Assessment of biomass and net primary productivity of a dry tropical forest using geospatial technology

作     者：Tarun Kumar Thakur S.L.Swamy Arvind Bijalwan Mammohan J.R.Dobriyal 

作者机构：Department of Environmental Science Indira Gandhi National Tribal University (IGNTU) Department of Forestry Indira Gandhi Agricultural University Faculty of Technical Forestry Indian Institute of Forest Management Navsari Agriculture University 

出 版 物：《Journal of Forestry Research》 (林业研究（英文版）)

年 卷 期：2019年第30卷第1期

页      面：157-170页

核心收录：

学科分类：09[农学] 

基　　金：Indira Gandhi Agricultural University Chhattisgarh Council of Science and Technology, CGCOST 

主　　题：Allometric regression equations Fine root biomass Litter fall LAI NDVI Spectral models 

摘      要：This study quantifies biomass, aboveground and belowground net productivity, along with additional environmental factors over a 2-3 year period in Barnawapara Sanctuary of Chhattisgarh, India through satellite remotesensing and GIS techniques. Ten sampling quadrates20×20, 5×5 and 1×1 m were randomly laid for overstorey (OS), understorey (US) and ground vegetation(GS), respectively. Girth of trees was measured at breast height and collar diameters of shrubs and herbs at 0.1 m height. Biomass was estimated using allometric regression equations and herb biomass by harvesting. Net primary productivity (NPP) was determined by Ssumming biomass increment and litter crop values. Aspect and slope influenced the vegetation types, biomass and NPP in different forests. Standing biomass and NPP varied from 18.6 to101.5 Mg ha^(-1) and 5.3 to 12.7 Mg ha^(-1) a^(-1), respectively,in different forest types. The highest biomass was found in dense mixed forest, while net production recoded in Teak forests. Both were lowest in degraded mixed forests of different forest types. OS, US and GS contributed 90.4, 8.7and 0.7%, respectively, for the total mean standing biomass in different forests. This study developed spectral models for the estimation of biomass and NPP using Normalized Difference Vegetation Index and other vegetation *** study demonstrated the potential of geospatial tools for estimation of biomass and net productivity of dry tropical forest ecosystem.