An ever increasing population associated with various other factors has put tremendous pressure on the environment and its respective resources. Hence it has become necessary to study the human interactions with its surrounding environment to facilitate sustainable developmental plans. Land use and land cover is the most dominant factor to study these interactions. Remote Sensing technology has...

In the presented methodology, multitemporal Landsat images were used to develop enhanced information about complex assemblages of vegetation and patterns of seasonal land cover variability, thereby facilitating improved land use and land cover (LULC) classification of urbanized areas among sensitive environments along the Mississippi Gulf Coast. For Landsat-5 and Landsat-7 images acquired for l...

1:50000 land cover classification and mapping program is an important part of the mapping project in western China, which is organized by Chinese State Bureau of Surveying and Mapping Organization and will finish 5032 maps at scale of 1:50000 until 2010. With an average altitude of 4400 m, Sanjiangyuan mapping district is located at the center of the Qinghai-Tibet Plateau. Because of complicate...

Although geographic object based image analysis (GEOBIA) has been successfully applied to derive local maps (1-10s km) from very high spatial resolution (VHR) image data (pixels < 1.0 x 1.0 m), its potential for automatically mapping large areas remains unknown. The aim of this study was to create and apply a GEOBIA method to automatically map land cover classes in subsets with different enviro...

Global land cover data are fundamental for applications, especially ecological environmental assessment and climate change research. Currently available global land cover data products show some deficiencies in data accuracy and spatial and temporal resolution. So we discuss fast automatic classification methods for the study area in Antarctica. A classification method based on a Support vector...

SUMMARY One of the main parameter for urban heat island mapping is the land cover information. Satellite data were used to map the land cover over the study area, CyberJaya. Remotely sensed data were processed using pixel based and object based image processing techniques. Most traditional classification approaches are based exclusively on the digital number of the pixel itself. Thereby only th...

Remotely sensed multi-spectral and -spatial data facilitates the study of mosquito-borne disease vectors and their response to land use and cover composition in the urban environment. In this study we assess the feasibility of integrating remotely sensed multispectral reflectance data and LiDAR (Light Detection and Ranging)-derived height information to improve land use and land cover classific...

The world is witnessing a dramatic shift of settlement pattern from rural to urban population, particularly in developing countries. The rapid Addis Ababa urbanization reflects this global phenomenon and the subsequent socio-economic and environmental impacts, are causing massive public uproar and political instability. The objective of this study was to use remotely sensed Landsat data to iden...

Commercially available high-resolution satellite imagery from sensors such as IKONOS and QuickBird are important data sources for a variety of urban area applications including infrastructure feature extraction and land cover mapping. Land cover maps from medium and high-resolution imagery are typically generated through supervised spectral classification of multispectral imagery. Supervised cl...