The objective of this study was to demonstrate a new, cost-effective method to define the sustainable amounts of harvested wood products in Southeast Asian countries case studies, while avoiding degradation (net loss) of total wood carbon stocks. Satellite remote sensing from the MODIS sensor was used in the CASA (Carnegie Ames Stanford Approach) carbon cycle model to map forest production for the Southeast Asia region from 2000 to 2010.

Sometime due to major accident and leakage the situation become worst for the nearby peoples. Kedarnath is a town located in the Indian state of Uttarakhand and has gained importance because of Kedarnath Temple located at the latitude of 30.73 and the longitude of 79.06. This region is seismically and ecologically very sensitive and delicate, even a minute changes (anthropogenic or natural) can create a dangerous disaster. A natural hazardous has been happened in Kedarnath valley due to torrential rainfall during 16 and 17 June 2013.

Wetlands, such as those of the Tana River Delta in Kenya, are vital but threatened ecosystems. The flooding characteristics of wetlands largely determine their physical, chemical and biological properties, so their quantification is crucial for wetland management. This quantification can be achieved through hydrological modelling. In addition, the analysis of satellite imagery provides essential hydrological data to monitor floods in poorly gauged zones.

Forest protection policies potentially reduce deforestation and re-direct agricultural expansion to already-cleared areas. Using satellite imagery, we assessed whether deforestation for conversion to pasture and cropland decreased in the lowlands of northern Costa Rica following the 1996 ban on forest clearing, despite a tripling of area under pineapple cultivation in the last

Satellite images provide information on the flood disaster footprints, which is essential for assessing the disaster impact and taking up flood mitigation activities. The Brahmaputra floods that occurred during June–July 2012 devastated a large part of Assam. This article discusses the maximum spatial extent affected due to the flood event, villages marooned and population affected, with the aid of multi-temporal satellite images coupled with the hydrological observations and freely available gridded population data.