Vova, Oyudari, authorKappas, Martin, authorRenchin, Tsolmon, authorDegener, Jan, authorNutag Action and Research Institute, publisher2017-06-192017-06-192015-06Vova, Oyudari, Martin Kappas, Tsolmon Renchin, Jan Degener, 2015. Land Degradation Assessment in Gobi-Altai Province. In (Fernandez-Gimenez ME, Batkhishig B, Fassnacht SR, Wilson D, eds.) Proceedings of Building Resilience of Mongolian Rangelands: A Trans-disciplinary Research Conference, Ulaanbaatar Mongolia, June 9-10, 2015, pp 54-59.9789996297175 (book)http://hdl.handle.net/10217/181731http://dx.doi.org/10.25675/10217/181731Includes bibliographical references.Presented at the Building resilience of Mongolian rangelands: a trans-disciplinary research conference held on June 9-10, 2015 in Ulaanbaatar, Mongolia.Remote Sensing and GIS analyses were embedded to monitor interactions and relationships between land use and land cover changes in the regional ecological space of Gobi-Altai province (Western part of Mongolia). In the last 76 years, Mongolia has experienced a combination of societal and governance system changes in transitioning from the feudal system to socialism and then from the socialist system with centrally planned economy to market. Each of these resulted in changes natural resources use throughout the country. Using GIS processing of data such as climate data (precipitation, air temperature) and vegetation, socio-economic data (livestock numbers, population density) were analyzed. We focused on developing a modeling approach for monitoring land degradation using GIS and Remote Sensing tools by merging climate and quantitative socio-economic data. The Modified Soil Adjusted Vegetation Index (MSAVI) from SPOT/VEGETATION was used to define vegetation cover change for the period from 2000 to 2013. GIS conditional functions were applied for mapping and analyzing climate and socio-economic driving factors, both of which affect land degradation. Conditional functions such as MAP-Algebra from ArcGIS were developed using ground truth data and data from National Administrative Department of Statistics. Remote sensing data were useful diagnostic tools for providing gross impressions on broad-scale spatial heterogeneity, to assist in land degradation monitoring. This paper defines that study area is affected by land degradation caused by climate and socio economic impacts.born digitalproceedings (reports)engCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.socio-economic changeclimate impactbiodiversitygrassland degradationMSAVIText