Estimating the fractional cover of photosynthetic vegetation, non-photosynthetic vegetation and bare soil from MODIS data: Assessing the applicability of the NDVI-DFI model in the typical Xilingol grasslands
Estimating the fractional cover of photosynthetic vegetation, non-photosynthetic vegetation and bare soil from MODIS data: Assessing the applicability of the NDVI-DFI model in the typical Xilingol grasslands
复制标题
利用MODIS数据估算光合植被、非光合植被和裸土覆盖度：评估NDVI-DFI模型在锡林郭勒典型草原的适用性
DOI：
10.1016/j.jag.2018.11.006
复制
发表时间：
2019-04
影响因子：
7.5
通讯作者：
Zhoulong Wang
中科院分区：
文献类型：
--
作者：
Guangzhen Wang;Jingpu Wang;Xueyong Zou;Guoqi Chai;Mengquan Wu;Zhoulong Wang
Quantitative estimations of the fractional cover of photosynthetic vegetation (fPV), non-photosynthetic vegetation (fNPV) and bare soil (fBS) are critical for soil wind erosion, desertification, grassland grazing, grassland fire, and grassland carbon storage studies. At present, regional and large-scalefPV,fNPVandfBSestimations have been carried out in many areas. However, few studies have used moderate resolution imaging spectroradiometer (MODIS) data to perform large-scale, long-termfPV,fNPVandfBSestimations in the Xilingol grassland of China. The objective of this study was to quantitatively estimate the time series offPV,fNPVandfBSin the typical grassland region of Xilingol from MODIS image data. Field measurement spectral and coverage data from May and September 2017 were combined with the 8-day composite product (MOD09A1) acquired during 2017. We established an empirical linear model of different non-photosynthetic vegetation indices (NPVIs) andfNPVbased on the sample scale. The linear correlation between the dead fuel index (DFI) andfNPVwas best (R2= 0.60, RMSE = 0.15). A normalized difference vegetation index (NDVI)-DFI model based on MODIS data was proposed to accurately estimate thefPV,fNPVandfBS(estimation accuracies of 44%, 71%, and 74%, respectively) in the typical grasslands of Xilingol in China. ThefPV,fNPVandfBSvalues for the typical grassland time series estimated by the NDVI-DFI model were consistent with the phenological characteristics of the grassland vegetation. The results show that the application of the NDVI-DFI model to the Xilingol grassland is reasonable and appropriate, and it is of great significance to the monitoring of soil wind erosion and fires in grasslands.
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影响因子：
13.5
作者：
J. A. Ballantine;G. Okin;D. Prentiss;D. Roberts
通讯作者：
J. A. Ballantine;G. Okin;D. Prentiss;D. Roberts
影响因子：
13.5
作者：
D. Jacques;L. Kergoat;P. Hiernaux;E. Mougin;P. Defourny
通讯作者：
D. Jacques;L. Kergoat;P. Hiernaux;E. Mougin;P. Defourny
DOI：
10.3390/rs8080692
发表时间：
2016-08
期刊：
Remote. Sens.
影响因子：
--
作者：
H. Jackson;S. Prince
通讯作者：
H. Jackson;S. Prince
影响因子：
3.4
作者：
Xin Cao;X. Cui;Miao Yue;Jin Chen;H. Tanikawa;Y. Ye
通讯作者：
Xin Cao;X. Cui;Miao Yue;Jin Chen;H. Tanikawa;Y. Ye
影响因子：
3.4
作者：
M. Hill;Qiang Zhou;Q. Sun;C. Schaaf;J. Southworth;Niti B. Mishra;Cerian Gibbes;Erin L. Bunting;Thomas B. Christiansen;K. Crews
通讯作者：
M. Hill;Qiang Zhou;Q. Sun;C. Schaaf;J. Southworth;Niti B. Mishra;Cerian Gibbes;Erin L. Bunting;Thomas B. Christiansen;K. Crews