The production of thematic maps, such as those depicting land cover, using an image classification is one of the most common applications of remote sensing. Considerable research has been directed at the various components of the mapping process, including the assessment of accuracy. This paper briefly reviews the background and methods of classification accuracy assessment that are commonly us...

The research used the satellite image (Landsat 7 ETM ) within the thermal infrared sixth band (TIR6) and geographic information system (GIS) to determine the air pollution and its relationship with the land cover (LC) and land use (LU) of Baghdad city. Concentration of total suspended particles (TSP), lead (Pb), carbon oxides (CO, CO2), and sulphur dioxide (SO2) were obtained from 22 ground mea...

Novel statistical modeling and training techniques are proposed for improving classification accuracy of land cover data acquired by LandSat Thermatic Mapper (TM). The proposed modeling techniques consist of joint modeling of spectral feature distributions among neighboring pixels and partial modeling of spectral correlations across TM sensor bands with a set of semi-tied covariance matrices in...

Support vector machines represent a promising development in machine learning research that is not widely used within the remote sensing community. This paper reports the results of Multispectral(Landsat-7 ETM+) and Hyperspectral DAIS)data in which multi-class SVMs are compared with maximum likelihood and artificial neural network methods in terms of classification accuracy. Our results show th...

Land cover plays a significant role in the earth system science, which reflects the influence of human activities and environmental changes (Sellers et al., 1997; IGBP, 1990; Aspinall et al, 2004). In China, Many land use/cover maps can be used in recent years derived from remote sensing observation. These data will be whether or how combined effectively to produce better land cover map that is...

Numerous applications make use of data on land use and land cover (LULC). Given their importance and use, land cover data is assumed to be readily available or trivially acquired for a given landscape. Unfortunately, this is often not the case. LULC data at hand are often out-of-date, inappropriate for a particular application [1], or contain other difficulties. Thematic mapping of remotely sen...

Digital Elevation Models (DEMs) and land cover products are primary inputs for hydrologic models of surface runoff that affects infiltration, erosion, and evapotranspiration. DEM and land cover play important role in determining the runoff characteristics of specific catchment areas. Recently, at local level, a number of data sources have been used to derive land cover products for high resolut...

Statewide land-cover change detection analysis provides a useful tool for conservation planning and environmental monitoring and addresses issues of habitat fragmentation and urban sprawl. Furthermore, land-cover data offer a historical and recent perspective on landscape dynamics. To this end, the first alliance level land-cover map of Kansas (Kansas Vegetation Map) recently completed by the K...

CORINE Land Cover is an Europeanwide land cover and land use classification which is based in most countries on visual interpretation of satellite images. The new CORINE2000 classification of Finland is based automated interpretation of satellite images and data integration with existing digital map data. Satellite images are used in estimation of continuous variables describing vegetation type...

Objects on the surface of earth describe unique patterns in time and this is exploited in the proposed land cover classification method enumerated in this paper. The applicability of various distance measures to reasonably find similarity or dissimilarity between time series vegetation index patterns for land cover classification is demonstrated. These distance metrics have inherent advantages ...