China has a vast territory with abundant crops,and how to collect crop information in China timely,objectively and accurately,is of great significance to the scientific guidance of agricultural development.In this pap...China has a vast territory with abundant crops,and how to collect crop information in China timely,objectively and accurately,is of great significance to the scientific guidance of agricultural development.In this paper,by selecting moderateresolution imaging spectroradiometer(MODIS)data as the main information source,on the basis of spectral and biological characteristics mechanism of the crop,and using the freely available advantage of hyperspectral temporal MODIS data,conduct large scale agricultural remote sensing monitoring research,develop applicable model and algorithm,which can achieve large scale remote sensing extraction and yield estimation of major crop type information,and improve the accuracy of crop quantitative remote sensing.Moreover,the present situation of global crop remote sensing monitoring based on MODIS data is analyzed.Meanwhile,the climate and environment grid agriculture information system using large-scale agricultural condition remote sensing monitoring has been attempted preliminary.展开更多
The new Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite image offers a large choice of opportunities for operational applications. The 1-km Advanced Very High Resolution Radiometer (AVHRR) image is not...The new Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite image offers a large choice of opportunities for operational applications. The 1-km Advanced Very High Resolution Radiometer (AVHRR) image is not suitable for retrieval of field level parameter and Landsat data are not frequent enough for monitoring changes in crop parameters during the critical crop growth periods.A methodology to map areas of paddy fields using MODIS,geographic information system (GIS) and global position system (GPS) is introduced in this paper. Training samples are selected and located with the help of GPS to provide maximal accuracy.A concept of assessing areas of potential cultivation of rice is suggested by means of GIS integration. By integration of MODIS with GIS and GPS technologies the actual areas of rice fields in 2002 have been mapped. The classification accuracy was 95.7% percent compared with the statistical data of the Agricultural Bureau of Zhejiang Province.展开更多
The Moderate Resolution Imaging Spectroradiometer(MODIS)surface reflectance data were used to analyze the temporal and spatial distribution characteristics of water clarity(Z_(sd))in the Jiaozhou Bay,Qingdao,China,in ...The Moderate Resolution Imaging Spectroradiometer(MODIS)surface reflectance data were used to analyze the temporal and spatial distribution characteristics of water clarity(Z_(sd))in the Jiaozhou Bay,Qingdao,China,in the Yellow Sea from 2000 to 2018.Z_(sd)retrieval models were regionally optimized using in-situ data with coincident MODIS images,and then were used to retrieve the Z_(sd) products in Jiaozhou Bay from 2000-2018.The analysis of the Z_(sd) results suggests that the spatial distribution of relative Z_(sd) spatial characteristics in Jiaozhou Bay was stable,being higher Z_(sd) in the southeast and a lower Z_(sd) in the northwest.The annual mean Z_(sd) in Jiaozhou Bay showed a significant upward trend,with an annual increase of approximately 0.02 m.Water depth and wind speed were important factors affecting the spatial distribution and annual variation of Z_(sd) in Jiaozhou Bay,respectively.展开更多
Vegetation phenology is an indicator of vegetation response to natural environmental changes and is of great significance for the study of global climate change and its impact on terrestrial ecosystems.The normalized ...Vegetation phenology is an indicator of vegetation response to natural environmental changes and is of great significance for the study of global climate change and its impact on terrestrial ecosystems.The normalized difference vegetation index(NDVI)and enhanced vegetation index(EVI),extracted from the Moderate Resolution Imaging Spectrometer(MODIS),are widely used to monitor phenology by calculating land surface reflectance.However,the applicability of the vegetation index based on‘greenness'to monitor photosynthetic activity is hindered by poor observation conditions(e.g.,ground shadows,snow,and clouds).Recently,satellite measurements of solar-induced chlorophyll fluorescence(SIF)from OCO-2 sensors have shown great potential for studying vegetation phenology.Here,we tested the feasibility of SIF in extracting phenological metrics in permafrost regions of the northeastern China,exploring the characteristics of SIF in the study of vegetation phenology and the differences between NDVI and EVI.The results show that NDVI has obvious SOS advance and EOS lag,and EVI is closer to SIF.The growing season length based on SIF is often the shortest,while it can represent the true phenology of vegetation because it is closely related to photosynthesis.SIF is more sensitive than the traditional remote sensing indices in monitoring seasonal changes in vegetation phenology and can compensate for the shortcomings of traditional vegetation indices.We also used the time series data of MODIS NDVI and EVI to extract phenological metrics in different permafrost regions.The results show that the length of growing season of vegetation in predominantly continuous permafrost(zone I)is longer than in permafrost with isolated taliks(zone II).Our results have certain significance for understanding the response of ecosystems in cold regions to global climate change.展开更多
Heat flux is important for studying interactions between atmosphere and lake.The heat exchange between air-water interfaces is one of the important ways to govern the temperature of the water surface.Heat exchange bet...Heat flux is important for studying interactions between atmosphere and lake.The heat exchange between air-water interfaces is one of the important ways to govern the temperature of the water surface.Heat exchange between the air-water interfaces and the surrounding environment is completed by solar radiation,conduction,and evaporation,and all these processes mainly occur at the air-water interface.Hulun Lake was the biggest lake which is also an important link and an indispensable part of the water cycle in Northeast China.This study mapped surface energy budget to better understand spatial and temporal variations in Hulun Lake in China from 2001 to 2018.Descriptive statistics were computed to build a historical time series of mean monthly heat flux at daytime and nighttime from June to September during 2001–2018.Remote sensing estimation methods we used was suitable for Hulun Lake(R2=0.81).At month scale,shortwave radiation and latent heat flux were decrease from June to September.However,the maximum sensible heat flux appeared in September.Net longwave radiation was the largest in August.The effective heat budget showed that Hulun Lake gained heat in the frost-free season with highest value in June(686.31 W/m2),and then steadily decreased to September(439.76 W/m2).At annual scale,net longwave radiation,sensible heat flux and latent heat flux all show significant growth trend from 2001 to 2018(P<0.01).Wind speed had the well correlation on sensible heat flux and latent heat flux.Water surface temperature showed the highest coefficient in sensitivity analysis.展开更多
文摘China has a vast territory with abundant crops,and how to collect crop information in China timely,objectively and accurately,is of great significance to the scientific guidance of agricultural development.In this paper,by selecting moderateresolution imaging spectroradiometer(MODIS)data as the main information source,on the basis of spectral and biological characteristics mechanism of the crop,and using the freely available advantage of hyperspectral temporal MODIS data,conduct large scale agricultural remote sensing monitoring research,develop applicable model and algorithm,which can achieve large scale remote sensing extraction and yield estimation of major crop type information,and improve the accuracy of crop quantitative remote sensing.Moreover,the present situation of global crop remote sensing monitoring based on MODIS data is analyzed.Meanwhile,the climate and environment grid agriculture information system using large-scale agricultural condition remote sensing monitoring has been attempted preliminary.
文摘The new Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite image offers a large choice of opportunities for operational applications. The 1-km Advanced Very High Resolution Radiometer (AVHRR) image is not suitable for retrieval of field level parameter and Landsat data are not frequent enough for monitoring changes in crop parameters during the critical crop growth periods.A methodology to map areas of paddy fields using MODIS,geographic information system (GIS) and global position system (GPS) is introduced in this paper. Training samples are selected and located with the help of GPS to provide maximal accuracy.A concept of assessing areas of potential cultivation of rice is suggested by means of GIS integration. By integration of MODIS with GIS and GPS technologies the actual areas of rice fields in 2002 have been mapped. The classification accuracy was 95.7% percent compared with the statistical data of the Agricultural Bureau of Zhejiang Province.
基金Supported by the National Key Research and Development Program of China(No.2017YFC0405804)the National Natural Science Foundation of China(Nos.41971318,41701402,41901272)the Science and Technology Service Network Initiative,Chinese Academy of Sciences(No.KFJ-STS-ZDTP-077)。
文摘The Moderate Resolution Imaging Spectroradiometer(MODIS)surface reflectance data were used to analyze the temporal and spatial distribution characteristics of water clarity(Z_(sd))in the Jiaozhou Bay,Qingdao,China,in the Yellow Sea from 2000 to 2018.Z_(sd)retrieval models were regionally optimized using in-situ data with coincident MODIS images,and then were used to retrieve the Z_(sd) products in Jiaozhou Bay from 2000-2018.The analysis of the Z_(sd) results suggests that the spatial distribution of relative Z_(sd) spatial characteristics in Jiaozhou Bay was stable,being higher Z_(sd) in the southeast and a lower Z_(sd) in the northwest.The annual mean Z_(sd) in Jiaozhou Bay showed a significant upward trend,with an annual increase of approximately 0.02 m.Water depth and wind speed were important factors affecting the spatial distribution and annual variation of Z_(sd) in Jiaozhou Bay,respectively.
基金Under the auspices of National Key Research and Development Projects(No.2018YFE0207800)National Natural Science Foundation of China(No.41871103)。
文摘Vegetation phenology is an indicator of vegetation response to natural environmental changes and is of great significance for the study of global climate change and its impact on terrestrial ecosystems.The normalized difference vegetation index(NDVI)and enhanced vegetation index(EVI),extracted from the Moderate Resolution Imaging Spectrometer(MODIS),are widely used to monitor phenology by calculating land surface reflectance.However,the applicability of the vegetation index based on‘greenness'to monitor photosynthetic activity is hindered by poor observation conditions(e.g.,ground shadows,snow,and clouds).Recently,satellite measurements of solar-induced chlorophyll fluorescence(SIF)from OCO-2 sensors have shown great potential for studying vegetation phenology.Here,we tested the feasibility of SIF in extracting phenological metrics in permafrost regions of the northeastern China,exploring the characteristics of SIF in the study of vegetation phenology and the differences between NDVI and EVI.The results show that NDVI has obvious SOS advance and EOS lag,and EVI is closer to SIF.The growing season length based on SIF is often the shortest,while it can represent the true phenology of vegetation because it is closely related to photosynthesis.SIF is more sensitive than the traditional remote sensing indices in monitoring seasonal changes in vegetation phenology and can compensate for the shortcomings of traditional vegetation indices.We also used the time series data of MODIS NDVI and EVI to extract phenological metrics in different permafrost regions.The results show that the length of growing season of vegetation in predominantly continuous permafrost(zone I)is longer than in permafrost with isolated taliks(zone II).Our results have certain significance for understanding the response of ecosystems in cold regions to global climate change.
基金Under the auspices of National Key Research and Development Program of China(No.2016YFA0602301,2016YFB0501502)Strategic Planning Project of the Northeast Institute of Geography and Agroecology(IGA),Chinese Academy of Sciences(No.Y6H2091001)National Forestry Science and Technology Demonstration Promotion Project(No.JLT2018-03)。
文摘Heat flux is important for studying interactions between atmosphere and lake.The heat exchange between air-water interfaces is one of the important ways to govern the temperature of the water surface.Heat exchange between the air-water interfaces and the surrounding environment is completed by solar radiation,conduction,and evaporation,and all these processes mainly occur at the air-water interface.Hulun Lake was the biggest lake which is also an important link and an indispensable part of the water cycle in Northeast China.This study mapped surface energy budget to better understand spatial and temporal variations in Hulun Lake in China from 2001 to 2018.Descriptive statistics were computed to build a historical time series of mean monthly heat flux at daytime and nighttime from June to September during 2001–2018.Remote sensing estimation methods we used was suitable for Hulun Lake(R2=0.81).At month scale,shortwave radiation and latent heat flux were decrease from June to September.However,the maximum sensible heat flux appeared in September.Net longwave radiation was the largest in August.The effective heat budget showed that Hulun Lake gained heat in the frost-free season with highest value in June(686.31 W/m2),and then steadily decreased to September(439.76 W/m2).At annual scale,net longwave radiation,sensible heat flux and latent heat flux all show significant growth trend from 2001 to 2018(P<0.01).Wind speed had the well correlation on sensible heat flux and latent heat flux.Water surface temperature showed the highest coefficient in sensitivity analysis.
