Готові списки джерел за темами / Monitoring of Land cover/Land use

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Добірка наукової літератури з теми "Monitoring of Land cover/Land use"

Автор: Grafiati

Опубліковано: 7 вересня 2022

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Статті в журналах з теми "Monitoring of Land cover/Land use"

Guliyeva, S. H. "LAND COVER / LAND USE MONITORING FOR AGRICULTURE FEATURES CLASSIFICATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 61–65. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-61-2020.

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Abstract. Remote sensing applications are directed to agricultural observation and monitoring. It has been huge of scientific papers are dedicated to the research of the contribution of remote sensing for agriculture studies. There are several global challenges needed to be considered within agriculture activities. It can be embraced by the main agriculture sector facing the obstacles impacting the production and productivity of the sector. These are the following options that can be pointed out: biomass and yield estimation; vegetation vigor and drought stress monitoring; assessment of crop phenological development; crop acreage estimation and cropland mapping; and mapping of disturbances and Land Use/Land Cover changes. In this study has been undertaken the realization of satellite-based Land Use/Land Cover monitoring based on various optical satellite data. It has been used satellite images taken from satellites AZERSKY, RapidEye, Sentinel-2B and further processed for Land Use/Land Cover classification. Following the complex approach of the supervised and unsupervised classification, the methodology has been used for satellite image processing. As the main satellite imagery for monitoring crop condition were AZERSKY taken during the growing season, from May to June of 2019 year. The study area was some part of the Sheki region, which covers the central part of the southern slope of the Greater Caucasus Mountain Range within Azerbaijan Republic. In this research work satellite imagery processing and mapping has been carried out on the basis of software application of ArcGIS Pro 2.5.

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Cieślak, Iwona, Karol Szuniewicz, Katarzyna Pawlewicz, and Szymon Czyża. "Land Use Changes Monitoring with CORINE Land Cover Data." IOP Conference Series: Materials Science and Engineering 245 (October 2017): 052049. http://dx.doi.org/10.1088/1757-899x/245/5/052049.

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Erickson, Donna L. "Rural land use and land cover change." Land Use Policy 12, no. 3 (July 1995): 223–36. http://dx.doi.org/10.1016/0264-8377(95)00005-x.

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Tol, Richard S. J. "Dynamic World: Land-Cover and Land-Use Change." Environmental Science & Policy 7, no. 1 (February 2004): 77. http://dx.doi.org/10.1016/j.envsci.2003.10.001.

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Bektas Balcik, F., and A. Karakacan Kuzucu. "DETERMINATION OF LAND COVER/LAND USE USING SPOT 7 DATA WITH SUPERVISED CLASSIFICATION METHODS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W1 (October 26, 2016): 143–46. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w1-143-2016.

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Land use/ land cover (LULC) classification is a key research field in remote sensing. With recent developments of high-spatial-resolution sensors, Earth-observation technology offers a viable solution for land use/land cover identification and management in the rural part of the cities. There is a strong need to produce accurate, reliable, and up-to-date land use/land cover maps for sustainable monitoring and management. In this study, SPOT 7 imagery was used to test the potential of the data for land cover/land use mapping. Catalca is selected region located in the north west of the Istanbul in Turkey, which is mostly covered with agricultural fields and forest lands. The potentials of two classification algorithms maximum likelihood, and support vector machine, were tested, and accuracy assessment of the land cover maps was performed through error matrix and Kappa statistics. The results indicated that both of the selected classifiers were highly useful (over 83% accuracy) in the mapping of land use/cover in the study region. The support vector machine classification approach slightly outperformed the maximum likelihood classification in both overall accuracy and Kappa statistics.

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Hansen, Matthew C., Peter V. Potapov, Amy H. Pickens, Alexandra Tyukavina, Andres Hernandez-Serna, Viviana Zalles, Svetlana Turubanova, et al. "Global land use extent and dispersion within natural land cover using Landsat data." Environmental Research Letters 17, no. 3 (March 1, 2022): 034050. http://dx.doi.org/10.1088/1748-9326/ac46ec.

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Abstract The conversion of natural land cover into human-dominated land use systems has significant impacts on the environment. Global mapping and monitoring of human-dominated land use extent via satellites provides an empirical basis for assessing land use pressures. Here, we present a novel 2019 global land cover, land use, and ecozone map derived from Landsat satellite imagery and topographical data using derived image feature spaces and algorithms suited per theme. From the map, we estimate the spatial extent and dispersion of land use disaggregated by climate domain and ecozone, where dispersion is the mean distance of land use to all land within a subregion. We find that percent of area under land use and distance to land use follow a power law that depicts an increasingly random spatial distribution of land use as it extends across lands of comparable development potential. For highly developed climate/ecozones, such as temperate and sub-tropical terra firma vegetation on low slopes, area under land use is contiguous and remnant natural land cover have low areal extent and high fragmentation. The tropics generally have the greatest potential for land use expansion, particularly in South America. An exception is Asian humid tropical terra firma vegetated lowland, which has land use intensities comparable to that of temperate breadbaskets such as the United States’ corn belt. Wetland extent is inversely proportional to land use extent within climate domains, indicating historical wetland loss for temperate, sub-tropical, and dry tropical biomes. Results highlight the need for planning efforts to preserve natural systems and associated ecosystem services. The demonstrated methods will be implemented operationally in quantifying global land change, enabling a monitoring framework for systematic assessments of the appropriation and restoration of natural land cover.

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Y. Jamal, Assist Prof Dr Saleem. "Use of Remote Sensing and Geographic Information System for the Classification of Agricultural Land Uses and Land Cover in the Al-Sad Al-Adhim sub District – Iraq." ALUSTATH JOURNAL FOR HUMAN AND SOCIAL SCIENCES 225, no. 2 (September 1, 2018): 245–73. http://dx.doi.org/10.36473/ujhss.v225i2.151.

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Land use refers to the human activity associated with a particular area of land. The land cover refers to the pattern of appearances located on the surface of the earth. Survey, inventory, monitoring and classification of land use and land cover are a fundamental step in the land use planning process, in evaluating and comparing alternatives and in choosing the best and sustainable use of land for development, accomplishment economic and social well-being. Remote sensing and Geographic Information System provided advantages that conventional methods could not provide for surveys and monitoring of natural and human resources, and classification of agricultural land uses and land cover in the area of the Al-Sad Al-Adhim sub District – Iraq. Depending on the Anderson system and others to classify land uses and land cover, through the integration of digital interpretation with the use of Digital Image Processing (ERDAS IMAGINE) software, and visual interpretation using ArcGIS software. Classification of agricultural land use and land cover up to the third level, with over all accuracy of the map 90%. the percentage distribution of the areas shows that the agricultural lands ranked first and occupy 52%, then grassland occupies 19%, barren land is occupied 17%, urban areas and built up occupy 9% water is ranked last occupy 3% of the total area of the study area.

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Dero, Kambo, Wakshum Shiferaw, and Biruk Zewde. "Urban induced land use land cover changes in upper Deme watershed, Southwest Ethiopia." Journal of Degraded and Mining Lands Management 9, no. 1 (October 1, 2021): 3045–53. http://dx.doi.org/10.15243/jdmlm.2021.091.3045.

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The study was aimed to assess urban induced land use land cover changes in the upper Deme watershed. Three satellite images of 1986, 2002, and 2019 were analyzed by ArcGIS and processed by supervised classification. Land use land cover change in the watershed increased for settlement, bare land, and croplands in the period 1986-2019 by 56.6%, 53%, and 0.25%, respectively. However, the land use land cover change in the watershed decreased for a water body, forest, and grassland by 65%, 57.7%, and 7%, respectively. These enforced to change the work habit and social bases. Out of converted lands, during 1986-2002, 34.9%, 53%, 18%, 40.9%, and 10.6% of bare land, cropland, forest land, grassland, and water bodies, respectively, in the upper Deme watershed were changed into settlement areas. During 2002-2019, 30.7%, 36.8%, 26.9%, 66%, and 33.3% of bare land, cropland, forest land, grassland, and water bodies, respectively, were changed into settlement areas. This shows urbanization results in a different change in economic, social, land use land cover, and watershed management activities in the upper Deme watershed.

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Mahmood, Rezaul, Roger A. Pielke, and Clive A. McAlpine. "Climate-Relevant Land Use and Land Cover Change Policies." Bulletin of the American Meteorological Society 97, no. 2 (February 1, 2016): 195–202. http://dx.doi.org/10.1175/bams-d-14-00221.1.

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Abstract Both observational and modeling studies clearly demonstrate that land-use and land-cover change (LULCC) play an important biogeophysical and biogeochemical role in the climate system from the landscape to regional and even continental scales. Without comprehensively considering these impacts, an adequate response to the threats posed by human intervention into the climate system will not be adequate. Public policy plays an important role in shaping local- to national-scale land-use practices. An array of national policies has been developed to influence the nature and spatial extent of LULCC. Observational evidence suggests that these policies, in addition to international trade treaties and protocols, have direct effects on LULCC and thus the climate system. However, these policies, agreements, and protocols fail to adequately recognize these impacts. To make these more effective and thus to minimize climatic impacts, we propose several recommendations: 1) translating international treaties and protocols into national policies and actions to ensure positive climate outcomes; 2) updating international protocols to reflect advancement in climate–LULCC science; 3) continuing to invest in the measurements, databases, reporting, and verification activities associated with LULCC and LULCC-relevant climate monitoring; and 4) reshaping Reducing Emissions from Deforestation and Forest Degradation+ (REDD+) to fully account for the multiscale biogeophysical and biogeochemical impacts of LULCC on the climate system.

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Treitz, Paul. "Remote sensing for mapping and monitoring land-cover and land-use change." Progress in Planning 61, no. 4 (May 2004): 267. http://dx.doi.org/10.1016/s0305-9006(03)00062-x.

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Дисертації з теми "Monitoring of Land cover/Land use"

Maus, Victor Wegner. "Land use and land cover monitoring using remote sensing image time series." Instituto Nacional de Pesquisas Espaciais (INPE), 2016. http://urlib.net/sid.inpe.br/mtc-m21b/2016/06.01.14.07.

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Land system change has a wide range of impacts on Earth system components. Tropical forests in particular have been identified as crucial ecosystems for climate regulation, global biodiversity, and hydrological cycling. The Brazilian Amazon has experienced a high rate of deforestation in the last decade and it is the main source of Brazils anthropogenic CO$_{2}$ emissions. The growing global population will further increase the demand for food and therefore increase the pressure on agricultural systems. High quality, fine resolution, and near-real time land use and land cover monitoring systems play a crucial role in generating information to advance our understanding of human impact on land cover. Earth Observation satellites are the only source that provides a continuous and consistent set of information about the Earth${'}$s land. The current large-scale classification systems such as MODIS Land Cover and GLC 2000 have limitations and their accuracy is not sufficient for land change modeling. Therefore, new techniques for improving land system products are urgently needed. The contribution of this thesis to Earth System Science is threefold. Firstly, the thesis presents a new method for analysis of remote-sensed image time series that improves spatio-temporal land cover data sets and has a substantial potential for contributing to land system change modeling. The developed Time- Weighted Dynamic Time Warping (TWDTW) method is a time-constraint variation of the well-known Dynamic Time Warping (DTW) method, which has in the extensive literature proved to be a robust time series data mining. Secondly, this thesis contributed to open and reproducible science by making the algorithms available for larger audience. TWDTW is implemented in an open source R package called dtwSat available in the Comprehensive R Archive Network (CRAN). Thirdly, this thesis presents an analysis of land cover changes in the Amazon, focusing on the Brazilian state of Mato Grosso that has gone through high rate of deforestation and cropland expansion in the last decade. This study identified and estimated the land cover change using MODIS image time series, contributing to better understand the land dynamics in the Brazilian Amazon. In the study area the pasture is the dominant land use after deforestation, whereas most of the single cropping area comes from pasture, and the cropping system is undergoing intensification from single to double cropping. Moreover, the regenerative secondary forest comes mainly from pasture. The study showed the potential of the TWDTW method for large-scale remote sensing data analysis, which could be extended to other Brazilian biomes to help understand land change in the whole Brazilian territory.
Mudanças na superfície da terra têm uma ampla gama de impactos sobre o sistema terrestre. Florestas tropicais, em particular, são ecossistemas cruciais para regulação climática, manutenção da biodiversidade, a ciclo hidrológico. Na última década a Amazônia brasileira tem experimentado uma alta taxa de desmatamento, sendo a principal fonte de emissões antropogênicas de CO$_{2}$ no Brasil. O crescimento da população mundial vai aumentar ainda mais a demanda por alimentos e, portanto, aumentar a pressão sobre agrícultura e pecuária. Dados com alta qualidade, melhor resolução espacial e temporal, e o desenvolvimento de sistemas de monitoramento desempenham um papel crucial na geração de informações para avançar nossa compreensão sobre os impactos humanos na cobertura da terra. Os satélites de observação da Terra são a única fonte que fornece um conjunto contínuo e consistente de informações sobre nosso planeta. Sistemas de classificação em grande escala, como MODIS Land Cover e GLC 2000 têm limitações e sua acurácia não é suficiente para a modelagem de mudanças de use da terra. Portanto, são necessárias novas técnicas para melhoramento dos dados de use e cobertura da terra. Esta tese traz três contribuições para a Ciência do Sistema Terrestre. Primeiramente, esta tese apresenta um novo método para análise de séries temporais de imagens satélite que melhora a classificação de cobertura da terra. O método tem grande potencial para contribuir para a modelagem de mudanças do sistema terrestre. O método desenvolvido, Time-Weigted Dynamic Time Warping (TWDTW), é uma adaptação ponderada por tempo do método clássico Dynamic Time Warping (DTW), que tem em uma extensa literatura provando ser um método robusto para mineração de dados em séries temporais. Em segundo lugar, esta tese contribuiu para a ciência aberta e reprodutível, tornando algoritmos disponíveis para o público. TWDTW está implementado em um pacote R de código aberto chamado dtwSat disponível no Comprehensive R Archive Network (CRAN). Em terceiro lugar, esta tese apresenta uma análise as mudanças do uso e cobertura da terra na Amazônia, com foco no estado do Mato Grosso, que passou por alta taxa de desmatamento e expansão agrícola na última década. Este estudo identificou e estimou mudanças de cobertura da terra com séries temporais de imagens MODIS, contribuindo para melhor compreender a dinâmica de ocupação da terra na Amazônia brasileira. Na área de estudo, a pastagem é o uso dominante após o desmatamento, ao passo que a maior parte da área de cultivo com um ciclo anual provem da área de pasto, com o sistema de cultivo passando por intensificação, mudando de cultivo simples para cultivo duplo. Além disso, áreas de regeneração vêm, principalmente, de áreas de pastagem. O estudo mostrou o potencial do método de TWDTW para análise de dados de sensoriamento remoto em grande escala, que poderia ser estendido a outros biomas brasileiros para ajudar a entender as mudanças da terra em todo o território brasileiro.

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Ek, Edgar. "Monitoring Land Use and Land Cover Changes in Belize, 1993-2003: A Digital Change Detection Approach." Ohio University / OhioLINK, 2004. http://www.ohiolink.edu/etd/view.cgi?ohiou1102520727.

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Qi, Zhixin, and 齐志新. "Short-interval monitoring of land use and land cover change using RADARSAT-2 polarimetric SAR images." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hdl.handle.net/10722/194623.

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Land use and land cover (LULC) change information is essential in urban planning and management. With the rapid urbanization in China, many illegal land developments have emerged in some rapidly developing regions and have caused irreversible environmental problems, posing a threat to sustainable urban development. Short-interval monitoring of LULC change therefore is necessary in these regions to control and prevent illegal land developments at an early stage. Conventional optical remote sensing is limited by weather conditions and has difficulties collecting timely data in tropical regions characterized by frequent cloud cover. Radar remote sensing, not affected by clouds, is therefore a potential tool for collecting timely LULC information in these regions. Polarimetric SAR (PolSAR) is more suitable than single-polarization SAR for monitoring LULC change because it can discriminate different types of scattering mechanisms. The overall objective of this study is to conduct short-interval monitoring of LULC change using RADARSAT-2 PolSAR images. Classification methods that achieve high accuracy for PolSAR images are essential in monitoring LULC change. In this study, a new method, based on the integration of polarimetric decomposition, PolSAR interferometry, object-oriented image analysis, and decision tree algorithms, is proposed for LULC classification using RADARSAT-2 PolSAR data. A comparison between the proposed classification method and Wishart supervised classification which is commonly used for the classification of PolSAR data showed that the proposed method can significantly improve LULC classification accuracy. Polarimetric decomposition, PolSAR interferometry, object-oriented image analysis, and decision tree algorithms have been determined to contribute to the improvement achieved by the proposed classification method. Selection of appropriate incidence angle is important in LULC classification using PolSAR images because incidence angle influences the intensity and patterns of radar return. Based on the proposed classification method, the present study further investigates the influence of incidence angle on LULC classification using RADARSAT-2 PolSAR images. LULC classifications using incidence angles of 31.50 and 37.56° were conducted separately. The influence of incidence angle on the classification was investigated by comparing the results of the two independent classifications. The comparison showed that large incidence angle performs much better than small incidence angle in the classification of different vegetation types, whereas small incidence angle outperforms large incidence angle in reducing the confusion between urban/built-up areas and vegetation, that between vegetable and barren land, and that among barren land, water, and lawn. Considering that the detection of urban/built-up areas and barren land is important in monitoring illegal land developments, small incidence angle is more suitable than large incidence angle in monitoring illegal land developments. Change detection methods that achieve high accuracy for PolSAR data are also essential in monitoring LULC change. The current study proposes a new method for LULC change detection using RADARSAT-2 PolSAR images. The proposed change detection method combines change vector analysis (CVA) and post-classification comparison (PCC) to detect LULC changes using object-oriented image analysis. The classification of PolSAR images is based on the proposed classification method. Compared with the PCC based on Wishart supervised classification, the proposed change detection method can achieve much higher accuracy for LULC change detection. Further investigation indicated that CVA, PCC, and object-oriented image analysis all contribute to the higher accuracy achieved by the proposed change detection method. Short-interval monitoring of LULC change was carried out using a time series of RADARSAT-2 PolSAR images. The monitoring was based on monthly LULC change detection using the proposed change detection method and appropriate incidence angle. The influence of environmental factors on short-interval monitoring of LULC change was investigated by analyzing the monthly change detection results. Paddy harvesting and planting, seasonal crop growth, and change in soil moisture and surface roughness were found to exert significant influence on the short-interval monitoring of LULC change. High accuracy can be achieved for short-interval monitoring of construction sites and bulldozed land using RADARSAT-2 PolSAR images. However, paddy harvesting and growth still cause false alarms on the monitoring of these two LULC classes. The study indicated that conducting short-interval monitoring of LULC change using RADARSAT-2 PolSAR images is effective. High accuracy can be achieved for short-interval monitoring of construction sites and bulldozed land using the proposed change detection and classification methods, which can provide important information for the control and prevention of illegal land developments at an early stage.
published_or_final_version
Urban Planning and Design
Doctoral
Doctor of Philosophy

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Liu, Qingling, and Fanting Gong. "Monitoring land use and land cover change: a combining approach of change detection to analyze urbanization in Shijiazhuang, China." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-13715.

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Detecting the changes of land use and land cover of the earth’s surface is extremely important to achieve continual and precise information about study area for any kinds of planning of the development. Geographic information system and remote sensing technologies have shown their great capabilities to solve the study issues like land use and land cover changes. The aim of this thesis is to produce maps of land use and land cover of Shijiazhuang on year 1993, 2000 and 2009 to monitor the possible changes that may occur particularly in agricultural land and urban or built-up land, and detect the process of urbanization in this city. Three multi-temporal satellite image data, Thematic Mapper image data from year 1993, Enhanced Thematic Mapper image data from 2000 and China Brazil Earth Resource Satellite image data from 2009 were used in this thesis. In this study, supervised classification was the major classification approach to provide classified maps, and five land use and land cover categories were identified and mapped. Post-classification approach was used to improve the qualities of the classified map. The noises in the classified maps will be removed after post-classification process. Normalized difference vegetation index was used to detect the changes of vegetated land and non-vegetated land. Change detection function in Erdas Imagine was used to detect the urban growth and the intensity of changes surrounding the urban areas. Cellular automata Markov was used to simulate the trends of land use and cover change during the period of 1993 to 2000 and 2000 to 2009, and a future land use map was simulated based on the land use maps of year 2000 and 2009. From this performance, the cross-tabulation matrices between different periods were produced to analyze the trends of land use and cover changes, and these statistic data directly expressed the change of land use and land cover. The results show that the agricultural land and urban or built-up land were changed a lot, approximately half of agricultural land was converted into urban or built-up land. This indicates that the loss of agricultural land is associated with the growth of urban or built-up land. Thus, the urbanization took place in Shijiazhuang, and the results of this urban expansion lead to the loss of agricultural land and environmental problems. During the process of detecting the land use and cover change, obtaining of high-precision classified maps was the main problem.

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Almutairi, Abdullah. "Monitoring land-cover change detection in an arid urban environment a comparison of change detection techniques /." Morgantown, W. Va. : [West Virginia University Libraries], 2000. http://etd.wvu.edu/templates/showETD.cfm?recnum=1410.

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Thesis (M.A.)--West Virginia University, 2000.
Title from document title page. Document formatted into pages; contains xi, 77 p. : ill. (some col.), maps (some col.) Includes abstract. Includes bibliographical references (p. 74-77).

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Hunt, John W. "Monitoring and resource management : streams, land cover, and the use of water quality information in public policy /." Diss., Digital Dissertations Database. Restricted to UC campuses, 2009. http://uclibs.org/PID/11984.

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James, Tosin. "Changes in Land Use Land Cover (LULC), Surface Water Quality and Modelling Surface Discharge in Beaver Creek Watershed, Northeast Tennessee and Southwest Virginia." Digital Commons @ East Tennessee State University, 2020. https://dc.etsu.edu/etd/3747.

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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.

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Mlotha, McArd Joseph. "Analysis of Land Use/Land Cover Change Impacts Upon Ecosystem Services in Montane Tropical Forest of Rwanda: Forest Carbon Assessment and REDD+ Preparedness." Antioch University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=antioch1527773591460797.

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Villarreal, Miguel Luis. "Land Use and Disturbance Interactions in Dynamic Arid Systems: Multiscale Remote Sensing Approaches for Monitoring and Analyzing Riparian Vegetation Change." Diss., The University of Arizona, 2009. http://hdl.handle.net/10150/195061.

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Riparian systems are comprised of interacting aquatic and terrestrial elements that contribute distinctively to the natural capital of arid landscapes. Riparian vegetation is a major component of riparian systems, providing the ecosystem services required to support watershed health. The spatial and temporal distributions of riparian vegetation are influenced by hydrologic and disturbance processes operating at scales from local to regional. I believe both these processes are well suited to monitoring using synoptic and multitemporal approaches.The research in this dissertation is presented as 3 related studies. The first study focused on historical riparian dynamics related to natural disturbance and land use. Using current and historical riparian vegetation maps, we examined vegetation change within catchments of varying land use intensity. Results suggest that land use activities and wastewater subsidy affect the rate of development and diversity of riparian community typesThe second study used moderate resolution satellite imagery to monitor changes in riparian structure and pattern within a land cover change framework. We classified Landsat Thematic Mapper satellite imagery of the Upper Santa Cruz River watershed using Classification and Regression Tree (CART) models. We tested the ability of our models to capture change at landscape, floodplain, and catchment scales, centering our change detection efforts on a riparian tree die-off episode and found they can be used to describe both general landscape dynamics and disturbance-related riparian change.The third study examined historical and environmental factors contributing to spatial patterns of vegetation following two riparian tree die-offs. We used high resolution aerial imagery to map locations of individual live and dead trees and collected a suite of environmental variables and historical variables related directly and indirectly to land use and disturbance history. We tested for differences between groups of live and dead trees using Multi-response Permutation Procedures and found strong relationships between historical factors and mortality incidence.The results from these studies demonstrate the importance of examining historical information and spatial linkages across scales when monitoring riparian vegetation. From a land management perspective, the results identify the need for landscape-level, ecosystem-based management programs to maintain functioning and spatially connected riparian systems.

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Leeper, Ronnie. "Near-surface Atmospheric Response to Simulated Changes in Land-cover Vegetation Fraction, and Soil Moisture over Western Kentucky." TopSCHOLAR®, 2009. http://digitalcommons.wku.edu/theses/108.

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A series of land-use-land-cover-change (LULCC) based sensitivity experiments, including changes in vegetation type, fractional vegetation (FV), and soil moisture (SM), over Western Kentucky were conducted to investigate atmospheric response to land-use. The choice of land-use for this study was chosen in the context of Western Kentucky’s historical LULCC. For this study, vegetation types considered were grassland, forest, and bare soil with further variations in FV for grassland and forest at 25, 50, 75, and 100 % and systematic increases and decreases in volumetric SM of 0.05, 0.10, and 0.15 m3 m-3. To the author’s knowledge, this is the first assessment of its kind that incorporates these types of LULCC in a single study. In addition, typical anthropogenic land-use change often incorporates several types of LULCC. Moreover, this assessment provides a robust analysis of the impacts LULCC has on atmospheric processes over Western Kentucky. To simulate the importance of land-use on atmospheric processes, a well known meso-scale model developed by the National Center for Atmospheric Research (NCAR) and the Pennsylvania State University (PSU) MM5 coupled with an intermediately complex land surface model (LSM) Noah was used. The purpose of this research is to investigate the impact of multiple types of LULCC on planetary boundary layer (PBL) evolution, PBL stability, near surface 3D-wind fields, temperature, and moisture. Furthermore, it is anticipated that multiple types of LULCC will provide more insight into the complex nonlinear land-atmosphere interactions from atmospheric, air quality, and climatology perspectives. Modeling analysis revealed the importance of land-use on atmospheric processes. Changes in all three types of LULCC (land-cover, FV, and SM) altered the distribution of surface energy and moisture, PBL structure, 3D-wind fields, and PBL stability. In general, it was found that LULCC that enhanced (diminished) ET rates reduced (increased) sensible heat flux, atmospheric temperature and, and PBL heights below (above) control (CTRL). For instance, the conversion of land-cover from CTRL to grassland reduced 2 m temperature and PBL heights by 0.60 °C and 228 m respectively compared to CTRL due to an evaporative advantage (lower stomata resistance). Multiple types of land-use change were found to either offset or enhance overall modeled response to LULCC. A reduction in FV to 25 % over grassland diminished ET despite the evaporation advantage of grassland and increased 2 m temperature and PBL heights with respect to CTRL by 3.3 °C and 504 m. These results significantly altered horizontal and vertical wind fields, affecting moisture advection and the development of meso-scale circulations. Compared to CTRL, these differences were enhanced over drier soils, but muted over moist soils. Moreover, the impact of LULCC on atmosphere evolution was not only dependent on the type of LULCC, but also on the current state of other unaltered land surface features such as vegetation type, FV, and SM. Alterations to modeled PBL development, as a result of LULCC, can have important impacts on a region’s climatology and air quality. Simulated changes in typical PBL moisture and temperature through time can affect local and regional climatology. Depending on the type of LULCC, these alterations in climate may lead to localized cooling. In addition, it was further hypothesized that changes in PBL height can affect air quality. Given the capping inversion layer at the top of the PBL, changes in PBL heights can significantly affect air quality with lower (higher) PBL heights diminishing (enhancing) air quality. Moreover, this research prescribes the importance of considering LULCC in atmospheric assessments of climatology and air quality, including pollutant dispersion and trajectory modeling.

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Книги з теми "Monitoring of Land cover/Land use"

Mackey, E. C. Land cover change: Scotland from the 1940s to the 1980s. Edinburgh: Stationery Office, 1998.

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Sluiter, Raymond. Mediterranean land cover change: Modelling and monitoring natural vegetation using GIS and remote sensing. Utrecht: Koninklijk Nederlands Aardrijkskundig Genootschap ; International Geographical Union Section The Netherlands, 2005.

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Muzein, Bedru Sherefa. Remote sensing & GIS for land cover/land use change detection and analysis in the semi-natural ecosystems and agriculture landscapes of the Central Ethiopian Rift Valley. Berlin: Rhombos-Verlag, 2010.

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Mölders, Nicole. Land-Use and Land-Cover Changes. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-1527-1.

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Lambin, Eric F., and Helmut Geist, eds. Land-Use and Land-Cover Change. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-32202-7.

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Dynamic world: Land-cover and land-use change. London: Arnold, 2002.

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Manakos, Ioannis, and Matthias Braun, eds. Land Use and Land Cover Mapping in Europe. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-7969-3.

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Walsh, Stephen J., Diego Riveros-Iregui, Javier Arce-Nazario, and Philip H. Page, eds. Land Cover and Land Use Change on Islands. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43973-6.

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National Conference on Land Use, Land Cover and Management Practices (2003 Hyderabad, India). Land use, land cover and management practices in India. Edited by Gautam Naresh Chandra 1941- and Raghavswamy V. Hyderabad, India: BS Publications, 2004.

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Al-Fares, Wafi. Historical Land Use/Land Cover Classification Using Remote Sensing. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00624-6.

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Частини книг з теми "Monitoring of Land cover/Land use"

Probeck, Markus, Gernot Ramminger, David Herrmann, Sharon Gomez, and Thomas Häusler. "European Forest Monitoring Approaches." In Land Use and Land Cover Mapping in Europe, 89–114. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-7969-3_7.

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Loveland, Thomas R., and Ruth S. DeFries. "Observing and monitoring land use and land cover change." In Ecosystems and Land Use Change, 231–46. Washington, D. C.: American Geophysical Union, 2004. http://dx.doi.org/10.1029/153gm18.

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Guàrdia, Núria Blanes, Tim Green, and Alejandro Simón. "The Users’ Role in the European Land Monitoring Context." In Land Use and Land Cover Mapping in Europe, 31–41. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-7969-3_3.

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Kuntz, Steffen, Elisabeth Schmeer, Markus Jochum, and Geoffrey Smith. "Towards an European Land Cover Monitoring Service and High-Resolution Layers." In Land Use and Land Cover Mapping in Europe, 43–52. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-7969-3_4.

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Roy, Santanu, Gouri Sankar Bhunia, and Abhisek Chakrabarty. "Land Use/Land Cover Characteristics of Odisha Coastal Zone." In Mapping, Monitoring, and Modeling Land and Water Resources, 49–70. First edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9781003181293-5.

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Kumar, Mundlamuri Satish, Venkatesh Kolluru, S. B. Gowthami, N. A. Anjita, N. Nayana, Linda Regi, and G. S. Dwarakish. "Monitoring Land Use and Land Cover Changes in Coastal Karnataka." In Lecture Notes in Civil Engineering, 785–95. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6828-2_57.

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Parece, Tammy E., and James B. Campbell. "Land Use/Land Cover Monitoring and Geospatial Technologies: An Overview." In The Handbook of Environmental Chemistry, 1–32. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14212-8_1.

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Haubold, Herbert, and Jan Feranec. "Chapter 1 Overview of Land Cover and Land Use Monitoring Programs." In European Landscape Dynamics, 1–8. 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742: CRC Press, 2016. http://dx.doi.org/10.1201/9781315372860-2.

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Corner, Robert J., Ashraf M. Dewan, and Salit Chakma. "Monitoring and Prediction of Land-Use and Land-Cover (LULC) Change." In Dhaka Megacity, 75–97. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6735-5_5.

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García-Álvarez, David, Francisco José Jurado Pérez, and Javier Lara Hinojosa. "Supra-National Thematic Land Use Cover Datasets." In Land Use Cover Datasets and Validation Tools, 443–62. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90998-7_22.

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AbstractSupra-national thematic Land Use Cover (LUC) datasets are not very common. While there are several general datasets mapping all the land uses or covers in different supra-national areas across the world, LUC datasets with a similar extent that focus on the mapping of specific land covers in greater thematic detail are scarce. In this chapter, we review six different supra-national thematic LUC datasets. Three others were also found in the literature, but are not fully available for download, namely the TREES Vegetation Map of Tropical South America, the Central Africa—Vegetation map and FACET. The Circumpolar Arctic Region Vegetation dataset was also excluded from this review because of its specificity and coarse scale (1:7,500,000). Europe is the continent with the most relevant, most updated and most detailed LUC thematic datasets at supra-national scales. This is due to the work being done by the European Commission through its Joint Research Centre (JRC) and the Copernicus Land Monitoring Programme. The High-Resolution Layers (HRL) provide very detailed information, both thematically and spatially (from 10 m), for five different themes: imperviousness, tree cover, grasslands, water and wet covers, and small woody features. The European Settlement Map also provides information on built-up areas at very detailed scales (from 2.5 m). HRL and ESM are recently launched datasets which, therefore, do not provide a long series of historical data. In addition, ESM is an experimental dataset produced within the framework of a research project funded by the European Commission and no updates are expected. The datasets reviewed in this chapter for other parts of the world focus on vegetation covers of tropical forests and other relevant areas in terms of biodiversity and environmental studies. These datasets were produced within projects funded by the European Commission and the United States Agency for International Development. Unlike the previous datasets for Europe, they are already outdated and are usually produced at coarser spatial resolutions: Insular Southeast Asia—Forest Cover Map (1 km, 1998/00); Continental Southeast Asia—Forest Cover Map (1 km, 1998/02). For its part, the Congo Basin Monitoring dataset, although outdated, provides information at a higher resolution (57 m) for two different dates: 1990, 2000. The Joint Research Centre of the European Commission also produced an African cropland mask as a source of information for policy-makers. Of all the datasets reviewed in this chapter, it is the only one to focus on agricultural covers. It was obtained from data fusion at 250 m. Consequently, it does not show the cropland areas of Africa for a specific date across the whole continent.

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Тези доповідей конференцій з теми "Monitoring of Land cover/Land use"

Orlovsky, L., S. Kaplan, N. Orlovsky, D. Blumberg, and E. Mamedov. "Monitoring land use and land cover changes in Turkmenistan using remote sensing." In RAVAGE OF THE PLANET 2006. Southampton, UK: WIT Press, 2006. http://dx.doi.org/10.2495/rav060461.

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Zewdie, Worku, and E. Csaplovics. "Monitoring land use/land cover dynamics in northwestern Ethiopia using support vector machine." In SPIE Remote Sensing, edited by Ulrich Michel and Karsten Schulz. SPIE, 2014. http://dx.doi.org/10.1117/12.2066461.

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Oad, Vipin Kumar, Muhammad Raza Ul Mustafa, Husna Binti Takaijudin, Ghulam Nabi, and Mubasher Hussain. "Monitoring Trends of Land Use and Land Cover Changes in Rajang River Basin." In 2020 Second International Sustainability and Resilience Conference: Technology and Innovation in Building Designs. IEEE, 2020. http://dx.doi.org/10.1109/ieeeconf51154.2020.9319939.

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Kussul, Nataliia, Andrii Shelestov, Mykola Lavreniuk, Andrii Kolotii, and Vladimir Vasiliev. "Land Cover and Land Use Monitoring Based on Satellite Data within World Bank Project." In 2019 10th International Conference on Dependable Systems, Services and Technologies (DESSERT). IEEE, 2019. http://dx.doi.org/10.1109/dessert.2019.8770040.

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Yumin Tan, Bingxin Bai, and Masum Syed Mohammad. "Time series remote sensing based dynamic monitoring of land use and land cover change." In 2016 4th International Workshop on Earth Observation and Remote Sensing Applications (EORSA). IEEE, 2016. http://dx.doi.org/10.1109/eorsa.2016.7552797.

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Hu, Guangyin, Zhibao Dong, Zhenhai Wei, and Junfeng Lu. "Land use and land cover change monitoring in the Zoige Wetland by remote sensing." In The Sixth International Symposium on Digital Earth, edited by Huadong Guo and Changlin Wang. SPIE, 2009. http://dx.doi.org/10.1117/12.873234.

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Sathya, N., S. Kalaiselvi, V. Gomathi, and K. G. Srinivasagan. "Unsupervised monitoring of urban land use and land cover change detection in multitemporal images." In 2014 International Conference on Electronics and Communication Systems (ICECS). IEEE, 2014. http://dx.doi.org/10.1109/ecs.2014.6892722.

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Zheng, Zezhong, Shijie Yu, Yong He, Wenqiang Guo, Wunian Yang, Hongsheng Zhang, and Jiang Li. "Monitoring of land use/land cover change of Ruoergai Nature Reserve in Sichuan province, China." In International Conference on Intelligent Earth Observing and Applications, edited by Guoqing Zhou and Chuanli Kang. SPIE, 2015. http://dx.doi.org/10.1117/12.2207619.

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Stephenne, Nathalie R. "Interactivity with the urban information users in the land-use/land-cover information extraction from VHR data." In Remote Sensing for Environmental Monitoring, GIS Applications, and Geology III. SPIE, 2004. http://dx.doi.org/10.1117/12.510986.

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Yu, Shijie, Zezhong Zheng, Wunian Yang, Mingcang Zhu, Yong He, Zhenlu Yu, Shengli Wang, Fu Wang, and Jiang Li. "The monitoring of land use and land cover change of Sichuan province and Chengdu district, China." In IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016. http://dx.doi.org/10.1109/igarss.2016.7730170.

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Звіти організацій з теми "Monitoring of Land cover/Land use"

Douglas, Thomas, M. Jorgenson, Hélène Genet, Bruce Marcot, and Patricia Nelsen. Interior Alaska DoD training land wildlife habitat vulnerability to permafrost thaw, an altered fire regime, and hydrologic changes. Engineer Research and Development Center (U.S.), February 2022. http://dx.doi.org/10.21079/11681/43146.

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Climate change and intensification of disturbance regimes are increasing the vulnerability of interior Alaska Department of Defense (DoD) training ranges to widespread land cover and hydrologic changes. This is expected to have profound impacts on wildlife habitats, conservation objectives, permitting requirements, and military training activities. The objective of this three-year research effort was to provide United States Army Alaska Garrison Fort Wainwright, Alaska (USAG-FWA) training land managers a scientific-based geospatial framework to assess wildlife habitat distribution and trajectories of change and to identify vulnerable wildlife species whose habitats and resources are likely to decline in response to permafrost degradation, changing wildfire regimes, and hydrologic reorganization projected to 2100. We linked field measurements, data synthesis, repeat imagery analyses, remote sensing measurements, and model simulations focused on land cover dynamics and wildlife habitat characteristics to identify suites of wildlife species most vulnerable to climate change. From this, we created a robust database linking vegetation, soil, and environmental characteristics across interior Alaska training ranges. The framework used is designed to support decision making for conservation management and habitat monitoring, land use, infrastructure development, and adaptive management across the interior Alaska DoD cantonment and training land domain.

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Wang, S. Land use/cover. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2016. http://dx.doi.org/10.4095/298873.

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Cooper, Christopher, Jacob McDonald, and Eric Starkey. Wadeable stream habitat monitoring at Congaree National Park: 2018 baseline report. National Park Service, June 2021. http://dx.doi.org/10.36967/nrr-2286621.

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The Southeast Coast Network (SECN) Wadeable Stream Habitat Monitoring Protocol collects data to give park resource managers insight into the status of and trends in stream and near-channel habitat conditions (McDonald et al. 2018a). Wadeable stream monitoring is currently implemented at the five SECN inland parks with wadeable streams. These parks include Horseshoe Bend National Military Park (HOBE), Kennesaw Mountain National Battlefield Park (KEMO), Ocmulgee Mounds National Historical Park (OCMU), Chattahoochee River National Recreation Area (CHAT), and Congaree National Park (CONG). Streams at Congaree National Park chosen for monitoring were specifically targeted for management interest (e.g., upstream development and land use change, visitor use of streams as canoe trails, and potential social walking trail erosion) or to provide a context for similar-sized stream(s) within the park or network (McDonald and Starkey 2018a). The objectives of the SECN wadeable stream habitat monitoring protocol are to: Determine status of upstream watershed characteristics (basin morphology) and trends in land cover that may affect stream habitat, Determine the status of and trends in benthic and near-channel habitat in selected wadeable stream reaches (e.g., bed sediment, geomorphic channel units, and large woody debris), Determine the status of and trends in cross-sectional morphology, longitudinal gradient, and sinuosity of selected wadeable stream reaches. Between June 11 and 14, 2018, data were collected at Congaree National Park to characterize the in-stream and near-channel habitat within stream reaches on Cedar Creek (CONG001, CONG002, and CONG003) and McKenzie Creek (CONG004). These data, along with the analysis of remotely sensed geographic information system (GIS) data, are presented in this report to describe and compare the watershed-, reach-, and transect-scale characteristics of these four stream reaches to each other and to selected similar-sized stream reaches at Ocmulgee Mounds National Historical Park, Kennesaw Mountain National Battlefield Park, and Chattahoochee National Recreation Area. Surveyed stream reaches at Congaree NP were compared to those previously surveyed in other parks in order to provide regional context and aid in interpretation of results. edar Creek’s watershed (CONG001, CONG002, and CONG003) drains nearly 200 square kilometers (77.22 square miles [mi2]) of the Congaree River Valley Terrace complex and upper Coastal Plain to the north of the park (Shelley 2007a, 2007b). Cedar Creek’s watershed has low slope and is covered mainly by forests and grasslands. Cedar Creek is designated an “Outstanding Resource Water” by the state of South Carolina (S.C. Code Regs. 61–68 [2014] and S.C. Code Regs. 61–69 [2012]) from the boundary of the park downstream to Wise Lake. Cedar Creek ‘upstream’ (CONG001) is located just downstream (south) of the park’s Bannister Bridge canoe landing, which is located off Old Bluff Road and south of the confluence with Meyers Creek. Cedar Creek ‘middle’ and Cedar Creek ‘downstream’ (CONG002 and CONG003, respectively) are located downstream of Cedar Creek ‘upstream’ where Cedar Creek flows into the relatively flat backswamp of the Congaree River flood plain. Based on the geomorphic and land cover characteristics of the watershed, monitored reaches on Cedar Creek are likely to flood often and drain slowly. Flooding is more likely at Cedar Creek ‘middle’ and Cedar Creek ‘downstream’ than at Cedar Creek ‘upstream.’ This is due to the higher (relative to CONG001) connectivity between the channels of the lower reaches and their out-of-channel areas. Based on bed sediment characteristics, the heterogeneity of geomorphic channel units (GCUs) within each reach, and the abundance of large woody debris (LWD), in-stream habitat within each of the surveyed reaches on Cedar Creek (CONG001–003) was classified as ‘fair to good.’ Although, there is extensive evidence of animal activity...

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Czaplewski, Raymond L., Glenn P. Catts, and Paul W. Snook. National land cover monitoring using large, permanent photo plots. Washington, DC: U.S. Department of Agriculture, Forest Service, Washington Office, 1987. http://dx.doi.org/10.2737/wo-gtr-39.

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Brown, Daniel, Alison Delgado, Richard Moss, and Fernando Sedano. Need and Options for Subnational Scale Land-Use and Land-Cover Scenarios for the United States. U.S. Global Change Research Program, 2015. http://dx.doi.org/10.7930/j0nc5z40.

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Hurtt, George. Quantification of Land-Use/Land Cover Change as Driver of Earth System Dynamics. Final Technical Report. Office of Scientific and Technical Information (OSTI), May 2019. http://dx.doi.org/10.2172/1523270.

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Maguranyanga, Caleb, Keen Marozva, Ian Scoones, and Toendepi Shonhe. The Political Economy of Land Use and Land Cover Change in Mvurwi Area Zimbabwe, 1984–2018. APRA, Future Agricultures Consortium, February 2021. http://dx.doi.org/10.19088/apra.2021.001.

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An analysis of the variations in land use and land cover over the past four decades in the Mvurwi area, Mazowe district, Zimbabwe illustrates how socio-economic dynamics and natural factors combine to shape environmental change. Land use and cover changes (LULCC) were assessed using a combination of quantitative analysis (satellite imagery) of land cover and a grounded analysis of the social, economic and political factors. Explanations for the changes observed in this study highlight social, economic and political drivers that have changed over time. A simple, linear explanation of land use and land cover change is inappropriate as multiple drivers intersect, and environmental change must always be understood as co-constituted with social dynamics and political economy.

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Short, Mary, та Sherry Leis. Vegetation monitoring in the Manley Woods unit at Wilson’s Creek National Battleﬁeld: 1998–2020. Редактор Tani Hubbard. National Park Service, червень 2022. http://dx.doi.org/10.36967/nrr-2293615.

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Natural resource management at Wilson’s Creek National Battleﬁeld (NB) is guided by our understanding of the woodlands and prairies at the time of the Civil War battle in 1861. This report is focused on the Manley Woods unit of the park. This unit is an oak-hickory woodland in the Springﬁeld Plain subsection of the Ozarks. Canopy closure for Missouri oak woodlands can be highly variable and ranges from 30–100% across the spectrum of savanna, open woodland, and closed woodland types. In 1861, the woodland was likely a savanna community. Changes in land use (e.g., ﬁre exclusion) caused an increase in tree density in woodlands at Wilson’s Creek NB and across the Ozarks. Savannas and open woodlands transitioned to closed canopy woodlands over time. Park management plans include restoring the area to a savanna/open woodland structure. Prescribed ﬁre was reintroduced to Wilson’s Creek NB in 1988 and continues as the primary mechanism for reducing the tree canopy. The Manley Woods unit of Wilson’s Creek NB has been subject to intense natural and anthropogenic disturbance events such as a tornado in 2003, timber removal in 2005, prescribed ﬁres in 2006, 2009, and 2019, an ice storm in 2007, and periodic drought. The Heartland Inventory and Monitoring Network (hereafter, Heartland Network) installed four permanent monitoring sites within the Manley Woods area of the park in 1997. Initially, we assessed ground ﬂora and regeneration within the sites (1998–1999). We added fuel sampling after the 2003 tornado. Although overstory sampling occurred prior to the tornado, the protocol was not yet stabilized and pre-2003 overstory data were not included in these analyses. In this report, we focus on the overstory, tree regeneration, and ground cover metrics; ground ﬂora data will be assessed in future analyses. Heartland Network monitoring data reveal that Manley Woods has undergone substantial change in canopy cover and midstory trees since 1998. While basal area and density metrics classify Manley Woods as an open woodland, the closed canopy of the midstory and overstory reveal a plant community that is moving toward closed woodland or forest structure. The most recent ﬁre in 2019 was patchy and mild, resulting in continued increases in fuels. Ground cover metrics indicate infrequent disturbance since leaf litter continued to increase. Management objectives to restore savanna or woodland composition and structure to the Manley Woods overstory, regeneration layer, and ground cover will require implementation of prescribed ﬁre in the future. Repeated ﬁres can thin midstory trees and limit less ﬁre tolerant early seral species. Additionally, mechanical or chemical treatments to reduce undesirable tree species should be considered for woodland restoration. Decreasing canopy closure is an important and essential step toward the restoration of a functioning savanna/open woodland plant community in Manley Woods. Treatments that thin the midstory and reduce fuel loading will also beneﬁt these plant communities. With the anticipated changing climate, maintaining an open woodland community type may also provide resilience through management for native species tolerant of increasingly warmer temperatures.

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Lewis, David J., and Ralph J. Alig. A spatial econometric analysis of land-use change with land cover trends data: an application to the Pacific Northwest. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 2014. http://dx.doi.org/10.2737/pnw-rp-600.

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Brown, D. G., C. Polsky, P. Bolstad, S. D. Brody, D. Hulse, R. Kroh, T. R. Loveland, and A. Thomson. Ch. 13: Land Use and Land Cover Change. Climate Change Impacts in the United States: The Third National Climate Assessment. Edited by J. M. Melillo, Terese (T C. ). Richmond, and G. W. Yohe. U.S. Global Change Research Program, 2014. http://dx.doi.org/10.7930/j05q4t1q.

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