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1、 后結(jié)果進(jìn)行精度驗(yàn)證。結(jié)果表明,MODIS 每日無(wú)云積雪產(chǎn)品總分類精度較高,為94.7%。考慮到光學(xué)遙感對(duì)薄雪的探測(cè)精度本身較差,若去掉雪深<=3cm 的樣本,總分類精度達(dá) 96.6%。用戶開發(fā)的“青藏高原 MODIS 逐日無(wú)云積雪面積”分類算法可用于研究區(qū)無(wú)云積雪產(chǎn)品的獲取。 3.基于 MODIS 無(wú)云積雪產(chǎn)品長(zhǎng)時(shí)間序列分析。 采用用戶開發(fā)的 MODIS 無(wú)云積雪圖像合成算法, 批量生產(chǎn)青藏高原 2002-2015 年的無(wú)云積雪
2、產(chǎn)品。 對(duì) 10 余年的 MODIS無(wú)云積雪圖像進(jìn)行分析計(jì)算,包括各像素每年的積雪覆蓋日數(shù)、積雪開始時(shí)間和結(jié)束時(shí)間,總結(jié)長(zhǎng)時(shí)間以來(lái)積雪的時(shí)空分布規(guī)律和變化,預(yù)測(cè)未來(lái)積雪的變化趨勢(shì)以及對(duì)氣候環(huán)境的影響。分析結(jié)果表明:十余年來(lái),永久積雪大致呈減少趨勢(shì),永久陸地呈上升趨勢(shì),未來(lái)將繼續(xù)按照這個(gè)趨勢(shì)變化,這與全球變暖有著直接關(guān)系。 關(guān)鍵詞 :青藏高原,MODIS,積雪,去云,精度驗(yàn)證,長(zhǎng)時(shí)間序列分析 研究類型:應(yīng)用研究 reliability
3、is poor .Method based on the spatial combination of neighboring pixels removes scattered cloud with a high accuracy rate of 95.5%, but removed less cloud.The approach based on elevation applies in mountain area.While in
4、the hinterland of the plateau,error of classification is larger due to the smaller slope.Algorithm combined with passive microwave remote sensing data for cloud removing depends on the its recognition rate on cloud, ofte
5、n has a larger error.Method based on mathematics has a weak physical meaning in the Qinghai-Tibet Plateau,where the snow is broken and melts quickly.The methods with high accuracy can be used in the Qinghai-Tibet plateau
6、,including combination of Terra and Aqua satellite images,spatial combination of neighboring pixels and elevation filtering method. 2. An improved algorithm of cloud removal based on MODIS snow cover data.In view of prev
7、ious conventional algorithm,and considering snow and mountain terrain features,8 steps are used to remove all the cloud.Then, daily insitu measurement of snow depth data at 176 meteorological stations in two snow seasons
8、 of 2009 to 2011 were collected to verify the accuracy of each steps and the final results.The results indicates that, MODIS cloudless snow products prove a high overall classification accuracy of 94.7%. Considering that
9、 the accuracy of optical remote sensing is poor in detecting thin snow , if snow samples whose depth is less than 3cm are removed,the general classification accuracy reaches up to 96.6%. The classification algorithm of “
10、MODIS daily cloudless snow products in the Qinghai-Tibet Plateau“ can be used in study area. 3. Long time series analysis based on MODIS daily cloudless snow data.Using the cloud removal algorithm above,we produce cloudl
11、ess snow products form 2002 to 2015 of the Qinghai-Tibet Plateau.Snow parameters for more than 10 years were calculated and analyzed, including snow cover days each year of each pixel , snow start time and end time.Lastl
12、y, paper analyzes the changes of snow during this time,and forecasts the snow trends. The results show that: in the past twelve years,the permanent snow is generally decreasing and the permanent land is rising, the trend
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