Land cover class composition of remotely sensed image pixels can be estimated using soft classification techniques increasingly available in many GIS packages. However, their output provides no indication of how such classes are distributed spatially within the instantaneous field of view represented by the pixel. Techniques that attempt to provide an improved spatial representation of land cov...

Land cover data derived from satellites are commonly used to prescribe inputs to models of the land surface. Since such data inevitably contains errors, quantifying how uncertainties in the data affect a model’s output is important. To do so, a spatial distribution of possible land cover values is required to propagate through the model’s simulation. However, at large scales, such as those requ...

always mazandaran province had been exposed to development and changes because of location in coastline of the caspian sea and having unique conditions. gis and remote sensing can be used to monitor in order to manage this sensitive province. then, this study is trying to detect land cover changes in coastal areas of mazandaran province using lcm. land cover changes detection have done using la...

Land Use/Land Cover (LULC) changes alter the ecosystem structure and function, resulting in variations of Ecosystem Service Values (ESVs). This study investigated impacts LULC on ESVs over 37 years Cherangany Hills Water Tower (CHWT) Kenya. Landsat images from 1985 2022 were used to examine historical CHWT. Supervised classification was carried out using Random Forest (RF) classifier R-Studio w...

Land cover plays a key role in terrestrial biogeochemical processes. Therefore many problems require accurate information on the distribution and properties of land cover. A decision tree classi cation algorithm is used to generate a land cover map of North America from remotely sensed data with 1 km resolution in a 6-biome classi cation scheme. To do this, the normalized di erence vegetation i...

Land-cover mapping efforts within the USGS Gap Analysis Program have traditionally been state-centered; each state having the responsibility of implementing a project design for the geographic area within their state boundaries. The Southwest Regional Gap Analysis Project (SWReGAP) was the first formal GAP project designed at a regional, multi-state scale. The project area comprises the southwe...

The main goal of this study is to develop a general framework for building a hybrid land-cover map by the synergistic combination of a number of land-cover classifications with different legends and spatial resolutions. The proposed approach assesses class-specific accuracies of datasets and establishes affinity between thematic legends using a common land-cover language such as the UN Land-Cov...