This paper describes the methodology developed and implemented for Remote Sensing DataBase (RSDB) preparation from multitemporal and multi-sensor data from Indian earth observation satellites. The characteristics of the RSDB prepared over parts of IndoGangetic Basin and Central India (IGB&CI) are summarised. An approach for extraction of long term (1988-89 to 2004-05) Land Use / Land Cover (LUL...

This study adopted a differential land-use/landcover (LULC) analysis to evaluate dam-triggered land– atmosphere interactions for a number of LULC scenarios. Two specific questions were addressed: (1) can damtriggered LULC heterogeneities modify surface and energy budget, which, in turn, change regional convergence and precipitation patterns? (2) How extensive is the modification in surface mois...

Soil moisture is a critical process in the water cycle and its assessment is of paramount importance to forecast changes in the water balance of a region. Ground Penetrating Radar (GPR) technology overcomes the limitations of point data by producing a tridimensional view of subsurface characteristics with a large economy of time, logistic, data processing and analysis. The purpose of this resea...

Land use–land cover (LULC) is an important feature for ecological environment research, land resource management and evaluation. Although global high-resolution LULC data sets are booming, their regional performances were still evaluated in limited regions. To demonstrate the local applicability of products, six emerging products compared Guangxi, China. The used European Space Agency GlobCover...

The state of Kerala, India, experienced massive flooding in August 2018. Unprecedented extreme rainfall left the region with huge losses infrastructure. Several studies reported role improper dam operations and climate change this region. However, changing land use/land cover (LULC) is an important driver flood modulation; we therefore studied regional LULC changes (over 4 decades) their impact...

Traditional pixel-based classification methods yield poor results when applied to synthetic aperture radar (SAR) imagery because of the presence of the speckle and limited spectral information in SAR data. A novel classification method, integrating polarimetric target decomposition, object-oriented image analysis, and decision tree algorithms, is proposed for land use and land cover (LULC) clas...

Multi-scale/multi-level geographic object-based image analysis (MS-GEOBIA) methods are becoming widely-used in remote sensing because single-scale/single-level (SSGEOBIA) methods are often unable to obtain an accurate segmentation and classification of all land use/land cover (LULC) types in an image. However, there have been few comparisons between SS-GEOBIA and MS-GEOBIA approaches for the pu...

land surface temperature (lst) is an important factor in global change studies. the information about lst has an important role in the range of issues and themes in earth sciences such as global environment change, human-environment interaction and more specifically to urban climatology. this research has been undertaken to analyze the potential of multispectral satellite data for retrieving th...