MODIS snow products MOD10A1\MYD10A1 provided us a unique chance to investigate snow cover as well as its spatial-temporal variability in response to global changes from regional and global perspectives.By means of MOD...MODIS snow products MOD10A1\MYD10A1 provided us a unique chance to investigate snow cover as well as its spatial-temporal variability in response to global changes from regional and global perspectives.By means of MODIS snow products MOD10A1\MYD10A1 derived from an extensive area of the Amur River Basin,mainly located in the Northeast part of China,some part in far east area of the former USSR and a minor part in Republic of Mongolia,the reproduced snow datasets after removal of cloud effects covering the whole watershed of the Amur River Basin were generated by using 6 different cloud-effect-removing algorithms.The accuracy of the reproduced snow products was evaluated with the time series of snow depth data observed from 2002 to 2010 within the Chinese part of the basin,and the results suggested that the accuracies for the reproduced monthly mean snow depth datasets derived from 6 different cloud-effect-removing algorithms varied from 82%to 96%,the snow classification accuracies(the harmonic mean of Recall and Precision)was higher than 80%,close to the accuracy of the original snow product under clear sky conditions when snow cover was stably accumulated.By using the reproduced snow product dataset with the best validated cloud-effect-removing algorithm newly proposed,spatial-temporal variability of snow coverage fraction(SCF),the date when snow cover started to accumulate(SCS)as well as the date when being melted off(SCM)in the Amur River Basin from 2002 to 2016 were investigated.The results indicated that the SCF characterized the significant spatial heterogeneity tended to be higher towards East and North but lower toward West and South over the Amur River Basin.The inter-annual variations of SCF showed an insignificant increase in general with slight fluctuations in majority part of the basin.Both SCS and SCM tended to be slightly linear varied and the inter-annual differences were obvious.In addition,a clear decreasing trend in snow cover is observed in the region.Trend analysis(at 10%significance level)showed that 71%of areas between 2,000 and 2,380 m a.s.l.experienced a reduction in duration and coverage of annual snow cover.Moreover,a severe snow cover reduction during recent years with sharp fluctuations was investigated.Overall spatial-temporal variability of Both SCS and SCM tended to coincide with that of SCF over the basin in general.展开更多
The main part of the Amur River basin(over 90%) belongs to the Russian Far East and Northeastern China.Forests and agricultural lands,covering more than 70%of considered watershed,in the 20th century played a role of ...The main part of the Amur River basin(over 90%) belongs to the Russian Far East and Northeastern China.Forests and agricultural lands,covering more than 70%of considered watershed,in the 20th century played a role of important resources base for both regional economic development and growth of national economies.Present-day and future environmental conditions of adjoining regions of Russia展开更多
基金This research was funded by the National Key Research and Development Program of China(Grant No.2016YFA0602302).
文摘MODIS snow products MOD10A1\MYD10A1 provided us a unique chance to investigate snow cover as well as its spatial-temporal variability in response to global changes from regional and global perspectives.By means of MODIS snow products MOD10A1\MYD10A1 derived from an extensive area of the Amur River Basin,mainly located in the Northeast part of China,some part in far east area of the former USSR and a minor part in Republic of Mongolia,the reproduced snow datasets after removal of cloud effects covering the whole watershed of the Amur River Basin were generated by using 6 different cloud-effect-removing algorithms.The accuracy of the reproduced snow products was evaluated with the time series of snow depth data observed from 2002 to 2010 within the Chinese part of the basin,and the results suggested that the accuracies for the reproduced monthly mean snow depth datasets derived from 6 different cloud-effect-removing algorithms varied from 82%to 96%,the snow classification accuracies(the harmonic mean of Recall and Precision)was higher than 80%,close to the accuracy of the original snow product under clear sky conditions when snow cover was stably accumulated.By using the reproduced snow product dataset with the best validated cloud-effect-removing algorithm newly proposed,spatial-temporal variability of snow coverage fraction(SCF),the date when snow cover started to accumulate(SCS)as well as the date when being melted off(SCM)in the Amur River Basin from 2002 to 2016 were investigated.The results indicated that the SCF characterized the significant spatial heterogeneity tended to be higher towards East and North but lower toward West and South over the Amur River Basin.The inter-annual variations of SCF showed an insignificant increase in general with slight fluctuations in majority part of the basin.Both SCS and SCM tended to be slightly linear varied and the inter-annual differences were obvious.In addition,a clear decreasing trend in snow cover is observed in the region.Trend analysis(at 10%significance level)showed that 71%of areas between 2,000 and 2,380 m a.s.l.experienced a reduction in duration and coverage of annual snow cover.Moreover,a severe snow cover reduction during recent years with sharp fluctuations was investigated.Overall spatial-temporal variability of Both SCS and SCM tended to coincide with that of SCF over the basin in general.
文摘The main part of the Amur River basin(over 90%) belongs to the Russian Far East and Northeastern China.Forests and agricultural lands,covering more than 70%of considered watershed,in the 20th century played a role of important resources base for both regional economic development and growth of national economies.Present-day and future environmental conditions of adjoining regions of Russia
