Snow Cover Monitoring And Early Warning Of Snow-caused Disaster Based On Remote Sensing And GIS Technologies In Pastoral Areas Of The Tibetan Plateau

Tibetan Plateau (TP) is not only one of the three major snowfall regions, but also an important pastoral area in China. However, because of the undeveloped agriculture infrastructure in the region, heavy snow in winter or spring often causes death of a large number of livestock due to cold weather and forage shortage. This has a great negative influence on the sustainable development of grassland animal husbandry. Therefore, it is extremely important to monitor snow dynamic variation for improving the ability of preventing disaster and maintaining the sustainable development of grassland animal husbandry in pastoral areas.In this study, snow cover mapping algorithm of cloud removal, algorithm improvement of fractional snow cover, comparison and inversion of snow depth, the response of snow to climate change, early warning of snow-caused disaster and risk assessment were analyzed systematically on TP from2003to2010. The results show that:1) This study presents an improved cloud removal algorithm to produce a daily cloud-free snow cover product (MA). The MA composite images not only have the advantages of AMSR-E (i.e., unaffected by weather conditions) and MODIS (i.e., relatively higher resolution), but also the high snow and overall accuracies (i.e.,80.75%and97.52%, respectively), much higher than those of existing daily snow cover products in all sky conditions. Therefore, MA has the ability to accurately monitor the daily snow cover dynamics in the study area, which is extremely important to study snow-caused disasters and offer snow-covered data.2) An improved algorithm of fractional snow cover is presented. Compared with the TM-based snow cover map, the standard error and the mean absolute error of the improved algorithm are reduced from0.35to0.22, and0.25to0.18, respectively. The correlation coefficient is increased from0.74to0.85.3) The snow depth product issued by the Canadian Meteorological Centre is not suitable to monitor snow depth because of higher errors (RMSE=47.70cm) on the different snow depth condition in the TP region. The snow depth data based on the SSM/I and AMSR-E products are able to accurately monitor daily snow depth in the study area.4) The mean annual temperature(MAT), mean annual precipitation(MAP) and snow cover area(SCA) during2003-2010in the TP region have increasing trend, in which the MAT, MAP and SCA increased0.72℃,6.85mm and5.75%, respectively. The annual permanent SCA and snow depth have decreasing trend, in which the annual permanent SCA decreased by the rate of0.35%, and2.80%totally from2003to2010; the average snow depth and snow water equivalant decreased about2.40%and4.16%.5) The snow-covered days(SCD) and snow water equivalent(SWE) have decreasing trend from2003to2010, and the decreasing areas take up35.3%and34.3%of the total area in the TP region respectively. It shows that spatial distribution of temperature and precipitation has correlation relationship with SCD and SWE. About50%of study area shows correlation relationship among SCD, SWE, mean annual temperature and mean annual precipitation. The correlation coefficient is up to0.6on the areas where the elevation is below6300m.6) There are seven crucial factors for early warning of snow disasters on TP. They are mean annual probability of snow disaster, SCD, livestock stocking rate, continual days of mean daily temperature blow-10℃, grassland burial index, rate of snow-covered grassland and per livestock GDP. Based on snow-caused disaster magnitude and snow influence on grazing of livestock, this study develops a model for early warning of snow disasters on county basis and proposes a method of risk assessment of snow disasters at500meter resolution for pastoral areas of TP. We choose411cases from2008to2010to validate the predicting results from the developed early warning model. An overall mean accuracy of85.64%is reached in classifying snow disaster and no disaster.7) On the basis of the existed studies, considering the system structure, data organization and system function design, a management information system for snow monitoring and early warning of snow disasters in the TP region is designed and developed by use of ArcGIS Server and Flex.