Open AccessLand cover classification using maximum likelihood method (2000 and 2019) at Khandgait valley in Mongolia
Author(s) -
Bayanmunkh Norovsuren,
Batchuluun Tseveen,
В. С. Батомункуев,
Tsolmon Renchin,
Enkhjargal Natsagdorj,
A. Yangiv,
Zaya Mart
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/381/1/012054
Subject(s) - land cover , ground truth , cover (algebra) , remote sensing , satellite imagery , environmental science , satellite , forest cover , land use , geography , physical geography , computer science , artificial intelligence , ecology , mechanical engineering , aerospace engineering , engineering , biology
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.