coastal types. For this purpose, the extraction process has been adapted for exploitation in tidal environments, and the resulting shorelines have been assessed under different oceanographic conditions offering an accuracy close to 5 m RMSE (Root-Mean-Square Error). From these shorelines, and taking into account the existing information needs for management, it is proposed to derive indicators to characterize the geomorphology of the beaches and to monitor their changes. To this end, the proposed methodologies ensure the efficient management of large volumes of shorelines, being able to characterize the beaches along broad coastal segments and periods. Thus, beach width and sediment grain size are derived as objective and easily understandable indicators of the beach geomorphology. Spatial-temporal modeling of the state and changes of shoreline position and beach width makes it possible to monitor the response to storms and anthropogenic actions, allowing to analyze changes that occur every few days or over decades. The large spatial coverage together with the integration with other cartographic databases allows characterizing the influence of beach geomorphology in the performance of its functions, offering a holistic view of the coast from a regional scale. The methodologies developed in this thesis and the indicators derived from remote sensing provide support and criteria for prioritizing the actions of managers. This contributes to fill the gap between the availability of techniques to obtain remote information and its application in the coastal decision-making process.
This research integrates findings and results obtained within the framework of the contract FPU15/04501 granted to the author by the Spanish Ministry of Education, Culture, and Sports, which has allowed this doctoral thesis to become a reality. The research has been supported by the funds of the project RESETOCOAST, by the Ministry of Economy, Industry, and Competitiveness (chapters 2 to 5), and the project MONOBESAT PID2019-111435RB-I00 by the Ministry of Science, Innovation, and Universities (chapter 6). About my stay in Portugal, it was possible with the funds of the Erasmus+ program. The contribution of Ó. Ferreira was funded by EW-COAST (PTDC/CTA-OHR/28657/2017) and by FCT and Univ. Algarve through the grant UID/MAR/00350/2013, while S. Costas’ was funded by IF/01047/2014. The following institutions have provided free access to essential data for the development of the publications that constitute this thesis: ESA and USGS for the satellite imagery; Puertos del Estado, and the Portuguese Hydrographic Institute in collaboration with CIMA for supplying oceanographic data; Ministry MITECO and DGSCM for data regarding beach sedimentology and nourishments.
Cabezas Rabadán, C. (2021). Beach Morphology and its Dynamism from Remote Sensing for Coastal Management Support [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/165076
TESIS

Doctor of Philosophy
Department of Geography
Kevin P. Price
A major strategy in response to rapid degradation and loss of Louisiana’s coastal wetlands has been the construction of siphon diversion projects. The diversions are designed to reintroduce nutrient enriched freshwater from the Mississippi River into wetland ecosystems to combat saltwater intrusion and stimulate marsh growth. The lack of consensus regarding the effects of river diversions on nutrient enrichment of wetland ecosystems is coupled with major concerns about eutrophication. Locating, assessing, and monitoring eutrophic marsh vegetation represent major challenges to understanding the impacts of freshwater diversions. As a result, this study was undertaken to investigate the feasibility of modeling eutrophication vulnerability of a coastal Louisiana marsh receiving turbid Mississippi River water. The major objective was to integrate remotely sensed data with field measurements of vegetation biophysical characteristics and historical ecosystem survey data to delineate landscape patterns suggestive of vulnerability to eutrophication. The initial step in accomplishing this goal was to model the spatial distribution of freshwater impacts using satellite image-based turbidity frequency data associated with siphon diversion operation. Secondly, satellite and spectroradiometer band combinations and vegetation indices optimal for modeling marsh biophysical characteristics related to nutrient enrichment were identified. Finally, satellite image data were successfully integrated with measures of historical and concurrent marsh biophysical characteristics to model the spatial distribution of eutrophication vulnerability and to elucidate the impacts of freshwater diversions.

The vegetation index products from the Moderate Resolution Imaging Spectroradiometer (MODIS) are designed to provide consistent, spatial and temporal comparisons of global vegetation conditions. The objective of this dissertation was to validate the robustness and global implementation of two MODIS VI algorithms, including the normalized difference vegetation index (NDVI) and "enhanced" vegetation index (EVI). Their performances have been evaluated in: (1) the normalization of canopy background (brightness) variations and the extraction of biophysical parameters across different canopy structures; (2) the characterization of seasonal vegetation profiles (phenological, intra-annual); and (3) spatial and temporal discrimination of vegetation differences (inter-annual). The validation was accomplished through multiple means, including canopy radiative transfer models which were utilized to extract pure vegetation spectra and "true" VI value free of background contamination for varying canopy structures and vegetation amount. The experimental field- and airborne-based radiometry and satellite imagery at multiple spatial resolutions were also coupled and scaled-up for comparison with coarse spatial resolution MODIS VI products to quantify characteristics of semiarid rangeland vegetation. The results showed that NDVI was advantageous in yielding biophysical relationships applicable across varying canopy types, but required knowledge of soils for biophysical estimations. The EVI provided biophysical relationships sensitive to canopy structure, thus requiring knowledge of canopy type for biophysical assessments. The MODIS VI products were successfully validated, radiometrically, by coupling field and the MODLAND Quick Airborne Looks (MQUALS) observations to high spatial resolution imagery (AVIRIS and ETM+), and appeared robust across the two parallel sites for depicting their ecological equivalents. MODIS multitemporal VI profiles were able to depict phenological activity, length of the growing season, peak and onset of greenness, and leaf turnover. Among the sensors tested, spatial resolution was found to be most important for discriminating the major land cover subtypes within the two parallel semiarid rangelands, and spectral resolution had major effects on capturing seasonal contrast due to atmosphere influences. The validation strategy utilized in this study to successively aggregate the integrity-inherent multiple fine spatial resolution data to the coarse MODIS pixel sizes appeared to perform well, thus showing potentials in the validation of other satellite products.

Thesis (M.E.S.) -- University of Waterloo, 2002.
"A thesis presented to the University of Waterloo in fulfillment of the requirements for the degree of Master of Environmental Studies in Planning". Includes bibliographical references.

Cities in developing countries are facing serious problems as a result of rapid urban population growth. Not the least of these problems is the creation of environmental stresses at the rural-urban fringe of these cities as they increase in area and envelop fertile surrounding agricultural lands. Because of this rapid rate of growth, sustainable urban environmental management (SUEM) policies and practices are often difficult to develop and implement proactively. This thesis argues that rapid population growth and subsequent urban expansion occurs such that urban form and function are built around the transportation network. In this context, a basic requirement for the facilitation of SUEM is the ability to be able to detect and extract indicators of urban expansion, in particular the road network, from available satellite remote sensing (RS) data. Subsequently, the indictors of growth derived from RS imagery can be integrated into a multi-source GIS database with ground-based census data to facilitate potential environmental stress analysis. The extraction of useful data from RS imagery for GIS-based analysis of urban growth is achieved through an integrated conceptual and operational framework presented in the thesis. This framework allows for environmental stress analysis at the urban periphery that can assist with the design of policies to contain urban growth.

It has become very crucial to manage water resources to meet the needs of the growing population. In irrigation command areas, and in order to build a better plan to manage service delivery from canals and reservoirs, it is important to build appropriate knowledge of water needs on a field basis. There is often a lag between the order and delivery of water to the field. Knowledge of the crop water requirement at the field level helps the decision maker to make the right choices leading to more efficient handling of the available water. The purpose of this study was to develop methodologies and tools that allow better management of irrigation water and water delivery systems, such as machine learning models that can be used as tools for decision support systems of water management. To achieve better modeling and prediction, wavelet decompositions were explored for their ability to give information about time and frequency changes in the data. Remote sensing approaches were also used for their ability to quantify water requirements at the spatial level. Therefore, this dissertation explored the use of the above-mentioned data tools and techniques to address water management problems. The framework of this dissertation consisted of three components that provide tools to support irrigation system operational decisions. In general, the results for each of the methods developed were satisfactory, relevant, and encouraging. They provided significant potential for improving decision making for real-time applications in irrigation command areas and better management of the water resources.

There is an undisputed need to increase accuracy of snow cover estimation in regions comprised of complex terrain, especially in areas dependent on winter snow accumulation for a substantial portion of their annual water supply, such as the Western United States, Central Asia, and the Andes. Presently, the most pertinent monitoring and research needs related to alpine snow cover area (SCA) are: (1) to improve SCA monitoring by providing detailed fractional snow cover (FSC) products which perform well in temporal/spatial heterogeneous forested and/or alpine terrains; and (2) to provide accurate measurements of FSC at the watershed scale for use in snow water equivalent (SWE) estimation for regional water management.

To address the above, the presented research approach is based on Landsat Fractional Snow Cover (Landsat-FSC), as a measure of the temporal/spatial distribution of alpine SCA. A fusion methodology between remotely sensed multispectral input data from Landsat TM/ETM+, terrain information, and IKONOS are utilized at their highest respective spatial resolutions. Artificial Neural Networks (ANNs) are used to capture the multi-scale information content of the input data compositions by means of the ANN training process, followed by the ANN extracting FSC from all available information in the Landsat and terrain input data compositions. The ANN Landsat-FSC algorithm is validated (RMSE ~ 0.09; mean error ~ 0.001-0.01 FSC) in watersheds characterized by diverse environmental factors such as: terrain, slope, exposition, vegetation cover, and wide-ranging snow cover conditions. ANN input data selections are evaluated to determine the nominal data information requirements for FSC estimation. Snow/non-snow multispectral and terrain input data are found to have an important and multi-faced impact on FSC estimation. Constraining the ANN to linear modeling, as opposed to allowing unconstrained function shapes, results in a weak FSC estimation performance and therefore provides evidence of non-linear bio-geophysical and remote sensing interactions and phenomena in complex mountain terrains. The research results are presented for rugged areas located in the San Juan Mountains of Colorado, and the hilly regions of Black Hills of Wyoming, USA.

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.

Research in global ecology has been concerned with the effect of vegetation removal in semi-arid regions including aspects such as plant succession and desertification and its impact on global change, specifically global warming. In addition, conditions along international borders often are presented as discontinuities in terms of vegetation and soil status. To better document these discontinuities in a semi-arid region, a multi-temporal study along the U.S.-Mexico border was conducted with a series of six Landsat Thematic Mapper (TM) images acquired over the 1992 growing season. Spatial and temporal variations across the border were analyzed with reflectance data. Spatial data was obtained from three different sampling size areas which included: the Parker Canyon grassland; the San Rafael Valley, a grassland combined with riparian areas and croplands; and the regional area along the Arizona-Sonora border including valleys and mountains, and diverse vegetation communities and soil conditions. These areas consisted of about 106 ha, 5,800 ha, and 738,000 ha, respectively, at each side of the border. Temporal data were obtained from the six TM images which were acquired in days of the year 162, 178, 194, 274, 306, and 322. Four remote sensing applications were considered for comparison studies on both sides of the border. These techniques included: (a) band comparisons, (b) albedo, derived from the discrete sensor band information, (c) vegetation indices, and (d) application of a linear mixing model. When comparing both sides of the border, significant differences were observed in most of the remote sensing techniques applied at the Parker Canyon area. Higher differences were found during the wet season with all of the applied techniques with the exception of albedo. The red band and albedo were the most important discriminants during the dry season. At the intermediate size, San Rafael Valley area, U.S.-Mexico differences followed the same pattern as Parker Canyon, but statistically, these differences were deemed insignificant. At the regional area, no differences were observed between the U.S. and Mexican side. The effect of pixel aggregation using the different remote sensing techniques and ground data from field campaigns in 1995 were also analyzed.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
The current study aims through some geotechnologies generating a data basis characterized with three hydrographic basins which are inserted in the Palma Sola S/A properties that works with logs in the county of Palma Sola. After characterizing the basins, it has been mapped the properties and it has been analyzed their representativeness in such basins, besides establishing conceptual basis needed to understand the matter. The work has aimed also to subsidy the environmental certification for the company which has acquired the FSC international seal, adjusting to the legislation encouraging the good practices of deforestation management. It has been made the proprieties digital maps of soil use and occupation, following the INCRA (Institute of Colonization for Agrarian Reform) technical policies for geo-referencing of rural properties for registration of the property, maps of use and soil occupation of hydrographic basins, maps with hydrographic and use of the soil in areas of permanent preservation, hypsometric maps, declivity and Numerical Model of the Terrain of hydrographic basins, 3D view and the profile of the hydrographic basins. The data obtained allowed to consider that the geotechnologies are a great tool in helping the environmental planning of hydrographic basins and forest certification, they generate information that answer the FSC principles and help on the reduction of environmental impact in hydrographic basins. The forest certification appeared as a great inductor of forest management good practices according to the environmental legislation.
O presente estudo busca, por meio de algumas geotecnologias, gerar uma base de dados com a caracterização de três bacias hidrográficas em que estão inseridas as propriedades da empresa Palma Sola S/A, que atua no setor madeireiro, no município de Palma Sola/SC. Após a caracterização das bacias, mapeou-se as propriedades e analisou-se a representatividade das mesmas nas respectivas bacias, além de estabelecer bases conceituais necessárias ao entendimento do assunto. O trabalho realizado teve como intuito, também, subsidiar a certificação ambiental do setor florestal da empresa, que adquiriu o selo internacional FSC® (Forest Stewardship Council), adequando-se à legislação e incentivando as boas práticas de manejo florestal. Foram elaborados os mapas digitais de uso e ocupação do solo das propriedades com perímetro seguindo as normas técnicas para georreferenciamento de imóveis rurais do INCRA (Instituto de Colonização e Reforma Agrária) para o cadastramento do imóvel, mapas de uso e ocupação do solo das bacias hidrográficas, mapas com a hidrografia e uso do solo em Áreas de Preservação Permanente, mapas hipsométricos, de declividade e Modelo Numérico do Terreno das bacias hidrográficas, visualização 3D e do perfil das bacias hidrográficas. Os dados obtidos permitiram considerar que as geotecnologias apresentaram-se como uma ótima ferramenta no auxílio ao planejamento ambiental das bacias hidrográficas e à certificação florestal, pois geram informações que atendem aos princípios do FSC® e auxiliam na redução do impacto ambiental nas bacias hidrográficas. A certificação florestal se apresentou como um ótimo indutor das boas práticas de manejo florestal em conformidade com a legislação ambiental.

Medusahead is a harmful weed that is invading public lands in the West. The invasion is a serious concern to the public because it can reduce forage for livestock and wildlife, increase fire frequency, alter important ecosystem cycles (like water), reduce recreational activities, and produce landscapes that are aesthetically unpleasing. Invasions can drive up costs that generally require taxpayer’s dollars. Medusahead seedlings typically spread to new areas by attaching itself to passing objects (e.g. vehicles, animals, clothing) where it can quickly begin to affect plants communities. To be effective, management plans need to be sustainable, informed, and considerate to invasion levels across large landscapes. Ecological remote sensing analysis is a method that uses airborne imagery, taken from drones, aircrafts, or satellites, to gather information about ecological systems. This Thesis strived to use remote sensing techniques to identify medusahead in the landscape and its changes through time. This was done for an extensive area of rangelands in the Channel Scabland region of eastern ashington. This Thesis provided results that would benefit land managers that include: 1) a dispersal map of medusahead, 2) a time line of medusahead cover through time, 3) “high risk’ dispersal areas, 4) climatic factors showing an influence on the time line of medusahead, 5) a strategy map that can be utilized by land managers to direct management needs. This Thesis shows how remote sensing applications can be used to detect medusahead in the landscape and understand its invasiveness through time. This information can help create sustainable and effective management plans so land managers can continue to protect and improve western public lands threatened by the invasion of medusahead.

Thesis (M.S. in Computer Science)--Naval Postgraduate School, March 2006.
Thesis Advisor(s): Cynthia E. Irvine, Thuy D. Nguyen. "March 2006." Includes bibliographical references (p. 123-124). Also available online.

Irrigation systems are designed to deliver water to crops, but their efficacy varies widely due to operational decisions, weather variability, and water availability. The operation of an irrigation system is studied in this dissertation to determine irrigation performance and potential for improvement.Satellite remote-sensing was used to determine inter-annual variability in crop evapotranspiration and link it with weather patterns and operational decisions. A decade was studied to include several dry, wet and average years of snowfall. It was found that the irrigation district has the capacity to buffer a dry year, but crop evapotranspiration patterns indicated that the buffer capacity of the irrigation district is limited in a second dry year. Studying the current operations of an irrigation system also requires an analysis of the spatial variability within the system to identify potential areas for improvement. Achieving such information is challenging due to the spatial heterogeneity between farm fields. The Ador irrigation system simulation model is used in this study with satellite remote sensing data, which were combined in the calibration and validation process to ease the re-adjustment of management parameters. This approach provides a cost-effective and innovative method for model simulation when field observations are limited. Alternative water delivery scenarios were simulated with the Ador irrigation system simulation model to quantify changes in the water balance, irrigation performance, and water productivity. Results for implementing a minimal irrigation time indicated that irrigation events occurred with a higher frequency and reduced crop water stress. Water productivity for the irrigation district increased substantially in this scenario, whilst district water savings were achieved by diverting less irrigation water. Advantages are only achieved if farmers collectively make the decision to change. A water accounting analysis is required to examine if water savings are achieved at basin scale. There is a potential for the rebound effect to occur, which suggests that an increase of water efficiency causes the increase of water consumption. Simulation results indicated that if the efficiency is increased through improvements of the water delivery, the water consumption increased. Water savings achieved by reducing irrigation diversions did not compensate for the decrease in drainage that downstream users depend on.

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.

The current study has been conducted in response to the growing problem of water scarcity and the need for more effective methods of irrigation water management. Remote sensing techniques have been used to match spatially and temporally distributed crop water demand to water application rates. Remote sensing approaches using Landsat imagery have been applied to estimate the components of a soil water balance model for an agricultural field by determining daily values of surface/root-zone soil moisture, evapotranspiration rates, and losses and by developing a forecasting model to generate optimal irrigation application information on a daily basis. Incompatibility of coarse resolution Landsat imagery (30m by 30m) with heterogeneities within the agricultural field and potential underestimation of field variations led the study to its main objective, which was to develop models capable of representing spatial and temporal variations within the agricultural field at a compatible resolution with farming management activities. These models support establishing real-time management of irrigation water scheduling and application. The AggieAirTM Minion autonomous aircraft is a remote sensing platform developed by the Utah Water Research Laboratory at Utah State University. It is a completely autonomous airborne platform that captures high-resolution multi-spectral images in the visual, near infrared, and thermal infrared bands at 15cm resolution. AggieAir flew over the study area on four dates in 2013 that were coincident with Landsat overflights and provided similar remotely sensed data at much finer resolution. These data, in concert with state-of-the-art supervised learning machine techniques and field measurements, have been used to model surface and root zone soil volumetric water content at 15cm resolution. The information provided by this study has the potential to give farmers greater precision in irrigation water allocation and scheduling.

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For proper exploitation of natural resources, it is necessary, besides the use of tools that assist in the planning of environmental activities and detailed knowledge of the region, an accurate environmental perception of those who inhabit this environment. Therefore, the aim of this paper is to propose a methodology for environmental management that helps in the understanding of processes related to conservation of natural resources with emphasis on its employees and neighboring communities. The study was carried out at Embrapa Acre with the use of direct and indirect research techniques (questionnaires), and also tools necessary for the utility of a geographic information system (GIS). To enhance the environmental perception of the communities involved two kinds of questionnaires were applied with closed and choice multiple questions. These were applied in the employees and neighboring communities levels, which resulted in a better understanding of the existing potentiality for development and the socioeconomic factors of the locality. We observed evident possibilities for the increase of the use of natural resources in the experimental field. The questionnaire results pointed and suggested practical unit developments, such as the reforestation of permanent preservation areas. These facts were corroborated by studies in the evaluation of field data collected and integrated in remote sensing. We highlighted the photointerpretation and as a result the suggestion of the adoption of a GIS by the company. Besides the theoretical emphasis, the compatibility between the use of aerial photographs and data mining was supported by softwares such as ArcGIS and made it possible the development of a database, which included the creation and development of spatial structures recognized and measured in field with the use of geographic position system (GPS). Thus, by means of experimental results obtained, the method of photointerpretation presented effective classification of the experimental field of Embrapa Acre, with elaboration of thematic maps of the area and a GIS. Allied to these techniques, the study infers the global perception of the community and employees as essential and confirms that environmental care has acquire more social and ecological sensitivity, in search of a better quality of life and sustainable development.
Para a exploração adequada dos recursos naturais é necessário, além da utilização de ferramentas que auxiliem no planejamento das atividades ambientais e do conhecimento detalhado da região, uma percepção ambiental apurada daqueles que habitam este meio. Portanto, o objetivo desse trabalho é propor uma metodologia de gestão ambiental que auxilie na compreensão dos processos relacionados à conservação dos recursos naturais, com ênfase em seus colaboradores e comunidades vizinhas. O estudo foi desenvolvido no campo experimental da Embrapa Acre com utilização de técnicas de pesquisa direta e indireta (questionários), além de ferramentas necessárias para utilização de um sistema de informação geográfica (SIG). Para acrescer a percepção ambiental das comunidades envolvidas, foram aplicados dois modelos de questionários com perguntas fechadas e de múltiplas escolhas. Estes foram aplicados nos níveis de colaboradores e das comunidades vizinhas, o que resultou uma melhor compreensão das potencialidades existentes de desenvolvimento e os fatores socioeconômicos da localidade. Observaram-se evidentes possibilidades de aumento do uso dos recursos naturais do campo experimental, como, por exemplo, o reflorestamento de áreas de preservação permanente. Este último, apoiado pelo estudo na avaliação dos dados de campo coletados e integrados no sensoriamento remoto. Destacou-se a fotointerpretação e, como resultado, a sugestão de adoção pela Empresa de um SIG. Além da ênfase teórica a compatibilidade entre o uso de fotografias aéreas e a mineração de dados, apoiou-se em softwares como o ArcGIS e tornou-se possível a elaboração de uma base de dados, que contou com a criação e elaboração de estruturas espaciais reconhecidas e aferidas no campo com auxílio de GPS Global Positioning System . Assim, por meio dos resultados experimentais obtidos, o método da fotointerpretação apresentou efetividade de classificação do campo experimental da Embrapa Acre, com elaboração de mapas temáticos da área e um SIG. Aliado a essas técnicas o estudo infere a percepção global das comunidades e colaboradores como essencial e confirma que o cuidado ambiental adquiriu maior sensibilidade social e ecológica na busca de uma melhor qualidade de vida e desenvolvimento sustentável.

Widespread mortality of quaking aspen (Populus tremuloides Michx.) has occurred over large expanses of the Western US during the 20th century. While much of this decline was due to conifer encroachment into seral aspen, significant aspen losses also occurred in areas of persistent aspen and may have been exasperated by drought conditions. Aspen decline has been especially notable at Cedar Mountain, Utah, an area of mostly private land and extensive persistent aspen coverage. The objectives of this study were to create a time series of live and dead aspen cover on the Cedar Mountain landscape, using remotely sensed imagery, and to test whether water stress correlated to the decline therein. To accomplish these objectives, a decision tree classifier was used to classify the Cedar Mountain area into live and dead aspen cover classes for the years 1985, 1990, 1995, 2001, 2005, and 2008. Thereafter, post-classification change analysis was performed to determine areas and time periods of elevated decline. Regression analyses were performed to ascertain correlations between climatic data and percent change in aspen cover. A topographic analysis using zonal statistics was also performed to determine landscape positions where aspen decline is more prevalent. The time series models indicated that aspen decline followed a step-wise pattern with an overall decrease of 23.57 % in aspen cover during a 23-year period. Considerable aspen decline occurred early in the study time frame, with decreases of 1.38 and 1.36 -1 in 1990 and 1995, respectively. The middle period between 1995 and 2001 had no net change in aspen cover. However, the end of the time series showed the greatest decline with decreases of 1.56 and 1.99 % yr-1 in 2005 and 2008, respectively. There was a correlation between percent change in aspen cover and precipitation, suggesting that drought weakens aspen, making it susceptible to future decline. The topographic zonal statistics revealed that drier landscape positions had greater frequencies of dead aspen. The most significant predictor of aspen decline was elevation, which was significantly greater in the live aspen for three of the five years.

Um quadro diagnóstico da Área de proteção Ambiental(APA) do Capivari Monos foi elaborado com informações produzidas através da aplicação de geoprocessamento e sensoriamento remoto. Essa Unidade de Conservação se localiza no extremo sul do município de São Paulo, onde ainda existem importantes fragmentos de Mata Atlântica e mananciais hídricos estratégicos para a Região Metropolitana de São Paulo . Um Mapa Geomorfológico foi produzido com o apoio de um Modelo Numérico de Terreno. Com a aplicação de Álgebra de Mapas, foram integrados os dados sobre Geotecnia e Geomorfologia e um mapa de Fragilidade do Meio Físico foi elaborado. As condições de hidrografia e relevo apontaram indícios de movimentação tectônica recente na região. Imagens dos Satélites Landsat-5 e Landsat-7 foram comparadas, com o emprego de técnicas de detecção de mudanças, para a quantificação do desmatamento no período entre 1991 e 2000. As imagens do satélite Landsat-7 foram classificadas, através do método supervisionado por regiões, para produção de um mapa temático de Uso do Solo e Cobertura Vegetal. Os resultados foram quantificados por sub-bacias hidrográficas, compondo um quadro comparativo que se destina a subsidiar a gestão ambiental da APA. Esses resultados mostram que o crescimento da ocupação urbana se concentra na bacia da Billings, principalmente na subbacia da Cratera de Colônia, onde a fragilidade do meio físico foi considerada muito alta.
Through the application of Geographical Information System and Remote Sensing it was elaborated a chart diagnosis for Capivari-Monos Environmental Protection Area. This Conservation Unit is located in the south end of São Paulo city where important Atlantic Forest fragments and strategic water spring still exist. With the support of a Digital Terrain Model it was produced a Geomorphologic map. Applying Map Algebra the data on Geothecnics and Geomorphorlogy had been integrated for mapping the fragility of physical environment. Relief and hidrography conditions pointed indications of neotectonic movements in this region. Employing change detection techniques in Landsat-7 images the deforestation between 1991 and 2000 was evaluated. A land use and land cover map was produced trough Landsat-7 image classification ( supervised per region method). The results show that the urban growth concentrates on the basin of Billings, mainly at the Cratera de Colônia sub-basin where the fragility regarding to phisical environment was considered very high.

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.

Beaver Creek is an impaired streams that is not supporting its designated use for recreation due to Escherichia coli (E.coli), and sediment. To address this problem, this thesis was divided into two studies. The first study explored changes in Land Use Land Cover (LULC), and its impact on surface water quality. Changes in E.coli load between 1997-2001 and 2014-2018 were analyzed. Also, Landsat data of 2001, and 2018 were examined in Terrset 18.31. Mann-Whitney test only showed a significant reduction in E.coli for one site. Negative correlation was established between E.coli load, and Developed LULC, Forest LULC, and Cultivated LULC. The second study modelled discharge for Beaver Creek watershed using HEC-HMS. This study simulated discharge in an upstream sub-watershed of Beaver Creek, and the full Beaver Creek with a Nash-Sutcliffe of 0.007, and R2 0.20. Sub-basins with high discharge were identified for further examination for possible high sediment load.

Increasing population and water conflicts are making water management one of the most important issues of the present world. It has become absolutely necessary to find ways to manage water more efficiently. Technological advancement has introduced various techniques for data acquisition and analysis, and these tools can be used to address some of the critical issues that challenge water resource management. This research used learning machine techniques and information acquired through remote sensing, to solve problems related to soil moisture estimation and crop identification on large spatial scales. In this dissertation, solutions were proposed in three problem areas that can be important in the decision making process related to water management in irrigated systems. A data assimilation technique was used to build a learning machine model that generated soil moisture estimates commensurate with the scale of the data. The research was taken further by developing a multivariate machine learning algorithm to predict root zone soil moisture both in space and time. Further, a model was developed for supervised classification of multi-spectral reflectance data using a multi-class machine learning algorithm. The procedure was designed for classifying crops but the model is data dependent and can be used with other datasets and hence can be applied to other landcover classification problems. The dissertation compared the performance of relevance vector and the support vector machines in estimating soil moisture. A multivariate relevance vector machine algorithm was tested in the spatio-temporal prediction of soil moisture, and the multi-class relevance vector machine model was used for classifying different crop types. It was concluded that the classification scheme may uncover important data patterns contributing greatly to knowledge bases, and to scientific and medical research. The results for the soil moisture models would give a rough idea to farmers/irrigators about the moisture status of their fields and also about the productivity. The models are part of the framework which is devised in an attempt to provide tools to support irrigation system operational decisions. This information could help in the overall improvement of agricultural water management practices for large irrigation systems. Conclusions were reached based on the performance of these machines in estimating soil moisture using remotely sensed data, forecasting spatial and temporal variation of soil moisture and data classification. These solutions provide a new perspective to problem–solving techniques by introducing new methods that have never been previously attempted.

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.

Spatial-temporal distribution of soil moisture in the vadose zone is an important aspect of the hydrological cycle that plays a fundamental role in water resources management, including modeling of water flow and mass transport. The vadose zone is a critical transfer and storage compartment, which controls the partitioning of energy and mass linked to surface runoff, evapotranspiration and infiltration. This dissertation focuses on integrating hydraulic characterization methods with remote sensing technologies to estimate the soil moisture distribution by modeling the spatial coverage of soil moisture in the horizontal and vertical dimensions with high temporal resolution. The methodology consists of using satellite images with an ultrafine 3-m resolution to estimate soil surface moisture content that is used as a top boundary condition in the hydrologic model, SWAP, to simulate transport of water in the vadose zone. To demonstrate the methodology, herein developed, a number of model simulations were performed to forecast a range of possible moisture distributions in the Everglades National Park (ENP) vadose zone. Intensive field and laboratory experiments were necessary to prepare an area of interest (AOI) and characterize the soils, and a framework was developed on ArcGIS platform for organizing and processing of data applying a simple sequential data approach, in conjunction with SWAP. An error difference of 3.6% was achieved when comparing radar backscatter coefficient (σ0) to surface Volumetric Water Content (VWC); this result was superior to the 6.1% obtained by Piles during a 2009 NASA SPAM campaign. A registration error (RMSE) of 4% was obtained between model and observations. These results confirmed the potential use of SWAP to simulate transport of water in the vadose zone of the ENP. Future work in the ENP must incorporate the use of preferential flow given the great impact of macropore on water and solute transport through the vadose zone. Among other recommendations, there is a need to develop procedures for measuring the ENP peat shrinkage characteristics due to changes in moisture content in support of the enhanced modeling of soil moisture distribution.

Master of Arts
Department of Geography
J. M. Shawn Hutchinson
Time series of normalized difference vegetation index (NDVI) data from satellite spectral measurements can be used to characterize and quantify changes in vegetation phenology and explore the role of natural and anthropogenic activities in causing those changes. Several programs and methods exist to process phenometric data from remotely-sensed imagery, including TIMESAT, which extracts seasonality parameters from time-series image data by fitting a smooth function to the series. This smoothing function, however, is dependent upon user-defined input parameter settings which have an unknown amount of influence in shaping the final phenometric estimates. To test this, a sensitivity analysis was conducted using MODIS maximum value composite NDVI time-series data acquired for Fort Riley, Kansas during the period 2001-2012. The phenometric data generated from the different input setting files were compared against that from a base scenario using Pearson and Lin’s Concordance Correlation Analyses. Findings show that small changes to parameter settings results in insignificant differences in phenometric estimates, with the exception of end of season data and growing season length. Next, a time-series analysis of the same MODIS NDVI data for Fort Riley and nearby Konza Prairie Biological Station (KPBS) was conducted to determine if significant differences existed in selected vegetation phenometrics. Phenometrics of interest were estimated using TIMESAT and based on a Savitzky-Golay filter with parameter settings found optimal in the previous study. The phenometrics start of season, end of season, length of season, maximum value, and small seasonal integral were compared using Kolmogorov-Smirnov (K-S) and showed significant differences existed for all phenometrics in the comparison of Fort Riley training areas and KPBS, as well as low- versus high-training intensity areas within Fort Riley. Fort Riley and high-intensity training areas have earlier dates for the start and end of the growing season, shorter growing season lengths, lower maximum NDVI values, and lower small seasonal integrals compared to KPBS and low-intensity training areas, respectively. Evidence was found that establishes a link between military land uses and/or land management practices and observed phenometric differences.

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.

Orientador: Jansle Vieira Rocha
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agricola
Made available in DSpace on 2018-08-04T06:01:57Z (GMT). No. of bitstreams: 1 Scheer_MarciaAparecidaProcopiodaSilva_D.pdf: 6623925 bytes, checksum: 85b9318d09e09bcd2acaf81b338eeea0 (MD5) Previous issue date: 2004
Resumo: Esta pesquisa teve como foco de estudo detectar as transformações ocorridas no uso da terra na área que abrange municípios componentes do Comitê da Bacia Hidrográfica do Rio Mogi-Guaçu (SP) - CBH-Mogi, entre 1979 e 2001. Ela foi dividida em três etapas distintas. A primeira teve como objetivo a elaboração de um banco de dados de atributos com os resultados da aplicação do modelo Shift-Share sobre dados estatísticos coletados nos Anuários de Produção Agrícola Municipal do Instituto Brasileiro de Geografia e Estatística -IBGE. Os cultivos agrícolas estudados foram: algodão, arroz, café, cana-de-açúcar, feijão, laranja, milho e soja para cada um dos trinta e oito municípios componentes do CBH-Mogi nos conjuntos trienais de 1979/1980/1981, 1989/1990/1991 e 1999/2000/2001. A segunda etapa consistiu na elaboração de um banco de dados espaciais com a análise multitemporal do uso da terra, cujas classes de mapeamento foram cana-de-açúcar, cultura anual, café, citrus e outros usos, para seis municípios componentes do CBH-Mogi (Barrinha, Dumont, Jaboticabal, Pitangueiras, Santa Lúcia e Sertãozinho) por meio de imagens de satélites LANDSAT 2-MSS, órbita/ponto: 235/075 (A e C), 235/076 (A) e 236/075 (A, B e D) do ano de 1981;LANDSAT 5-TM, órbita/ponto: 219/075 (A e C), 219/076 (A) e 220/075 (A, B e D) do ano de 1990; e LANDSAT7-ETM+, órbita/ponto: 219/075 (A e C), 219/076 (A) e 220/075 (A, B e D) do ano de 2001. Na terceira etapa foram realizadas a integração e comparação das duas metodologias de análise da mudança do uso da terra e a produção agrícola, sendo que os resultados evidenciaram que elas são complementares para as análises realizadas. Enquanto o modelo Shift Share tem como principal característica quantificar os principais componentes de variação agrícola, o estudo das transformações no uso da terra por meio de geoprocessamento fez com que fossem locados onde ocorreram estas mudanças e com isso possibilitou inferir sobre as causas que levaram a tal transformação. Na área de estudo pode-se notar que a expansão da produção agrícola ocorreu principalmente pela substituição dos cultivos agrícolas menos rentáveis pela canade- açúcar e também pelo uso mais intensivo da terra, conseqüência do avanço tecnológico no processo produtivo, de políticas governamentais e das tendências do mercado econômico regional, nacional e mundial
Abstract: This research identified the main factors that influenced the land use changes in counties belonging to the Mogi-Guaçu river Watershed Committe, between 1979 and 2001. The area is located in a strategic geographical region and has a significant agricultural production at the state, national and international levels. This study was carriOOout in three steps. The first one had the objective of elaborating a database with the results of the Shift-Share model applied to the statistic data gathered from the Annual Agricultural Municipal Production Report, ftom the Brazilian Institute of Geography and Statistics (IBGE), for the study area in periods of three years: 1979/80/81, 1989/90/91 and 1999/2000/2001. The se~ond step consisted of elaborating a Spatial Database, with the multitemporal analysis of the ~ agricultural land use within the study area (Barrinha, Dumont, Jaboticabal, Pitangueiras, Santa Lúcia and Sertãozinho) using LANDSAT2-MSS, patb/row 235/075 (A e C), 235/076 (A) and 236/075 (A, B e D) of 1981;LANDSAT 5-TM, path/row 219/075 (A e C), 219/076 (A) and 220/075 (A, B e D) of 1990; and LANDSAT 7-ETM+, patb/row 219/075 (A e C), 219/076 (A) e 220/075 (A, B e D) of 2001. The third part was the integration and comparison of the two methodologies for the analysis of land use changes and agricultural production. The resuhs had evidenced that they are complementary for the carried through analyses. The Shift Share model basic characteristic is to quantify the main components of agricultural variation, while the study of land use changes using geoprocessing gave a geographicallocation of these changes possibiliting to analyse causes that had 100 to such transformation. In the study area it can be noticed that the the expansion of agricultural production occured mainly because the substitution of lesser yield agricultural crops by sugarcane, and also by more agricultural intesive land use
Doutorado
Planejamento e Desenvolvimento Rural Sustentável
Doutor em Engenharia Agrícola

Thesis (MSc)--Stellenbosch University, 2013.
ENGLISH ABSTRACT: Current efforts to address Zimbabwe‘s decade long veld fire crisis has partly been hindered by a lack of financial resources and fire data. This study illustrates the potential of using the MODIS burned area product as an alternative cost- and time-effective method for reconstructing historical fire records in Zimbabwe. Two MODIS burned area products were evaluated, namely the MCD45A1 and WAMIS (Meraka Institute‘s MODIS burned area product). Both products yielded similar levels of accuracy despite the difference in algorithms. However, it is assumed that at certain thresholds, either in tree cover or fire intensity, WAMIS ceases to map fires as accurately as the MCD45A1. Ten years of fire data for Charara Safari Area (CSA) was extracted from the MCD45A1, and used as a basis to establish six parameters: fire incidence, extent, seasonality, fire size, frequency and fire return interval (FRI). It was observed that approximately 50% of CSA burned annually, with an average of 132 fires occurring every year. Although there was no overall increase or decrease in the extent of area burned over the 10 year study period, an increasing trend in fire incidence was noted. Through an assessment of effective fire size, it was established that more fires in CSA were gradually becoming smaller in size, while the extent of area burned remained fairly constant. Hence, the increase in fire incidences and lack of a corresponding increase in area burned. This study was also used to identify areas in the fire regime that may be a potential ecological risk to the miombo woodland in CSA. Three points of concern were revealed: firstly, a high prevalence of late season fires was observed in the northern bounds of CSA. Secondly, 64.2% of the total area burned in CSA burned between 6 and 10 times over the 10 year period, and lastly, 85% of the total area burned over the period 2001 and 2010 had a FRI of less than 2 years. The combination of late season fires, high fire frequency and short FRI in CSA is indicative of possible alterations in the state of the miombo woodlands, which may have negative socio-economic implications on CSA and its surrounding communities. This study has demonstrated that the MCD45A1 is a useful source of much needed fire information for Zimbabwe. Therefore, the possibility of integrating methods employed in this study into the current collection of fire data should be given due consideration.
AFRIKAANSE OPSOMMING: Huidige pogings om Zimbabwe se dekade lank veldbrand krisis aan te spreek is gedeeltelik belemmer deur 'n gebrek aan finansiële hulpbronne en vuurdata. Hierdie studie illustreer die potensiaal van die gebruik van die MODIS verbrande area produk as 'n alternatiewe koste-en tyd-effektiewe metode vir die rekonstruksie van historiese vuurrekords in Zimbabwe. Twee MODIS verbrande area produkte is geëvalueer, naamlik die MCD45A1 en WAMIS (Meraka Instituut se MODIS verbrand area produk). Beide produkte het soortgelyke vlakke van akkuraatheid opgelewer ten spyte van die verskil in die algoritmes. Dit word egter aanvaar dat op sekere drempels, óf in die boom bedekking, of brandintensiteit, WAMIS brande minder akkuraat karteer as die MCD45A1 produk. Tien jaar van vuurdata vir Charara Safari Area (CSA) is uit die MCD45A1 data onttrek, en gebruik as 'n basis om ses parameters vas te stel: vuurvoorkoms, omvang, seisoenaliteit, vuurgrootte, frekwensie en tyd tussen die terugkeer van vuur na ‗n spesifieke plek (nl. FRI). Dit is waargeneem dat ongeveer 50% van die CSA jaarliks gebrand word, met 'n gemiddeld van 132 brande wat elke jaar voorkom. Daar was nie 'n algehele toename of afname in die omvang van die totale verbrande area oor die 10 jaar studietydperk nie. Maar 'n toenemende neiging in die vuurvoorkoms was wel opgemerk. Deur middel van 'n assessering van effektiewe vuurgrootte, is daar vasgestel dat meer kleiner brande in CSA voorkom, terwyl die omvang van die verbrand area redelik konstant gebly het. Dus was daar ‗n toename in die aantal vuurvoorvalle al was daar nie 'n ooreenstemmende toename in die totale verbrande oppervlakte was nie. Hierdie studie is ook gebruik om gebiede in die vuurregime te identifiseer wat 'n potensiële ekologiese risiko vir die miombobosveld in CSA inhou. Drie punte van kommer word geopenbaar: eerstens, 'n hoë voorkoms van laatseisoen brande is waargeneem in die noordelike grense van CSA. Tweedens, 64,2% van die totale verbrande oppervlakte in die CSA brand tussen 6 en 10 keer bine die 10-jaar periode. Laastens, 85% van die totale verbrande oppervlakte oor die tydperk 2001 tot 2010 het 'n FRI van minder as twee jaar. Die kombinasie van laatseisoen brande, hoë vuurfrekwensie en kort FRI in CSA is 'n aanduiding van moontlike veranderinge in die toestand van die miomboveld, wat negatiewe sosio-ekonomiese implikasies op die CSA en die omliggende gemeenskappe kan uitoefen. Hierdie studie het getoon dat die MCD45A1 'n nuttige bron van broodnodige vuur inligting vir Zimbabwe is. Daarom, moet die moontlikheid van die integrasie van die metodes wat gebruik word in hierdie studie in die huidige versameling van vuurdata behoorlike oorweging gegee word.

Geografinei informacijai apie erdvinį žemės paviršių kaupti pastaruoju metu vis dažniau naudojamas vietovės skenavimo lazeriu iš orlaivio metodas LIDAR (Light Detection and Ranging). Šiuo metodu gaunama nereguliari taškinė labai tanki trijų dimensijų žemės paviršiaus objektų išsidėstymą sumodeliuojanti geometrinė ir radiometrinė informacija. Tai gana neseniai atsiradęs būdas, naudojamas žemės topografijos duomenims užrašyti, kuris Lietuvoje dar tik pradedamas naudoti. Dėl to naudinga ištirti šio metodo patikimumą, palyginant su įprastais duomenų surinkimo metodais (GPS), ir įvertinti šio metodo panaudojimo galimybes. Darbe nagrinėjama nuotolinių tyrimų metodais (LIDAR) gautų duomenų patikimumo problema. Tyrimo tikslas – nustatyti įvairiais metodais gautų reljefo aukščių duomenų patikimumą, analizuojant Riešės upelio baseino reljefą. Tyrimo eigoje buvo surinkti įvairiais metodais gauti Riešės upelio baseino reljefo duomenys; atlikti natūriniai matavimai pasirinktuose kontroliniuose ploteliuose, naudojantis geodeziniais instrumentais; pagal nuotolinių tyrimų gautus rezultatus sudarytas skaitmeninis reljefo modelis ir įvertintas jų tikslumas. Darbe palyginus natūrinių matavimų ir nuotolinių tyrimų metodais gautus rezultatus įrodyta, jog nuotoliniais tyrimų metodais gauti duomenys yra patikimi ir juos galima naudoti baseino tūriui ir plotui skaičiuoti.
LIDAR terrain laser scanning technique is increasingly used in digital terrain model creation. This method provides dense uneven three-dimensional scatter geometric and radiometric information that simulates objects on earth’s surface. This is a relatively recent method used to record topographic data of the land. One of the key issues still associated with remote sensing methods is its reliability, which is why it is relevant to analyze and evaluate this aspect. This thesis aims at evaluating LIDAR data reliability, comparing them with data obtained by field measurements carried out at selected control areas using geodesic instruments. Riešės river basin area was selected as an object for the study and its elevation data have been investigated in the research. It was concluded that LIDAR data are reliable and can be used for the basin volume calculation. However, the size of the grid should be selected according to terrain relief.

Net primary productivity (NPP) is a key ecological parameter that is important in estimating carbon stocks in large forested areas. NPP is estimated using models of which leaf area index (LAI) is a key input. This research computes a variety of ground-based and remote sensing LAI estimation approaches and examines the impact of these estimates on modeled NPP. A relative comparison of ground-based LAI estimates from optical and allometric techniques showed that the integrated LAI-2000 and TRAC method was preferred. Spectral mixture analysis (SMA), accounting for subpixel influences on reflectance, outperformed vegetation indices in LAI prediction from remote sensing. LAI was shown to be the most important variable in modeled NPP in the Kananaskis, Alberta region compared to soil water content (SWC) and climate inputs. The variability in LAI and NPP estimates were not proportional, from which a threshold was suggested where first LAI is limiting than water availability.
xii, 181 leaves : ill. ; 28 cm.

Os SIG Sistemas de Informação Geográfica vêm sendo cada vez mais estudados como ferramentas facilitadoras de análises territoriais com o objetivo de subsidiar a gestão ambiental. A Ilha Grande, que pertence ao município de Angra dos Reis, localiza-se na baía de Ilha Grande no sul do estado do Rio de Janeiro e constitui-se no recorte espacial de análise. Apresenta uma dinâmica ambiental complexa que se sobrepõem principalmente aos usos de proteção ambiental e de atividade turística em uma porção do território em que as normatizações legais são difíceis de serem aplicadas, pois são reflexos de interesses que se manifestam em três esferas do poder a municipal, a estadual e a federal. O objetivo principal desta pesquisa é a realização do processamento digital de imagem para auxiliar a gestão territorial da Ilha Grande. Em foco, a estrada Abraão - Dois Rios, que liga Abraão (local de desembarque dos turistas, principal núcleo da Ilha) a Dois Rios (local de visitação por estudantes e pesquisadores, núcleo que abrigava o presídio, atualmente abriga sede do centro de pesquisa e museu da Universidade do Estado do Rio de Janeiro), ambos protegidos por diferentes categorias de unidades de conservação. A metodologia fundamenta-se no processamento digital de imagem através da segmentação e da classificação supervisionada por pixel e por região. O processamento deu-se a partir da segmentação (divisão de uma imagem digital em múltiplas regiões ou objetos, para simplificar e/ou mudar a representação de uma imagem) e dos processos de classificações de imagem, com a utilização de classificação por pixel e classificação por regiões (com a utilização do algoritmo Bhattacharya). As segmentações e classificações foram processadas no sistema computacional SPRING versão 5.1.7 e têm como objetivo auxiliar na análise de uso da Terra e projetar cenários a partir da identificação dos pontos focais de fragilidade encontrados ao longo da estrada Abraão-Dois Rios, propensos a ocorrências de movimentos de massa e que potencializam o efeito de borda da floresta e os impactos ambientais. A metodologia utilizada baseou-se em análise de campo e comparações de tecnologias de classificação de imagens. Essa estrada eixo de ligação entre os dois núcleos tem significativa importância na história da Ilha, nela circulam veículos, pesados e leves, de serviço, pedestres e turistas. Como resultados da presente foram gerados os mapas de classificação por pixel, os mapas de classificação por região, o mapa fuzzy com a intersecção dos mapas de classificação supervisionada por região e os mapas com os locais coletados em campo onde são verificadas ocorrências de movimentos de massa nas imagens ALOS, 2000, IKONOS, 2003 e ortofotografias, 2006. Esses mapas buscam servir de apoio à tomada de decisões por parte dos órgãos locais responsáveis.
GIS - Geographic Information Systems - have been increasingly studied as tools that facilitate analysis of territorial order to subsidize environmental management. The Big Island, which belongs to the municipality of Angra dos Reis, located in the Bay of Ilha Grande in the southern state of Rio de Janeiro and constitutes the spatial area of analysis. Presents a complex dynamic environment that overlap mainly the uses of environmental protection and tourism activity in a portion of the territory in which legal norms are difficult to apply because they are reflections of interests manifested in three spheres of power - the municipal the state and federal levels. The main objective of this research is the realization of digital image processing to assist territorial management of the Big Island. Focus on the road Abraham - Two Rivers, linking Abraham (landing place for tourists, the main core of the Island) at Two Rivers (site visits by students and researchers, the core that housed the prison currently houses the headquarters of the research center museum and the State University of Rio de Janeiro), both protected by different categories of conservation units. The methodology is based on digital image processing via supervised classification and segmentation by pixel and region. The process occurred from the segmentation (division of a digital image into multiple regions or objects to simplify and / or change the representation of an image) and the image classification process, using pixel classification by classification, and By regions (using the algorithm Bhattacharya). The segmentations and classifications were processed in the computer system SPRING version 5.1.7 and aim to assist in analyzing the usage scenarios and design earth from the identification of the focal points of weakness found along the road Abraham-Two Rivers, prone to occurrences mass movements and to potentiate the effect of forest edge and environmental impacts. The methodology used was based on field analysis and comparisons of technologies for image classification. This road axis connecting the two cores have significant importance in the history of the island, it circulating vehicles, light and heavy, service, pedestrians and tourists. As a result of this the maps were generated by pixel classification, the classification by region maps, map of the intersection with fuzzy supervised classification maps by region and maps with the locations where they are collected in the field verified occurrence of mass movements in ALOS, 2000, IKONOS, 2003 and orthophotos, 2006. These maps seek to serve to support decision-making by local bodies responsible.

Many lakes, coastal zones and oceans are directly or indirectly influenced by human activities. Through the outlet of a vast amount of substances in the air and water, we are changing the natural conditions on local and global levels.

Remote sensing sensors, on satellites or airplanes, can collect image data, providing the user with information about the depicted area, object or phenomenon. Three different applications are discussed in this thesis. In the first part, we have used a bio-optical model to derive information about water quality parameters from remote sensing data collected over Swedish lakes. In the second part, remote sensing data have been used to locate and map wastewater plumes from pulp and paper industries along the east coast of Sweden. Finally, in the third part, we have investigated to what extent satellite data can be used to monitor coral reefs and detect coral bleaching.

Regardless of application, it is important to understand the limitations of this technique. The available sensors are different and limited in terms of their spatial, spectral, radiometric and temporal resolution. We are also limited with respect to the objects we are monitoring, as the concentration of some substances is too low or the objects are too small, to be identified from space. However, this technique gives us a possibility to monitor our environment, in this case the aquatic environment, with a superior spatial coverage. Other advantages with remote sensing are the possibility of getting updated information and that the data is collected and distributed in digital form and therefore can be processed using computers.

Several studies in hydrology have reported differences in outcomes between models in which spatial autocorrelation (SAC) is accounted for and those in which SAC is not. However, the capacity to predict the magnitude of such differences is still ambiguous. In this thesis, I hypothesized that SAC, inherently possessed by a response variable, influences spatial modeling outcomes. I selected ten watersheds in the USA and analyzed them to determine whether water quality variables with higher Moran’s I values undergo greater increases in the coefficient of determination (R²) and greater decreases in residual SAC (rSAC) after spatial modeling. I compared non-spatial ordinary least squares to two spatial regression approaches, namely, spatial lag and error models. The predictors were the principal components of topographic, land cover, and soil group variables. The results revealed that water quality variables with higher inherent SAC showed more substantial increases in R² and decreases in rSAC after performing spatial regressions. In this study, I found a generally linear relationship between the spatial model outcomes (R² and rSAC) and the degree of SAC in each water quality variable. I suggest that the inherent level of SAC in response variables can predict improvements in models before spatial regression is performed. The benefits of this study go beyond modeling selection and performance, it has the potential to uncover hydrologic connectivity patterns that can serve as insights to water quality managers and policy makers.