Using NDVI-NSSI feature space for simultaneous estimation of fractional cover of non-photosynthetic vegetation and photosynthetic vegetation

被引:8
|
作者
Zhu, Cuicui [1 ,2 ,4 ]
Tian, Jia [1 ,3 ]
Tian, Qingjiu [1 ,2 ,4 ]
Wang, Xiaoqiong [1 ,2 ]
Li, Qianjing [1 ,2 ]
机构
[1] Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210023, Peoples R China
[2] Nanjing Univ, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Nanjing 210023, Peoples R China
[3] Beihang Univ, Sch Instrumentat & Optoelect Engn, Beijing 100191, Peoples R China
[4] Minist Nat Resources, Key Lab Urban Land Resources Monitoring & Simulat, Shenzhen 518000, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Non -photosynthetic vegetation; Vegetation coverage; Pixel decomposition; NDVI; NSSI; LEAF-AREA INDEX; BARE SOIL; HYPERSPECTRAL DATA; LAI; RESIDUE; PERFORMANCE; VALIDATION; ALGORITHMS; DYNAMICS; HYPERION;
D O I
10.1016/j.jag.2023.103282
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
The NDVI-NSSI feature space, which is constructed by the NPV soil separation index (NSSI) calculated from the two near-infrared bands and the normalized difference vegetation index (NDVI), is often represented as a triangle. It can be combined with the pixel decomposition method to achieve simultaneous estimation of the fractional cover of non-photosynthetic vegetation, photosynthetic vegetation, and bare soil (fNPV, fPV, and fBS, respectively). However, NDVI saturation in dense vegetation and the deleterious effects of shading due to topography are inevitable. To overcome this difficulty, we compare and analyze the NDVI-NSSI and enhanced vegetation index-NSSI (EVI-NSSI) triangular spaces and their differences when applying on the Sentinel-2A/B images. The results show that EVI-NSSI index combination still forms a triangle-like feature, with the triangle transformed from obtuse to acute, and it can be better used for pixel three-decomposition when PV cover is high. NDVI-NSSI underestimates (overestimates) fPV when PV cover is low (high). The NDVI-NSSI and EVI-NSSI produce significantly different estimates of fPV and fBS but similar estimates of fNPV and can be combined for estimation of a wider range of NPV cover in different seasons, including sparse or dense green vegetation scenarios.
引用
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页数:13
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