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The purpose of this study is to estimate long-term SMC and find its relation with soil moisture (SM) of climate station in different depths and NDVI for the growing season. The study area is located in agricultural regions in the North of Mongolia. The Pearson’s correlation methodology was used in this study. We used MODIS and SPOT satellite data and 14 years data for precipitation, temperature and SMC of 38 climate stations. The estimated SMC from this methodology were compared with SM from climate data and NDVI. The estimated SMC was compared with SM of climate stations at a 10-cm depth (r2 = 0.58) and at a 50-cm depth (r2 = 0.38), respectively. From the analysis, it can be seen that the previous month’s SMC affects vegetation growth of the following month, especially from May to August. The methodology can be an advantageous indicator for taking further environmental analysis in the region. 相似文献
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After analyzing the mean pressure, dominant wind and temperature data of 40 observation sta-tions in Mongolia from 1961 to 1990, we reach some conclusions as below: (a) The warm advec-tion in the free atmosphere hardly reaches the ground in the west in winter. Because of thermody-namic differences of various meso- and micro-topography, there are "multi-centers" in the pressurefield, and the dominant wind field is "disordered": the temperatures on the convexi-concave orog-raphy and sun-shady slope are different significantly. There is cold advection in the east side,which can reaches the ground and the air pressure field is a "unity". The wind field is dominated bythe west wind. The temperature differences of various slope directions are small, and becomesmaller with height. (b) In summer, the upper control flow (planetary west wind) becomes weak-er, and the orographic air pressure centers in the east develop. Over the windward side of themountain high pressure prevails, and over the lee side low pressure does. These areas becomedeserts for dryness and lack of rainfall. Air temperature in summer can be expressed by latitude,longitude and elevation. 相似文献
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After analyzing the mean pressure, dominant wind and temperature data of 40 observation stations in Mongolia from 1961 to 1990, we reach some conclusions as below: (a) The warm advection in the free atmosphere hardly reaches the ground in the west in winter. Because of thermodynamic differences of various meso- and micro-topography, there are "multi-centers" in the pressure field, and the dominant wind field is "disordered": the temperatures on the convexi-concave orography and sun-shady slope are different significantly. There is cold advection in the east side,which can reaches the ground and the air pressure field is a "unity". The wind field is dominated by the west wind. The temperature differences of various slope directions are small, and become smaller with height. (b) In summer, the upper control flow (planetary west wind) becomes weaker, and the orographic air pressure centers in the east develop. Over the windward side of the mountain high pressure prevails, and over the lee side low pressure does. These areas become deserts for dryness and lack of rainfall. Air temperature in summer can be expressed by latitude,longitude and elevation. 相似文献
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Enkhjargal Natsagdorj Martin Kappas Batchuluun Tseveen Chimgee Dari Oyunbileg Tsend 《地球空间信息科学学报》2017,20(1):46-55
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. 相似文献
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