To extract quantitative land information accurately and monitor the air pollution at city scale from moderate to high spatial resolution (MHSR) with a resolution no coarser than 30 m, optical remotely sensed imagery and aerosol parameters, especially aerosol optical depth (AOD), are a necessary step. In this paper, we introduce a new algorithm that can effectively estimate the spatial distribut...

In the present paper a geospatial analysis is performed to understand the meandering behaviour of Barak River in southern Assam between 1988 and 2010. Landsat images (with Thematic mapper and Enhanced thematic mapper-plus sensors) for years 1988, 1999, and 2010 are considered for the study. River Barak within the study area is digitized as polygons for three years and sinuosity index (SI) are c...

Urbanization is found to be closely associated with land use/land cover change which has an important influence in our environment and ecosystems, such as urban heat island effect, biodiversity loss, soil erosion, and pollutions. Studies on accurately simulating urban expansion have been inspired by increasing concerns of the sustainability of urban development. This paper reports our research ...

The broad overviews obtained with Landsat data can provide information concerning the location, types, and magnitudes of forest changes not easily obtainable by other means. One of the main goals of the current study is to provide spatial information regarding the more subtle forms of forest change rather than those primarily related to land cover conversion. A forest-dominated area in northern...

Urban development has expanded rapidly in the Las Vegas, Nevada metropolitan area over the last fifty years. Associated with this growth trend has been the transformation of the landscape from natural cover types to increasingly impervious urban land. To map urban extent and its change over time, an innovative approach is employed that determines sub-pixel impervious surfaces from highresolutio...

The quality of remotely sensed land use and land cover (LULC) maps is affected by the accuracy of image data classifications. Various efforts have been made in advancing supervised or unsupervised classification methods to increase the repeatability and accuracy of LULC mapping. This study incorporates a data-assisted labeling approach (DALA) into the unsupervised classification of remotely sen...

The USDA Forest Service, through its Forest Inventory and Analysis (FIA) program, periodically estimates forest/non-forest area at the county level using aerial photographs. Satellite-based remotely sensed data and digital image processing techniques could substantially reduce the time required to generate this information. Satellites collect data on a repeat basis and with higher frequency tha...

a knowledge of soil surface conditions, especially desert crust, salt crust and desert varnish is useful for improving classification of remotely sensed data. desert crust can generate high levels of reflectance, similar to those areas with high salt concentration and non-saline soil. therefore, soil surface crusts might bias thematic remote sensing of soils. in this study, we evaluated the eff...