International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLII-5/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5/W3, 71–76, 2019
https://doi.org/10.5194/isprs-archives-XLII-5-W3-71-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5/W3, 71–76, 2019
https://doi.org/10.5194/isprs-archives-XLII-5-W3-71-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  05 Dec 2019

05 Dec 2019

ESTIMATION OF FOREST COVERAGE IN NORTHERN REGION OF MONGOLIA USING SENTINEL AND LANDSAT DATA

B. Norovsuren1,2,3, T. Renchin1, B. Tseveen2, A. Yangiv4, and T. Altanchimeg1 B. Norovsuren et al.
  • 1NUM-ITC-UNESCO Laboratory for Space Science and Remote Sensing, National University of Mongolia, Ulaanbaatar, Mongolia
  • 2Dept. of Environment and Forest Engineering, National University of Mongolia, Ulaanbaatar, Mongolia
  • 3Laboratory for Geo mineralization, Mongolian National University (MNU), Mongolia
  • 4Environmental Research, Information and Study Centre (ERISC), Mongolia

Keywords: Remote Sensing, Forest Index, Forest Cover, Sentinel, Management

Abstract. This paper aims to apply Forest Index (FI) and to determine forest coverage in the study area. The study area (49° 15ʹ to 49° 10ʹ N and 104° 05ʹ to 104° 15ʹ E) is located in the northern region of Mongolia and consist of mixed forest. Larch forest (86.12%) is dominating in the study area. The Sentinel-2 satellite data for the years 2015–2019 were used in the research. The land surface temperature (LST) was produced from Landsat-8 OL. FI methodology was applied for the Sentinel data in order to estimate larch forest coverage. The output map of forest coverage was compared with ground truth measurements and thematic map. The agreement between FI map and ground measurement was 85%. LST from Landsat and FI from Sentinel were sampled in to same size. The relationship between LST (Landsat-8) and FI (Sentinel-2) was reasonable (R = 0.5). FI index and LST is applicable for different forest type in the region.