Remote sensing is an important method for rapidly obtaining farmland information. Once meteorological disaster occurs,using the remote sensing technology to extract disaster area of crops and monitor disaster level ha...Remote sensing is an important method for rapidly obtaining farmland information. Once meteorological disaster occurs,using the remote sensing technology to extract disaster area of crops and monitor disaster level has great significance for evaluating disasters and making a timely remedy. This paper elaborated the importance of monitoring agro-meteorological disasters using remote sensing in current special historical period,overviewed remote sensing methods both at home and abroad,analyzed existing problems,made clear major problems to be solved in monitoring agro-meteorological disasters using remote sensing,and discussed the development prospect of the remote sensing technology.展开更多
In recent years, grassland degradation has become one of the most important ecological problems in China under the interwoven influence of environmental and human factors. Based on the analysis of the spatial-temporal...In recent years, grassland degradation has become one of the most important ecological problems in China under the interwoven influence of environmental and human factors. Based on the analysis of the spatial-temporal characteristics and driving factors of grassland degradation and in order to deeply understand the research status of grassland degradation monitoring methods and evaluation index system, this paper mainly investigates the research progress of grassland degradation remote sensing monitoring methods and evaluation indicators. Furthermore, this paper summarizes the more commonly used remote sensing monitoring methods and evaluation methods, analyzes the problems existing in the evaluation indicators of grassland degradation, and points out the research direction of the evaluation indicators in the future. Finally, a comprehensive remote sensing monitoring and evaluation system are established in this paper. Research findings: because of the variety of grassland degradation types and the emergence of remote sensing monitoring and evaluation methods, establishing a comprehensive remote sensing monitoring and evaluation system to classify and summarize the research methods of different grassland degradation can lay a foundation for the development of grassland degradation evaluation and monitoring in the future and provide research ideas. It is the trend of grassland degradation remote sensing research in the future.展开更多
Summer floods occur frequently in many regions of China,affecting economic development and social stability.Remote sensing is a new technique in disaster monitoring.In this study,the Sihu Basin in Hubei Province of Ch...Summer floods occur frequently in many regions of China,affecting economic development and social stability.Remote sensing is a new technique in disaster monitoring.In this study,the Sihu Basin in Hubei Province of China and the Huaibei Plain in Anhui Province of China were selected as the study areas.Thresholds of backscattering coefficients in the decision tree method were calculated with the histogram analysis method,and flood disaster monitoring in the two study areas was conducted with the threshold method using Sentinel-1 satellite images.Through satellite-based flood disaster monitoring,the flooded maps and the areas of expanded water bodies and flooded crops were derived.The satellite-based monitoring maps were derived by comparing the expanded area of images during a flood disaster with that before the disaster.The difference in spatiotemporal distribution of flood disasters in these two regions was analyzed.The results showed that flood disasters in the Sihu Basin occurred frequently in June and July,and flood disasters in the Huaibei Plain mostly occurred in August,with a high interannual vari-ability.Flood disasters in the Sihu Basin were usually widespread,and the affected area was between Changhu and Honghu lakes.The Huaibei Plain was affected by scattered disasters.The annual mean percentages of flooded crop area were 14.91%and 3.74% in the Sihu Basin and Huaibei Plain,respectively.The accuracies of the extracted flooded area in the Sihu Basin in 2016 and 2017 were 96.20% and 95.19%,respectively.展开更多
Environment and Disasters Monitoring Microsatellite Constellation with high spatial resolution,high temporal resolution and high spectral resolution characteristics was put forward by China.HJ-1B satellite,one of the ...Environment and Disasters Monitoring Microsatellite Constellation with high spatial resolution,high temporal resolution and high spectral resolution characteristics was put forward by China.HJ-1B satellite,one of the first two small optical satellites,had a CCD camera and an infrared camera,which would provide an important new data source for snow monitoring.In the present paper,through analyzing the sensor and data characteristics of HJ-1B,we proposed a new infrared normalized difference snow index(INDSI) referring to the traditional normalized difference snow index(NDSI).The accuracy of these two automatic snow recognition methods was estimated based on a supervised classification method.The accuracy of the traditional NDSI method was 97.761 9% while that of the new INDSI method was 98.617 1%.展开更多
基金Supported by Key Application Technological Innovation Project of Agriculturein Shandong Province"Monitoring,Early Warning and Evaluation Technical Research of Corn Floods Based on Remote Sensing Data"Special Fund Project for Informationization(E-government)of Shandong Province"Construction of Agricultural Monitoring through Remote Sensing in Shandong Province"+1 种基金Special Project for Autonomous Innovation of Shandong Province(2012CX90204)Key Sci-tech Innovation Project of Shandong Academy of Agricultural Sciences(2014CXZ09-2)
文摘Remote sensing is an important method for rapidly obtaining farmland information. Once meteorological disaster occurs,using the remote sensing technology to extract disaster area of crops and monitor disaster level has great significance for evaluating disasters and making a timely remedy. This paper elaborated the importance of monitoring agro-meteorological disasters using remote sensing in current special historical period,overviewed remote sensing methods both at home and abroad,analyzed existing problems,made clear major problems to be solved in monitoring agro-meteorological disasters using remote sensing,and discussed the development prospect of the remote sensing technology.
文摘In recent years, grassland degradation has become one of the most important ecological problems in China under the interwoven influence of environmental and human factors. Based on the analysis of the spatial-temporal characteristics and driving factors of grassland degradation and in order to deeply understand the research status of grassland degradation monitoring methods and evaluation index system, this paper mainly investigates the research progress of grassland degradation remote sensing monitoring methods and evaluation indicators. Furthermore, this paper summarizes the more commonly used remote sensing monitoring methods and evaluation methods, analyzes the problems existing in the evaluation indicators of grassland degradation, and points out the research direction of the evaluation indicators in the future. Finally, a comprehensive remote sensing monitoring and evaluation system are established in this paper. Research findings: because of the variety of grassland degradation types and the emergence of remote sensing monitoring and evaluation methods, establishing a comprehensive remote sensing monitoring and evaluation system to classify and summarize the research methods of different grassland degradation can lay a foundation for the development of grassland degradation evaluation and monitoring in the future and provide research ideas. It is the trend of grassland degradation remote sensing research in the future.
基金This work was supported by the National Key Research and Development Program of China(Grants No.2018YFC1508302 and 2018YFC1508301)the Natural Science Foundation of Hubei Province of China(Grant No.2019CFB507).
文摘Summer floods occur frequently in many regions of China,affecting economic development and social stability.Remote sensing is a new technique in disaster monitoring.In this study,the Sihu Basin in Hubei Province of China and the Huaibei Plain in Anhui Province of China were selected as the study areas.Thresholds of backscattering coefficients in the decision tree method were calculated with the histogram analysis method,and flood disaster monitoring in the two study areas was conducted with the threshold method using Sentinel-1 satellite images.Through satellite-based flood disaster monitoring,the flooded maps and the areas of expanded water bodies and flooded crops were derived.The satellite-based monitoring maps were derived by comparing the expanded area of images during a flood disaster with that before the disaster.The difference in spatiotemporal distribution of flood disasters in these two regions was analyzed.The results showed that flood disasters in the Sihu Basin occurred frequently in June and July,and flood disasters in the Huaibei Plain mostly occurred in August,with a high interannual vari-ability.Flood disasters in the Sihu Basin were usually widespread,and the affected area was between Changhu and Honghu lakes.The Huaibei Plain was affected by scattered disasters.The annual mean percentages of flooded crop area were 14.91%and 3.74% in the Sihu Basin and Huaibei Plain,respectively.The accuracies of the extracted flooded area in the Sihu Basin in 2016 and 2017 were 96.20% and 95.19%,respectively.
基金HJ-1 Satellite data Application Research Project(2008A01A1300)National High Technology Research and Development Program(2009AA12Z101)Key Project of Knowledge Innovation Program of Chinese Academy of Sciences(KZCX2-YW-Q03-07)
文摘Environment and Disasters Monitoring Microsatellite Constellation with high spatial resolution,high temporal resolution and high spectral resolution characteristics was put forward by China.HJ-1B satellite,one of the first two small optical satellites,had a CCD camera and an infrared camera,which would provide an important new data source for snow monitoring.In the present paper,through analyzing the sensor and data characteristics of HJ-1B,we proposed a new infrared normalized difference snow index(INDSI) referring to the traditional normalized difference snow index(NDSI).The accuracy of these two automatic snow recognition methods was estimated based on a supervised classification method.The accuracy of the traditional NDSI method was 97.761 9% while that of the new INDSI method was 98.617 1%.
