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您的检索式：作者名="Renchin Tsolmon"
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| 1 | Tracking desertification on the Mongolian steppe through NDVI and field-survey data显示文摘Changing environmental and socio-economic conditions make land degradation,a major concern in Central and East Asia.Globally satellite imagery,particularly Normalized Difference Vegetation Index(NDVI)data,has proved an effective tool for monitoring land cover change.This study examines 33 grassland water points using vegetation field studies and remote sensing techniques to track desertification on the Mongolian plateau.Findings established a significant correlation between same-year field observation(line transects)and NDVI data,enabling an historical land cover perspective to be developed from 1998 to 2006.Results show variable land cover patterns in Mongolia with a 16%decrease in plant density over the time period.Decline in cover identified by NDVI suggests degradation;however,continued annual fluctuation indicates desertificationirreversible land cover changehas not occurred.Further,in situ data documenting greater cover near water points implies livestock overgrazing is not causing degradation at water sources.In combination of the two research methodsremote sensing and field surveysstrengthen findings and provide an effective way to track desertification in dryland regions. | Troy Sternberg Renchin Tsolmon Nicholas Middleton David Thomas | 2011 | International Journal of Digital Earth2011，4，1： | 11 |
| 2 | An integrated methodology for soil moisture analysis using multispectral data in Mongolia显示文摘Soil moisture(SM)content is one of the most important environmental variables in relation to land surface climatology,hydrology,and ecology.Long-term SM data-sets on a regional scale provide reasonable information about climate change and global warming specific regions.The aim of this research work is to develop an integrated methodology for SM of kastanozems soils using multispectral satellite data.The study area is Tuv(48°40′30″N and 106°15′55″E)province in the forest steppe zones in Mongolia.In addition to this,land surface temperature(LST)and normalized difference vegetation index(NDVI)from Landsat satellite images were integrated for the assessment.Furthermore,we used a digital elevation model(DEM)from ASTER satellite image with 30-m resolution.Aspect and slope maps were derived from this DEM.The soil moisture index(SMI)was obtained using spectral information from Landsat satellite data.We used regression analysis to develop the model.The model shows how SMI from satellite depends on LST,NDVI,DEM,Slope,and Aspect in the agricultural area.The results of the model were correlated with the ground SM data in Tuv province.The results indicate that there is a good agreement between output SM and SM of ground truth for agricultural area.Further research is focused on moisture mapping for different natural zones in Mongolia.The innovative part of this research is to estimate SM using drivers which are vegetation,land surface temperature,elevation,aspect,and slope in the forested steppe area.This integrative methodology can be applied for different regions with forest and desert steppe zones. | Enkhjargal Natsagdorj Tsolmon Renchin Martin Kappas Batchuluun Tseveen Chimgee Dari Oyunbileg Tsend Ulam-Orgikh Duger | 2017 | Geo-Spatial Information Science2017，20，1： | 2 |
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