Paper
10 October 2018 Land degradation assessment of agricultural zone and its causes: a case study in Mongolia
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Abstract
Land degradation is a serious environmental issue in the world. Both space and ground-based observations could be used to define the land changes and develop the assessment of land degradation. This study assessed land degradation in the Orkhon sub-province, the best representation sample in the prominent agricultural zone of Mongolia, using Landsat Thermal Mapper (TM) and Landsat Operation Land Imager (OLI) satellite images during the periods of 1990, 1994, 2000, 2006, 2010, and 2015. The land degradation of a region could be detected by changes in spectral indices and correlation of these indices. The most frequently used spectral indices include Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), and Normalized Difference Water Index (NDWI). These indices were selected as indicators for representing land surface conditions vegetation biomass, landscape pattern, micrometeorology and human activities. The land degradation analysis was described by descriptive statistics, correlation distributions and correlation coefficients of changes in index outputs. In addition, the validations of these indices were also verified by comparing LST and NDWI index values with in-situ, realtime climate data from 1984 to 2010. The Land Degradation Risk Mapping (LDRM) analysis shows that the agricultural and urban areas experienced degradation due to human activities and this has led to decline in the soil moisture in this region.
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Byambakhuu Gantumur, Falin Wu, Battsengel Vandansambuu, Tsogtdulam Munaa, Fareda Itiritiphan, and Yan Zhao "Land degradation assessment of agricultural zone and its causes: a case study in Mongolia", Proc. SPIE 10783, Remote Sensing for Agriculture, Ecosystems, and Hydrology XX, 107831W (10 October 2018); https://doi.org/10.1117/12.2325164
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Cited by 5 scholarly publications.
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KEYWORDS
Earth observing sensors

Landsat

Vegetation

Agriculture

Statistical analysis

Soil science

Satellites

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