The acquisition of spatial-temporal information of frozen soil is fundamental for the study of frozen soil dynamics and its feedback to climate change in cold regions.With advancement of remote sensing and better unde...The acquisition of spatial-temporal information of frozen soil is fundamental for the study of frozen soil dynamics and its feedback to climate change in cold regions.With advancement of remote sensing and better understanding of frozen soil dynamics,discrimination of freeze and thaw status of surface soil based on passive microwave remote sensing and numerical simulation of frozen soil processes under water and heat transfer principles provides valuable means for regional and global frozen soil dynamic monitoring and systematic spatial-temporal responses to global change.However,as an important data source of frozen soil processes,remotely sensed information has not yet been fully utilized in the numerical simulation of frozen soil processes.Although great progress has been made in remote sensing and frozen soil physics,yet few frozen soil research has been done on the application of remotely sensed information in association with the numerical model for frozen soil process studies.In the present study,a distributed numerical model for frozen soil dynamic studies based on coupled water-heat transferring theory in association with remotely sensed frozen soil datasets was developed.In order to reduce the uncertainty of the simulation,the remotely sensed frozen soil information was used to monitor and modify relevant parameters in the process of model simulation.The remotely sensed information and numerically simulated spatial-temporal frozen soil processes were validated by in-situ field observations in cold regions near the town of Naqu on the East-Central Tibetan Plateau.The results suggest that the overall accuracy of the algorithm for discriminating freeze and thaw status of surface soil based on passive microwave remote sensing was more than 95%.These results provided an accurate initial freeze and thaw status of surface soil for coupling and calibrating the numerical model of this study.The numerically simulated frozen soil processes demonstrated good performance of the distributed numerical model based on the coupled water-heat transferring theory.The relatively larger uncertainties of the numerical model were found in alternating periods between freezing and thawing of surface soil.The average accuracy increased by about 5%after integrating remotely sensed information on the surface soil.The simulation accuracy was significantly improved,especially in transition periods between freezing and thawing of the surface soil.展开更多
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
Landslides pose a frequent geological threat,endangering both productivity and the wellbeing of human life and property.In recent years,landslides have received widespread attention in various fields.This article pres...Landslides pose a frequent geological threat,endangering both productivity and the wellbeing of human life and property.In recent years,landslides have received widespread attention in various fields.This article presents a comprehensive review of landslide research in the Qinling Mountains,China.The first part introduces landslide investigation and inventory,which include manual visual interpretation and automatic landslide extraction.The second part discusses the types,characteristics,and temporal-spatial distribution of landslides in the Qinling Mountains.In the third part,the mechanisms and stability analysis of landslides are explored,along with a discussion of the applicability of various simulation methods.The fourth part focuses on significant studies related to landslide evaluation,including susceptibility,hazard,and risk assessment.The fifth part addresses landslide monitoring and early warning systems.Finally,an assessment is made of the current issues and research status concerning landslide studies in the Qinling Mountains,followed by a discussion on future research directions.展开更多
基金This work was supported by the National Key R&D Program of(Grant No.2016YFA0602302).
文摘The acquisition of spatial-temporal information of frozen soil is fundamental for the study of frozen soil dynamics and its feedback to climate change in cold regions.With advancement of remote sensing and better understanding of frozen soil dynamics,discrimination of freeze and thaw status of surface soil based on passive microwave remote sensing and numerical simulation of frozen soil processes under water and heat transfer principles provides valuable means for regional and global frozen soil dynamic monitoring and systematic spatial-temporal responses to global change.However,as an important data source of frozen soil processes,remotely sensed information has not yet been fully utilized in the numerical simulation of frozen soil processes.Although great progress has been made in remote sensing and frozen soil physics,yet few frozen soil research has been done on the application of remotely sensed information in association with the numerical model for frozen soil process studies.In the present study,a distributed numerical model for frozen soil dynamic studies based on coupled water-heat transferring theory in association with remotely sensed frozen soil datasets was developed.In order to reduce the uncertainty of the simulation,the remotely sensed frozen soil information was used to monitor and modify relevant parameters in the process of model simulation.The remotely sensed information and numerically simulated spatial-temporal frozen soil processes were validated by in-situ field observations in cold regions near the town of Naqu on the East-Central Tibetan Plateau.The results suggest that the overall accuracy of the algorithm for discriminating freeze and thaw status of surface soil based on passive microwave remote sensing was more than 95%.These results provided an accurate initial freeze and thaw status of surface soil for coupling and calibrating the numerical model of this study.The numerically simulated frozen soil processes demonstrated good performance of the distributed numerical model based on the coupled water-heat transferring theory.The relatively larger uncertainties of the numerical model were found in alternating periods between freezing and thawing of surface soil.The average accuracy increased by about 5%after integrating remotely sensed information on the surface soil.The simulation accuracy was significantly improved,especially in transition periods between freezing and thawing of the surface soil.
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.
基金supported by the National Natural Science Foundation of China(No.42077259)the National Key Research and Development Program of China(No.2021YFB3901205)。
文摘Landslides pose a frequent geological threat,endangering both productivity and the wellbeing of human life and property.In recent years,landslides have received widespread attention in various fields.This article presents a comprehensive review of landslide research in the Qinling Mountains,China.The first part introduces landslide investigation and inventory,which include manual visual interpretation and automatic landslide extraction.The second part discusses the types,characteristics,and temporal-spatial distribution of landslides in the Qinling Mountains.In the third part,the mechanisms and stability analysis of landslides are explored,along with a discussion of the applicability of various simulation methods.The fourth part focuses on significant studies related to landslide evaluation,including susceptibility,hazard,and risk assessment.The fifth part addresses landslide monitoring and early warning systems.Finally,an assessment is made of the current issues and research status concerning landslide studies in the Qinling Mountains,followed by a discussion on future research directions.