Evaluation of the Airborne CASI/TASI Ts-VI Space Method for Estimating Near-Surface Soil Moisture

作者:Fan, L (Fan, Lei)[ 1,2 ] ; Xiao, Q (Xiao, Qing)[ 1 ] ; Wen, JG (Wen, Jianguang)[ 1,3 ] ; Liu, Q (Liu, Qiang)[ 4 ] ; Tang, Y (Tang, Yong)[ 1 ] ; You, DQ (You, Dongqin)[ 1,2 ] ; Wang, HS (Wang, Heshun)[ 1 ] ; Gong, ZN (Gong, Zhaoning)[ 5 ] ; Li, XW (Li, Xiaowen)[ 6 ]

REMOTE SENSING

卷: 7  期: 3  页: 3114-3137

DOI: 10.3390/rs70303114

出版年: MAR 2015

摘要

High spatial resolution airborne data with little sub-pixel heterogeneity were used to evaluate the suitability of the temperature/vegetation (Ts/VI) space method developed from satellite observations, and were explored to improve the performance of the Ts/VI space method for estimating soil moisture (SM). An evaluation of the airborne Delta T-s/Fr space (incorporated with air temperature) revealed that normalized difference vegetation index (NDVI) saturation and disturbed pixels were hindering the appropriate construction of the space. The non-disturbed Delta T-s/Fr space, which was modified by adjusting the NDVI saturation and eliminating the disturbed pixels, was clearly correlated with the measured SM. The SM estimations of the non-disturbed Delta T-s/Fr space using the evaporative fraction (EF) and temperature vegetation dryness index (TVDI) were validated by using the SM measured at a depth of 4 cm, which was determined according to the land surface types. The validation results show that the EF approach provides superior estimates with a lower RMSE (0.023 m(3)center dot m(-3)) value and a higher correlation coefficient (0.68) than the TVDI. The application of the airborne Delta T-s/Fr space shows that the two modifications proposed in this study strengthen the link between the Delta T-s/Fr space and SM, which is important for improving the precision of the remote sensing Ts/VI space method for monitoring SM.

通讯作者地址: Xiao, Q (通讯作者)

Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.

地址:

[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China

[ 2 ] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

[ 3 ] Joint Ctr Global Change Studies, Beijing 100875, Peoples R China

[ 4 ] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China

[ 5 ] Capital Normal Univ, Coll Resource Environm & Tourism, Beijing 100048, Peoples R China

[ 6 ] Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China