Promoting the recovery of forest management has been identified as a key priority by the Government of Mongolia. The objective of this paper is to define land cover classification and land cover change in Khandgait valley between 2000 and 2019. The study area is located in the North central part of Mongolia in Bulgan province. Landsat satellite images with 30m resolution were applied. For the validation, we used ground truth measurements. Maximum-likelihood method was applied in this study. The output map of land cover classification was analyzed and compared with the ground truth measurements. The results showed an overall accuracy of 86.5% and 89.0% for the 2000 and 2019 images, respectively. Land cover changes were quantitatively presented with the results of accuracy assessments between 2000 and 2019. In the future, we need to improve forest monitoring and analyze forest management using satellite images.

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.

The estimation of forest biomass using satellite data has received increasing attention for several reason in Mongolia. Since forest in Mongolia is decreasing and it is important to estimate forest resources using satellite data. This research aims to apply recently launched Sentinel-1B Synthetic Aperture Radar (SAR) C-band and optical Sentinel-2B satellite data for estimation forest biomass and coverage and develop model for the study area. The study area is small scale forestry area named by Khanbuyan community, Bulgan province is situated in the Northern part of Mongolia. Boreal and montane forest belts of larch is dominated in this area. Sentinel-1B was used for estimation forest biomass and multispectral bands of Sentinel-2B applied for forest classification map. We used regression analysis to develop the model using Sentinel-1B and Sentinel-2B VV and VH polarizations for Sentinel-1B and Normalized Difference Vegetation Index (NDVI) for Sentinel-2B were applied in this research. Ground truth data was collected in July 2016 and September 2016 for forest coverage and biomass measurements. NDVI and backscatter coefficients for polarizations VV and VH of Sentinel-1B 2016 were related to ground truth biomass for modeling. Comparison of the model and ground truth measurements for above ground biomass have a good agreement.