Snow Cover Monitoring Based On Remote Sensing And GIS Technologies In Pastoral Area Of The Northern Xinjiang, China

In general, the northern Xinjiang is one of three major snow distribution regions, andis also an important pastoral area in China. Massive snow accumulation frequently causesdisasters such as frost-bite and death of a large number of grazing animals, and destroytraffic and telecommunication devices. Therefore, monitoring snow-covered extentprecisely plays a significant role in the dynamic studies and preventing of snow disastersin pastoral areas.In this Ph.D. dissertation, an great effort was made to systematically study theMODIS snow mapping algorithm, the MODIS snow cover composite products, the snowdepth model based on passive microwave remote sensing data AMSR-E, and the temporaland spatial variation of snow cover area and snow depth in Northern Xinjiang.The main results may be concluded as follows:1) The snow mapping agreement between MODIS daily snow maps and surfaceobservations is high at 94.6% over the four snow seasons under clear sky conditions. Theomission errors mainly determined by snow depth and land cover types, especially whensnow depth is less than 3 cm, the MODIS snow cover mapping algorithm intends tomisclassify thin and patchy snow as land. The cloud agreement is 95.9%, andapproximately 4.1% cloud is misclassified as snow when the sky view at climate stationswas completely covered by clouds.2) Basically, MOD10A2 products can satisfy snow and related subject researches on alarge spatial scale. However, the sequential composite approach in terms of the timeseries of receiving MODIS data, with a longer composite period and a given compositestarting date, lacks of flexibilities, which is not advantageous to the efficient and effectivemonitoring and estimates for regional snow-caused disasters. In this study, wecomposited a new 2-11 days composite snow products, and the snow classificationaccuracy is between 70～100%, the average accuracy reach to 87.2%.3) A new daily snow cover product was developed through combining MODIS dailysnow cover data and AMSR-E daily snow water equivalent (SWE) data. By takingadvantage of both high spatial resolution of optical data and cloud transparency ofpassive microwave data, the new daily snow cover product greatly complements thedeficiency of MODIS product when cloud cover is present especially for snow coverproduct on a daily basis and effectively improves daily snow detection accuracy. In ourexample, the daily snow agreement of the new product with the in situ measurements at20 stations is 75.4%, which is much higher than the 33.7% of the MODIS daily product in all weather conditions, even a little higher than the 71% of the MODIS 8-day product(cloud cover of～5%). The new snow cover product can better and effectively capturedaily SCA dynamics during the snow seasons, which plays a significant role in reduction,mitigation, and prevention of snow-caused disasters in pastoral areas.4) Through regression analysis of horizontal, vertical polarization brightnesstemperature difference of 18 GHz and 36 GHz band and snow depth value, the snowdepth model was established based on the AMSR-E brightness temperature data innorthern Xinjiang. At the same time, the accuracy of the model was evaluated. The resultsindicated that the remote sensing model is impacted seriously by temperature, snowmelt,rain, wet snow and deep frost layers. And there is a good correlation between snow depth(y) over 2.5 cm and the vertical polarization brightness temperature difference of 18GHzand 36GHz. The equation is SD=0.49(Tb18V-Tb36V)+8.72, and the correlationcoefficient is up to 0.65. However, the accuracy of the model is lower when the surface iscovered by fallow or deep snow. Basically, the model can reflect the trend of snow depthvariation in Northern Xinjiang, but it has a low accuracy, and needs to be improved in thefuture.5) The air temperature and elevation play important roles in the fractional snow coveredarea and the spatial distribution of snow cover differed greatly in varied areas. It showedmore snow accumulation in the mountainous areas than that in the plain areas, and themountainous areas had a longer snow period than the plain area.