Exploring the potential of Sentinel-2A satellite data for aboveground biomass estimation in fragmented Himalayan subtropical pine forest

作     者：Mobushir Riaz KHANI Iftikhar Ahmad KHAN Muhammad Hasan Ali BAIG LIU Zheng-jia Muhammad Irfan ASHRAF Mobushir Riaz KHAN;Iftikhar Ahmad KHAN;Muhammad Hasan AliBAIG;LIU Zheng-jia;Muhammad Irfan ASHRAF

作者机构：School of Environmental ScienceCharles Sturt UniversityAlburyNSW 2640Australia Institute of Geo-information&Earth ObservationArid Agriculture University RawalpindiPakistan&(ii)Department of ForestAzad Jammu&Kashmir Muzaffarabad-i3100Pakistan Institute of Geo-information&Earth Observation(IGEO)PMAS Arid Agriculture University Rawalpindi 46300Pakistan Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Department of Forestry&Range ManagementPMAS Arid Agriculture University Rawalpindi 46300Pakistan 

出 版 物：《Journal of Mountain Science》 (山地科学学报（英文）)

年 卷 期：2020年第17卷第12期

页      面：2880-2896页

核心收录：

学科分类：09[农学] 0903[农学-农业资源与环境] 

主　　题：Field inventory Forest Biomass Sentinel 2A AGB Modelling Spectral features Textures 

摘      要：The Sentinel-2 A satellite having embedded advantage of red edge spectral bands offers multispectral imageries with improved spatial,spectral and temporal resolutions as compared to the other contemporary satellites providing medium resolution *** study was aimed at exploring the potential of Sentinel-2 A imagery to estimate Above Ground Biomass(AGB) of Subtropical Pine Forest in Pakistan administered *** developed an AGB predictive model using field inventory and Sentinel 2 A based spectral and textural parameters along with topographic features derived from ALOS Digital Elevation Model(DEM).Field inventory data was collected from 108 randomly distributed plots(0.1 ha each) across the study *** stepwise linear regression method was employed to investigate the potential relationship between field data and corresponding satellite *** and carbon mapping of the study area was carried out through established AGB estimation model with R(o.86),R2(0.74),adjusted R2(0.72) and RMSE value of 33 t/*** results showed that first order textures(mean,standard deviation and variance) significantly contributed in AGB predictive modeling while only one spectral band ratio made contribution from spectral *** study leads to the conclusion that Sentinel-2 A optical data is a potential source for AGB estimation in subtropical pine forest of the area of interest with added benefit of its free of cost availability,higher quality data and long-term continuity that can be utilized for biomass carbon distribution mapping in the resource constraint study area for sustainable forest management.