Long-term moisture analysis using Remotely sensed data in Mongolia
The purpose of this research work is to estimate long-term soil moisture moisture content in central part of Mongolia. The soil moisture (SM) content is one of the most important environmental variables in relation to land surface climatology, hydrology and ecology. Climate is changing in the global...
| Main Authors: | , , , |
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| Format: | Conference Object |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://biblio.ugent.be/publication/8585228 http://hdl.handle.net/1854/LU-8585228 |
| Summary: | The purpose of this research work is to estimate long-term soil moisture moisture content in central part of Mongolia. The soil moisture (SM) content is one of the most important environmental variables in relation to land surface climatology, hydrology and ecology. Climate is changing in the global spotlight and Mongolia is a hotspot of climate change especially temperature rises and drought frequencies increased. Mongolia has six different natural zones which are high mountain, taiga forest, mountain forest steppe, steppe, desert steppe and desert. The amount of moisture is decreasing north to south. In my previous study, the annual evaporation is 150~250 mm in the steppe zone and over 150 mm in desert steppe and deserted zones. The study area includes seven provinces which are situated in the central part of Mongolia. It is situated between 589 and 2788 masl and contains thirty-eight climate stations. In the long-term analysis, satellite-derived products can provide moisture contents. For the interpolation, we interpolated precipitation data into raster imagery from May to August for the 2000-2013 over Mongolia using 127 climate stations. The potential evapotranspiration (PET) was estimated from MODIS data. The Normalized Difference Vegetation Index (NDVI) was calculated using the near infrared (NIR) and the visible red (RED) bands from the SPOT data during the growing season (May toAugust) for 2000-2013. The method of Mathew Tybersky (2008) used to derive from precipitation and PET. For the accuration, we used NDVI and climate station data. The results of the long-term soil moisture maps were compared with the NDVI data. The relationship between moisture of June and NDVI of July is determined 0.68, moisture of July and NDVI of August is determined 0.80. The amount of moisture (May-July) was compared with NDVI of August correlation coefficient was 0.75 and the relationship between amount of moisture (June-July) and NDVI of August was determined 0.79. According the results that moisture of previous months ... |
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