The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLIII-B4-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2022, 621–626, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B4-2022-621-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2022, 621–626, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B4-2022-621-2022
 
02 Jun 2022
02 Jun 2022

CHANGES OF SAND DUNE DISTRIBUTION – A CASE STUDY IKH NUURUUDYN KHOTGOR OF MONGOLIA

D. Ganbat1,2, Y. Bao2, S. Dalantai1,3, B. Natsagdorj1, N. Tseren1, T. Batsaikhan1,2, U. Mandakh1, and S. Bayarsaikhan3 D. Ganbat et al.
  • 1Institute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar 15170, Mongolia
  • 2College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China
  • 3Department of Geography, School of Arts and Sciences, National University of Mongolia, Ulaanbaatar 14201, Mongolia

Keywords: Sand, Desertification, Change detection, Classification, Landsat image, Distribution

Abstract. Ikh Nuuruudyn khotgor in western Mongolia which is characterized by large vertical extend of the sand and area with intensity of desertification in Mongolia. Therefore, it is required to do scientific basis of preservation and usage after examining sand shifting, type, extents of sand in this area. The main objective is to detect the dune sand distribution and its movement in study area, including 1) to determine the geographical conditions 2) to mapping dune sand distribution from topographic map and satellite images, 3) to calculate correlation with climate factors. The variations of spatial and time series of the sand distribution area in this area were delineated using Landsat, NOAA, DEM, MODIS data from 1985-1990-1995-2000-2005-2010-2015-2020 and variations of precipitation and temperature is estimated between these periods. Correlation matrix by Pearson’s correlation coefficient (2) and the ordinary least square estimation of regression analysis was applied in this study to analyze time series of field study area. The result of the study showed sand accumulation area as 1457722.3 hectares (12.7% of total study area) and 1889957.9 hectares (16.5% of total study area) in 1985 and 2020 respectively in this area. Compared to 1985, the sandy area increased by 432235.6 ha in 2020. It is increased by 29.07 % as relative variation percent for three decades in study area. The results showed that the sand distribution changes are negatively correlated with NDVI and precipitation as Pearson’s correlation coefficient. Besides, sand distribution changes are linear correlated with temperature between 1985 and 2020 in study area.