Land cover classification is the most important element of land cover mapping and is a key input to many societal benefits. Traditional classification methods require a large amount of remotely sensed images, which are time consuming and labour intensive. Recently, crowdsourcing geographic information (CGI), including geo-tagged photos and other sources, has been widely used with lower costs, b...

Land degradation is a major danger which restricting different areas of Iran. Systematic description of the environmentfor detection of environmental changes and the human-related causes and responses is essential in land cover changestudy. Use of land cover data allow detection of where certain changes occur, what type of change, as well as how theland is changing. Existing systems for classif...

This study presents results for urban flood susceptibility mapping (FSM) using image-based 2D-convolutional neural networks (2D-CNN). The model input multiparametric spatial data comprised of land-useland-cover (LULC), digital elevation (DEM), and the topographic hydrologic conditioning derivatives, precipitation, soil types. implemented dropout regularization 2D-CNN with ReLU activation functi...

Land cover data constitutes highly useful information to monitor the extension and status of land resources, hence it has been realized how important it is to have accurate land cover data. Here, an interactive WebGIS is built in order to validate GlobeLand30 global land cover data. The Game with a Purpose (GWAP) human-based computation technique is adopted. The system is based on crowdsourcing...

Land cover classification using remotely sensed data is a critical first step in large-scale environmental monitoring, resource management and regional planning. The classification task is made difficult by severe atmospheric scattering and absorption, seasonal variation, spatial dependence, complex surface dynamics and geometries, and large intra-class variability. Most of the recent research ...

Problem statement: It is an important task to detect land cover changes from remotely sensed data for environmental monitoring. Although there are some applications of visual textures to the land use, they are limited to a few land cover categories with the application of one texture measure. Since land cover types are complex and often the integration of various objects, applying one texture m...

land use may be regarded as one of the most important factors affecting theenvironment with respect to human activities. so far, destroying the rangelands andchanging them into the waste lands and poor rangelands has been proposed as the mostsignificant variations of land use done by human beings. this paper has been conducted toevaluate the variations of vegetation percentage and land uses in ...

many investigations have demonstrated that arid regions display ideal conditions for remote sensing applications such as, land cover/land use detection. the aim of this study was to evaluate the capability of thematic mapper (tm) thermal band in land cover/land use mapping in the ardakan region of yazd province, an area of desert with severe salinity conditions, and the mook region in the f...

the growing population and increasing socio-economic necessities creates a pressure on land use/land cover. nowadays, land use change detection using remote sensing data provides quantitative and timely information for management and evaluation of natural resources. this study investigates the land use changes in part of hableh rood watershed of iran using landsat 7 and 8 (sensor etm+ and oli) ...

The Wisconsin Initiative for Statewide Cooperation on Landscape Analysis and Data (WISCLAND) is a consortium of government and private organizations formed in 1993 to promote development of digital geographic data for the state. The initial focus of the consortium was to acquire funding and resources to develop a land cover classification. That effort has now been completed statewide. This docu...