Ms. Die Hu Profile

Die Hu

at Lanzhou Institute of Arid Meteorology

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Proceedings Article | 22 October 2018 Paper

Preliminary study on the applicability of several remote sensing drought indices to agricultural drought monitoring in Gansu province of China

Sha Sha, Die Hu, Lijuan Wang, Yiping Li

Proceedings Volume 10777, 107770H (2018) https://doi.org/10.1117/12.2324624

KEYWORDS: Remote sensing, Vegetation, Agriculture, MODIS, Scientific research

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The spacing of Gansu Province from the eastern to western regions is very large and adjacent to the Qinghai–Tibet Plateau. On the one hand, Agriculture in western area is irrigated rather than non-irrigated agriculture in eastern area. On the other hand, elevation where adjacent to the Tibetan Plateau is much higher than other places. In this study, remote sensing drought indices, such as temperature vegetation dryness index (TVDI), vegetation condition index (VCI), temperature condition index (TCI), perpendicular drought index (PDI), and modified perpendicular drought index (MPDI), were calculated using historical MODIS data. The applicability of these remote sensing indices was preliminarily studied by comparing the Relative Soil Moisture (RSM) of the sites. Results showed that:1) In whole area, irrigated areas and high-altitude areas, the remote sensing indices have different degree of indication for the spatial distribution of RSM in the superficial layer in spring, summer, and autumn. Among them, TVDI has the best indication, followed by VCI and TCI, and PDI and MPDI have very limited indication. But TVDI has no indication in May in irrigated areas at all. 2) None of them can indicate the temporal variation characteristics of the RSM in the irrigated areas, and TVDI and TCI based on the surface temperature can indicate the temporal variation of the 10 and 20 cm-deep RSM in the high-altitude areas. In general, TVDI is a good indicator for RSM in the superficial layer in Gansu Province during spring, summer, and autumn.

Proceedings Article | 8 November 2014 Paper

Estimate the soil moisture over semi-arid region of Loess Plateau using Radarsat-2 SAR data

D. Hu, N. Guo, L. Wang, S. Sha

Proceedings Volume 9260, 92602N (2014) https://doi.org/10.1117/12.2068501

KEYWORDS: Soil science, Vegetation, Data modeling, Polarization, Backscatter, Synthetic aperture radar, Radar, Remote sensing, MODIS, Microwave remote sensing

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Radarsat-2 Synthetic Aperature Radar (SAR) remote sensing data were used to record soil surface moisture and evaluate the utility of a cross polarization (VV/VH) combination. Studies were conducted at Dingxi, in the semi-arid region of the Loess Plateau, China. We combined these data with MODIS optical data, used a Water-Cloud model to correct for the influence of vegetation, and then estimated the soil moisture under crop cover. For bare surfaces, the value of the cross polarization combination model was highly correlated to the measurement of soil moisture at 10~20 cm depth (R=0.75, P<0.01). The correlations between estimated values and the measured soil moisture at 0~10 cm and 20~30 cm depths were lower but still significant (R=0.47 and R=0.52, respectively, P<0.05). For soil surfaces covered with vegetation the model significantly underestimated soil moisture. After vegetation removal, the correlation coefficient increased from 0.30 to 0.70, the standard deviation decreased from 4.99 to 3.05, and the accuracy of the soil moisture model improved. Most soil moisture readings in the study area were 10~30％ and these were consistent with the actual field moisture levels. Improving the accuracy of soil moisture readings in agricultural fields using optical and microwave remote sensing data will promote increased use of this technology.

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