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Long-term soil moisture content estimation using satellite and climate data in agricultural area of Mongolia

(2019) GEOCARTO INTERNATIONAL. 34(7). p.722-734
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Abstract
The purpose of this study is to estimate long-term SMC and find its relation with soil moisture (SM) of climate station in different depths and NDVI for the growing season. The study area is located in agricultural regions in the North of Mongolia. The Pearson's correlation methodology was used in this study. We used MODIS and SPOT satellite data and 14 years data for precipitation, temperature and SMC of 38 climate stations. The estimated SMC from this methodology were compared with SM from climate data and NDVI. The estimated SMC was compared with SM of climate stations at a 10-cm depth (r(2) = 0.58) and at a 50-cm depth (r(2) = 0.38), respectively. From the analysis, it can be seen that the previous month's SMC affects vegetation growth of the following month, especially from May to August. The methodology can be an advantageous indicator for taking further environmental analysis in the region.
Keywords
PET, soil moisture content, climate station, NDVI, Mongolia

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Citation

Please use this url to cite or link to this publication:

MLA
Natsagdorj, Enkhjargal, et al. “Long-Term Soil Moisture Content Estimation Using Satellite and Climate Data in Agricultural Area of Mongolia.” GEOCARTO INTERNATIONAL, vol. 34, no. 7, 2019, pp. 722–34.
APA
Natsagdorj, E., Renchin, T., De Maeyer, P., Dari, C., & Tseveen, B. (2019). Long-term soil moisture content estimation using satellite and climate data in agricultural area of Mongolia. GEOCARTO INTERNATIONAL, 34(7), 722–734.
Chicago author-date
Natsagdorj, Enkhjargal, Tsolmon Renchin, Philippe De Maeyer, Chimgee Dari, and Batchuluun Tseveen. 2019. “Long-Term Soil Moisture Content Estimation Using Satellite and Climate Data in Agricultural Area of Mongolia.” GEOCARTO INTERNATIONAL 34 (7): 722–34.
Chicago author-date (all authors)
Natsagdorj, Enkhjargal, Tsolmon Renchin, Philippe De Maeyer, Chimgee Dari, and Batchuluun Tseveen. 2019. “Long-Term Soil Moisture Content Estimation Using Satellite and Climate Data in Agricultural Area of Mongolia.” GEOCARTO INTERNATIONAL 34 (7): 722–734.
Vancouver
1.
Natsagdorj E, Renchin T, De Maeyer P, Dari C, Tseveen B. Long-term soil moisture content estimation using satellite and climate data in agricultural area of Mongolia. GEOCARTO INTERNATIONAL. 2019;34(7):722–34.
IEEE
[1]
E. Natsagdorj, T. Renchin, P. De Maeyer, C. Dari, and B. Tseveen, “Long-term soil moisture content estimation using satellite and climate data in agricultural area of Mongolia,” GEOCARTO INTERNATIONAL, vol. 34, no. 7, pp. 722–734, 2019.
@article{8636860,
  abstract     = {The purpose of this study is to estimate long-term SMC and find its relation with soil moisture (SM) of climate station in different depths and NDVI for the growing season. The study area is located in agricultural regions in the North of Mongolia. The Pearson's correlation methodology was used in this study. We used MODIS and SPOT satellite data and 14 years data for precipitation, temperature and SMC of 38 climate stations. The estimated SMC from this methodology were compared with SM from climate data and NDVI. The estimated SMC was compared with SM of climate stations at a 10-cm depth (r(2) = 0.58) and at a 50-cm depth (r(2) = 0.38), respectively. From the analysis, it can be seen that the previous month's SMC affects vegetation growth of the following month, especially from May to August. The methodology can be an advantageous indicator for taking further environmental analysis in the region.},
  author       = {Natsagdorj, Enkhjargal and Renchin, Tsolmon and De Maeyer, Philippe and Dari, Chimgee and Tseveen, Batchuluun},
  issn         = {1010-6049},
  journal      = {GEOCARTO INTERNATIONAL},
  keywords     = {PET,soil moisture content,climate station,NDVI,Mongolia},
  language     = {eng},
  number       = {7},
  pages        = {722--734},
  title        = {Long-term soil moisture content estimation using satellite and climate data in agricultural area of Mongolia},
  url          = {http://dx.doi.org/10.1080/10106049.2018.1434686},
  volume       = {34},
  year         = {2019},
}

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