Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Enkhmanlai Amarsaikhan"'
Publikováno v:
Geocarto International, Vol 39, Iss 1 (2024)
The aim of this study is to compare the performances of different machine learning and parametric techniques for differentiating highly mixed urban land cover classes in Ulaanbaatar, the capital city of Mongolia, using multisource data sets. For data
Externí odkaz:
https://doaj.org/article/fecba6b7f8d54b75a326cc921afe2d44
Autor:
Enkhmanlai Amarsaikhan, Nyamjargal Erdenebaatar, Damdinsuren Amarsaikhan, Munkhdulam Otgonbayar, Batbileg Bayaraa
Publikováno v:
Geocarto International, Vol 38, Iss 1 (2023)
Mongolian pasture plays an essential role in the national economy. Reliable pasture biomass estimation is indispensable to support the agricultural sector and also sustainable livelihood in the country. The aim of this study is to determine an approp
Externí odkaz:
https://doaj.org/article/048e82c93f8d4f9591a8f6ab4bc73b21
Publikováno v:
Geocarto International; Jun2024, Vol. 39 Issue 1, p1-28, 28p
Autor:
Damdinsuren, Amarsaikhan, Amarsaikhan, Enkhmanlai, Gurjav, Tsogzol, Altangerel, Munkh-Erdene, Enkhtuya, Jargaldalai, Damdinsuren, Enkhjargal, Tsedev, Bat-Erdene, Batdorj, Byambadolgor
Publikováno v:
Journal of Institute of Mathematics & Digital Technology (JIMDT); 2023, Vol. 5 Issue 1, p40-49, 10p
Autor:
Amarsaikhan, Enkhmanlai, Erdenebaatar, Nyamjargal, Amarsaikhan, Damdinsuren, Otgonbayar, Munkhdulam, Bayaraa, Batbileg
Publikováno v:
Geocarto International; 2023, Vol. 38 Issue 1, p1-17, 17p