000			01543nam a2200133Ia 4500
008			220615s9999||||xx |||||||||||||| ||und||
020			_a9783040000000
245		0	_aApplications of Remote Sensing Data in Mapping of Forest Growing Stock and Biomass
546			_aEnglish[eng]
650			_aAGB estimation and mapping||mangroves||UAV LiDAR||WorldView-2||terrestrial laser scanning||above-ground biomass||nondestructive method||DBH||bark roughness||Landsat dataset||forest AGC estimation||random forest||spatiotemporal evolution||aboveground biomass||variable selection||forest type||machine learning||subtropical forests||Landsat 8 OLI||seasonal images||stepwise regression||map quality||subtropical forest||urban vegetation||biomass estimation||Sentinel-2A||Xuzhou||forest biomass estimation||forest inventory data||multisource remote sensing||biomass density||ecosystem services||trade-off||synergy||multiple ES interactions||valley basin||norway spruce||LiDAR||allometric equation||individual tree detection||tree height||diameter at breast height||GEOMON||ALOS-2 L band SAR||Sentinel-1 C band SAR||Sentinel-2 MSI||ALOS DSM||stand volume||support vector machine for regression||ordinary kriging||forest succession||leaf area index||plant area index||machine learning algorithms||forest growing stock volume||SPOT6 imagery||Pinus massoniana plantations||sentinel 2||landsat||remote sensing||GIS||shrubs biomass||bioenergy||vegetation indices
700			_aAranha, José
856			_uhttps://mdpi.com/books/pdfview/book/4062
942			_cEB
999			_c12570 _d12570