Vegetation Parameter Derivation for Forest Health Measurement and Stress Detection in a Time Series

Abstract

Abstract

The forest health of Jharkhand is declining for the reasons which includes heavy unscientific mining, climate change, air pollution and increased human activities. Vegetation plays a key role in reducing an ambient temperature, moisture and pollutant capture, energy use and subsequent ground level ozone reduction. There is an urgent need of detailed measurement and monitoring of forest’s health. Modern technological advancement in the field of remote sensing technology enables us to quantify and observe various parameters and health of vegetation. In this present study a comprehensive approach of vegetation indices, satellite derived land surface temperature and field study has been adopted to monitor forest health of Ghatsila, Musabani and Dhalbhumgarh block, Jharkhand over a period of 25 years. In recent years, vegetation mapping has become more and more important especially when the climate is changing dynamically. Traditionally, the field survey has been used to calculate the forest health. Hear we used some index like SAVI, TCI and LST to calculate vegetation health and also modified this index to calculate modified vegetation condition Index (MVCI) and new- generation vegetation health index (NVHI). After analysis of NVHI and complete extended field visit we found better results when compared to the traditional health index.

Keywords: SAVI, MVCI, TCI, LST, NVHI, forest health

Cite this Article

Somnath Maiti, Rajat Satpathy, Jatisankar Bandyopadhyay et al. Vegetation parameter derivation for forest health measurement and stress detection in a time series. Research & Reviews: Journal of Ecology. 2015; 4(3): 19–26p.