Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 537-542, 2016
https://doi.org/10.5194/isprs-archives-XLI-B7-537-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
21 Jun 2016
MONITORING SOIL MOISTURE IN A COAL MINING AREA WITH MULTI-PHASE LANDSAT IMAGES
J. L. Kong1,2, T. Xian1, J. Yang1, L. Chen1, and X. T. Yang1 1School of Earth Science and Resources, Chang’an University, 126 Yanta Road, Xi'an 710054, China
2Key Laboratory of Subsurface Hydrology and Ecology in Arid Areas (Chang’an University), Ministry of Education, Xi’an 710054, China
Keywords: Monitoring soil moisture, Remote sensing retrieval, Landsat images, Ground surface deformation, Coal mining area Abstract. The coal development zone of Northern Shaanxi, China is one of the eight largest coal mines in the world, also the national energy and chemical bases. However, the coal mining leads to ground surface deformation and previous studies show that in collapse fissure zone soil water losses almost 50% compared with non-fissure zone. The main objective of this study is to develop a retrieval model that is reliable and sensitive to soil moisture in the whole coal mining zone of Northern Shaanxi based upon the soil sample parameters collected from in situ site investigation, spectral data gathered simultaneously and the images of Landsat7 ETM. The model uses different phases of Landsat data to retrieve soil moisture and analyze the patterns of spatial and temporal variations of soil moisture caused by ground deformation in the coal mining areas. The study indicated that band4 of Landsat7 ETM is the most sensitive band for soil moisture retrieval using the spectrum method. The quadratic model developed by remote sensing reflectance (Rrs4) (corresponding to the band4) is the best pattern with the correlation coefficient of 0.858 between the observed and the estimated soil moisture. Two-phase Landsat7 ETM data of 2002 and 2009 and one phase Landsat8 OLI data of 2015 for the study area were selected to retrieve soil moisture information. The result showed that the mean relative error was 35.16% and the root-mean-squared error (RMSE) was 0.58%. The changes of the spatial distribution of inversed soil moisture revealed that the trend of soil moisture contents of the study area was in general being gradually reduced from 2002 to 2015. The study results can serve as the baseline for monitoring environmental impacts on soil moisture in the regions due to coal mining.
Conference paper (PDF, 1861 KB)


Citation: Kong, J. L., Xian, T., Yang, J., Chen, L., and Yang, X. T.: MONITORING SOIL MOISTURE IN A COAL MINING AREA WITH MULTI-PHASE LANDSAT IMAGES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 537-542, https://doi.org/10.5194/isprs-archives-XLI-B7-537-2016, 2016.

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