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Retrieving land surface temperature and soil moisture from HJ-1B data: A case study of Yimin open-cast coal mine region in Hulunbeier grassland |
| ZHAO Feifei1, 2, BAO Nisha1, WU Lixin1, 3, SUN Rui4 |
1. Institute for Geo-information & Digital Mine Research, Northeastern University, Shenyang 110819, China;
2. Beijing SatImage Information Technology Co., Ltd, Beijing 100048, China;
3. School of Geoscience and Info-Physics, Central South University, Changsha 410083, China;
4. Jiangsu Geologic Surveying and Mapping Institute, Nanjing 210008, China |
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Abstract The soil moisture can be considered as an appropriate indicator to investigate the level of ecological environment disturbance resulting from mining activities in semi-arid grassland. The main objective of this research is to explore the applicability of Chinese HJ-1B data for LST and soil moisture monitoring around mining-affected areas on the local scale. The JM&S, Qin and Artis methods for temperature retrieval were comparatively analyzed. The relationship space of NDVI-LST was used to generate temperature vegetation dryness index(TVDI). Furthermore, the reference data including in situ soil moisture and MODIS LST products were used for “dry edge” correcting of TVDI. Some conclusions have been reached: The Qin’s mono-window algorithm performs best in LST retrieval from HJ-1B data; there is a highest correlation between corrected TVDI value with C=0.3 and in situ soil moisture value; the feature of NDVI-LST space indicates that there is a linear relationship for “wet edge”, while the relationship for “dry edge” is conic; the TVDI imagery and LST imagery show different drought conditions of different features. The obvious geographical heterogeneity has been found from the TVDI and LST imagery in this area as well.
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| Keywords
SRTM
DEM
hydrologic analysis
LiDAR
topographic wetness index
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Issue Date: 15 August 2017
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2017,
Vol. 29
