Mapping forest aboveground biomass using airborne hyperspectral and LiDAR data in the mountainous conditions of Central Europe

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• 作者：Olga Brovkina^a ; ^{brovkina.o@czechglobe.cz} ; Jan Novotny^a ; Emil Cienciala^b ; Frantisek Zemek^a ; Radek Russ^b
• 关键词：Biomass estimation ; Spruce ; Beech ; Airborne remote sensing ; Tree level ; Plot level
• 刊名：Ecological Engineering
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：100
• 期：Complete
• 页码：219-230
• 全文大小：3668 K
• 卷排序：100

文摘

The study presents three methods for estimation of forest aboveground biomass (AGB) at tree and plot levels using different categories of airborne data. The first method estimates AGB from high spatial resolution hyperspectral (HS) data. The second method estimates AGB from airborne laser scanning data. The third method explores the synergy between hyperspectral and LiDAR data to estimate AGB. The results are compared with AGB estimated from field measurements. The results demonstrate that: 1) The biomass estimation from the HS data showed a good correlation with field biomass values for spruce, beech and mixture of these species at tree and plot levels, but also the highest uncertainties in comparison with the other two methods; 2) The biomass estimation from the LiDAR data had a strong correlation with field biomass values for spruce for tree level and a good correlation for spruce, beech and mixture of these species for plot level; 3) The biomass estimation from fused HS and LiDAR data showed the best results for tree and plot levels for the study sites. This study expands on previous research assessing the applicability of HS, LiDAR and fused datasets for AGB assessment. It proves the efficiency of using fused HS and LiDAR data and suggests the use of HS-based methods for biomass assessment when laser scanning data are not available.