The detection of glacial lake change in the Himalayas, Nepal is extremely significant since the glacial lake change is one of the crucial indicators of global climate change in this area, where is the most sensitive a...The detection of glacial lake change in the Himalayas, Nepal is extremely significant since the glacial lake change is one of the crucial indicators of global climate change in this area, where is the most sensitive area of the global climate changes. In the Hima- layas, some of glacial lakes are covered by the dark mountains＇ shadow because of their location. Therefore, these lakes can not be de- tected by conventional method such as Normalized Difference Water Index （NDWI）, because the reflectance feature of shadowed glacial lake is different comparing to the ones which are located in the open flat area. The shadow causes two major problems： 1） glacial lakes which are covered by shadow completely result in underestimation of the number of glacial lakes; 2） glacial lakes which are partly iden- tified are considered to undervalue the area of glacial lakes. The aim of this study is to develop a new model, named Detection of Shadowed Glacial Lakes （DSGL） model, to identify glacial lakes under the shadow environment by using Advanced Space-borne Ther- mal Emission and Reflection Radiometer （ASTER） data in the Himalayas, Nepal. The DSGL model is based on integration of two dif- ferent modifications of NDWI, namely NDWls model and NDWIshe model. NDWI~ is defined as integration of the NDWI and slope analysis and used for detecting non-shadowed lake in the mountain area. The NDWIshe is proposed as a new methodology to overcome the weakness of NDWI~ on identifying shadowed lakes in highly elevated mountainous area such as the Himalayas. The first step of the NDWIshe is to enhance the data from ASTER 1B using the histogram equalization （HE） method, and its outcome product is named AS- TERho. We used the ASTERhe for calculating the NDWIhc and the NDWIshe. Integrated with terrain analysis using Digital Elevation Model （DEM） data, the NDWIshe can be used to identify the shadowed glacial lakes in the Himalayas. NDWIs value of 0.41 is used to identify the glacier lake （NDWI~ 〉 0.41）, and 0.3 of NDWIshe is used to identify the shadowed glacier lake （NDWIsho 〈 0.3）. The DSGL model was proved to be able to classify the glacial lakes more accurately, while the NDWI model had tendency to underestimate the presence of actual glacial lakes. Correct classification rate regarding the products from NDWI model and DSGL model were 57% and 99%, respectively. The results of this paper demonstrated that the DSGL model is promising to detect glacial lakes in the shadowed en- vironment at high mountains.展开更多
Temporal and spatial anomalies associated with the Yushu earthquake, including the Outgoing Longwave Radiation( OLR), the Land Surface Temperature( LST) and surface temperature from the National Center for Environment...Temporal and spatial anomalies associated with the Yushu earthquake, including the Outgoing Longwave Radiation( OLR), the Land Surface Temperature( LST) and surface temperature from the National Center for Environmental Prediction( NCEP) are studied using thermal infrared remote sensing data in this paper. All results confirmed the previous observations of thermal anomalies in the seismic region prior to this earthquake.Among the multi-parameter anomalies, the underground water temperature anomaly appeared first and lasted for the longest time; OLR anomaly,an infrared parameter which indicates the radiation characteristics of the land surface medium,was the first to be detected; LST anomalies appeared later than OLR. NCEP temperature indicates the average atmosphere temperature with a certain vertical thickness; therefore,it was the last detected anomaly. The anomalies of OLR and LST lasted for a similar time length and were all located in the south or southwest of the epicenter.展开更多
Based on light-use efficiency model, an MODIS-derived daily net primary production (NPP) model was developed. In this model, a new model for the fraction of photosynthetically active radiation absorbed by vegetation (...Based on light-use efficiency model, an MODIS-derived daily net primary production (NPP) model was developed. In this model, a new model for the fraction of photosynthetically active radiation absorbed by vegetation (FPAR) is developed based on leaf area index (LAI) and albedo parameters, and a pho- tosynthetically active radiation (PAR) is calculated from the combination of Bird's model with aerosol optical thickness and water vapor derived from cloud free MODIS images. These two models are inte- grated into our predicted NPP model, whose most parameters are retrieved from MODIS data. In order to validate our NPP model, the observed NPP in the Qianyanzhou station and the Changbai Mountains station are used to compare with our predicted NPP, showing that they are in good agreement. The NASA NPP products also have been downloaded and compared with the measurements, which shows that the NASA NPP products underestimated NPP in the Qianyanzhou station but overestimated in the Changbai Mountains station in 2004.展开更多
An algorithm of hyperspectral remote sensing images classification is proposed based on the frequency spectrum of spectral signature.The spectral signature of each pixel in the hyperspectral image is taken as a discre...An algorithm of hyperspectral remote sensing images classification is proposed based on the frequency spectrum of spectral signature.The spectral signature of each pixel in the hyperspectral image is taken as a discrete signal,and the frequency spectrum is obtained using discrete Fourier transform.The discrepancy of frequency spectrum between ground objects' spectral signatures is visible,thus the difference between frequency spectra of reference and target spectral signature is used to measure the spectral similarity.Canberra distance is introduced to increase the contribution from higher frequency components.Then,the number of harmonics involved in the proposed algorithm is determined after analyzing the frequency spectrum energy cumulative distribution function of ground object.In order to evaluate the performance of the proposed algorithm,two hyperspectral remote sensing images are adopted as experimental data.The proposed algorithm is compared with spectral angle mapper (SAM),spectral information divergence (SID) and Euclidean distance (ED) using the product accuracy,user accuracy,overall accuracy,average accuracy and Kappa coefficient.The results show that the proposed algorithm can be applied to hyperspectral image classification effectively.展开更多
The calibration experiment data at Dunhuang radiometric calibration site in October, 2008 were used to achieve the on-orbit radiometric calibration for HJ-1A hyper spectral imager (HSI). Two other field experiments da...The calibration experiment data at Dunhuang radiometric calibration site in October, 2008 were used to achieve the on-orbit radiometric calibration for HJ-1A hyper spectral imager (HSI). Two other field experiments data were used to validate the Dunhuang calibration results. One field experiment took place in Inner-Mongolia, China in September, 2008, and the other field experiment took place in Lake Frome, Australia in February, 2009. Finally, the ‘confidence interval of calibration error’ concept was put forward for quantitatively computing the calibration coefficient error confidence interval. The results showed that the Dunhuang calibration results in 2008 had high reliability. The confidence intervals of calibration error for all HSI channels were between 2% to 12%, which could satisfy the requirement of the HSI quantitative applications.展开更多
Radiometric calibration of sensor is the basis of quantitative remote sensing,and uncertainty analysis is critical to ensure the accuracy of cross-calibration.Therefore,firstly,cross-calibration formulas were improved...Radiometric calibration of sensor is the basis of quantitative remote sensing,and uncertainty analysis is critical to ensure the accuracy of cross-calibration.Therefore,firstly,cross-calibration formulas were improved by redefining calibration coefficient and spectral band matching factor.In these formulas,cci was redefined as the calibration coefficient of normalized apparent reflectance,and spectral band matching factor as the ratio of normalized apparent reflectance.Secondly,based on the contrast of ideal and actual conditions in cross-calibration,8 sources of cross-calibration uncertainty were proposed:calibration uncertainty of standard sensor;pixel matching uncertainty;spectral band matching factor uncertainty caused by site altitude setting error,atmospheric parameters setting error,surface spectrum source,surface bidirectional reflectance characteristic,and error of atmospheric radiative transfer model;and uncertainty caused by other factors which were not considered.Finally,the contribution of each uncertainty was further analyzed and discussed for the HJ-1 CCD camera.The results provide many valuable references for evaluating the feasibility of alternative cross-calibration measurements.展开更多
Modeling and analyzing dynamic changes of land thermal radiance scenes play an important role in thermal remote sensing. In this paper, the diurnal variation of ground surface thermal scene is mainly discussed. Firstl...Modeling and analyzing dynamic changes of land thermal radiance scenes play an important role in thermal remote sensing. In this paper, the diurnal variation of ground surface thermal scene is mainly discussed. Firstly, based on the land surface energy balance equation, the diurnal variation of land surface temperatures （LSTs） over bare land covers were simulated by an analyt- ical thermal model with second harmonic terms, and the diurnal LST variation of vegetation canopy was simulated using the Cupid model. Secondly, normalized difference vegetation index （NDVI）, normalized difference water index （NDWI）, and ratio resident-area index （RRI） were used to evaluate the endmember abundance of four land cover types including vegetation, bare soil, impervious and water area, which were calculated from IKONOS visible and near infrared （VNIR） bands. Finally, the thermal radiance scenes at various times and view angles were modeled based on the linear-energy-mixing hypothesis. The re- suits showed that the simulated daily LST variations for vegetated and bare surfaces are correlated with the measured values with a maximum standard deviation of 2.7℃, that land thermal radiant textures with high-resolution are restored from the lin- ear-energy-mixing method, and that the information abundance of the scene are related to the distribution of land cover, the imaging time, and the view angle.展开更多
基金Under the auspices of Taikichiro Mori Memorial Research Grants of Keio University (No. 19, 2010)Doctoral Students Research Support Program of Keio University (No. 87, 2010)Academic Frontier Fund's 'Integrated Research for Community Strategic Concept by Construction and Management of Digital Asia' by Ministry of Education, Culture, Sports, Science and Technology (MEXT) (No. 04F003, 2004-2008)
文摘The detection of glacial lake change in the Himalayas, Nepal is extremely significant since the glacial lake change is one of the crucial indicators of global climate change in this area, where is the most sensitive area of the global climate changes. In the Hima- layas, some of glacial lakes are covered by the dark mountains＇ shadow because of their location. Therefore, these lakes can not be de- tected by conventional method such as Normalized Difference Water Index （NDWI）, because the reflectance feature of shadowed glacial lake is different comparing to the ones which are located in the open flat area. The shadow causes two major problems： 1） glacial lakes which are covered by shadow completely result in underestimation of the number of glacial lakes; 2） glacial lakes which are partly iden- tified are considered to undervalue the area of glacial lakes. The aim of this study is to develop a new model, named Detection of Shadowed Glacial Lakes （DSGL） model, to identify glacial lakes under the shadow environment by using Advanced Space-borne Ther- mal Emission and Reflection Radiometer （ASTER） data in the Himalayas, Nepal. The DSGL model is based on integration of two dif- ferent modifications of NDWI, namely NDWls model and NDWIshe model. NDWI~ is defined as integration of the NDWI and slope analysis and used for detecting non-shadowed lake in the mountain area. The NDWIshe is proposed as a new methodology to overcome the weakness of NDWI~ on identifying shadowed lakes in highly elevated mountainous area such as the Himalayas. The first step of the NDWIshe is to enhance the data from ASTER 1B using the histogram equalization （HE） method, and its outcome product is named AS- TERho. We used the ASTERhe for calculating the NDWIhc and the NDWIshe. Integrated with terrain analysis using Digital Elevation Model （DEM） data, the NDWIshe can be used to identify the shadowed glacial lakes in the Himalayas. NDWIs value of 0.41 is used to identify the glacier lake （NDWI~ 〉 0.41）, and 0.3 of NDWIshe is used to identify the shadowed glacier lake （NDWIsho 〈 0.3）. The DSGL model was proved to be able to classify the glacial lakes more accurately, while the NDWI model had tendency to underestimate the presence of actual glacial lakes. Correct classification rate regarding the products from NDWI model and DSGL model were 57% and 99%, respectively. The results of this paper demonstrated that the DSGL model is promising to detect glacial lakes in the shadowed en- vironment at high mountains.
基金supported by the project of 2017 Directional Task of Earthquake Tracking of CEA(Grant No.2017010406)the project of Youth Foundation of CENC(Grant No.QNJJ201603)
文摘Temporal and spatial anomalies associated with the Yushu earthquake, including the Outgoing Longwave Radiation( OLR), the Land Surface Temperature( LST) and surface temperature from the National Center for Environmental Prediction( NCEP) are studied using thermal infrared remote sensing data in this paper. All results confirmed the previous observations of thermal anomalies in the seismic region prior to this earthquake.Among the multi-parameter anomalies, the underground water temperature anomaly appeared first and lasted for the longest time; OLR anomaly,an infrared parameter which indicates the radiation characteristics of the land surface medium,was the first to be detected; LST anomalies appeared later than OLR. NCEP temperature indicates the average atmosphere temperature with a certain vertical thickness; therefore,it was the last detected anomaly. The anomalies of OLR and LST lasted for a similar time length and were all located in the south or southwest of the epicenter.
基金the National Basic Research Program of China (Grant No. 2002CB412506)the National Natural Science Foundation of China (Grant No. 40471092)
文摘Based on light-use efficiency model, an MODIS-derived daily net primary production (NPP) model was developed. In this model, a new model for the fraction of photosynthetically active radiation absorbed by vegetation (FPAR) is developed based on leaf area index (LAI) and albedo parameters, and a pho- tosynthetically active radiation (PAR) is calculated from the combination of Bird's model with aerosol optical thickness and water vapor derived from cloud free MODIS images. These two models are inte- grated into our predicted NPP model, whose most parameters are retrieved from MODIS data. In order to validate our NPP model, the observed NPP in the Qianyanzhou station and the Changbai Mountains station are used to compare with our predicted NPP, showing that they are in good agreement. The NASA NPP products also have been downloaded and compared with the measurements, which shows that the NASA NPP products underestimated NPP in the Qianyanzhou station but overestimated in the Changbai Mountains station in 2004.
基金supported by the National Basic Research Program of China ("973" Program) (Grant No. 2010CB950800)International S&T Cooperation Program of China (Grant No. 2010DFA21880)China Postdoctoral Science Foundation (Grant No. 2012M510053)
文摘An algorithm of hyperspectral remote sensing images classification is proposed based on the frequency spectrum of spectral signature.The spectral signature of each pixel in the hyperspectral image is taken as a discrete signal,and the frequency spectrum is obtained using discrete Fourier transform.The discrepancy of frequency spectrum between ground objects' spectral signatures is visible,thus the difference between frequency spectra of reference and target spectral signature is used to measure the spectral similarity.Canberra distance is introduced to increase the contribution from higher frequency components.Then,the number of harmonics involved in the proposed algorithm is determined after analyzing the frequency spectrum energy cumulative distribution function of ground object.In order to evaluate the performance of the proposed algorithm,two hyperspectral remote sensing images are adopted as experimental data.The proposed algorithm is compared with spectral angle mapper (SAM),spectral information divergence (SID) and Euclidean distance (ED) using the product accuracy,user accuracy,overall accuracy,average accuracy and Kappa coefficient.The results show that the proposed algorithm can be applied to hyperspectral image classification effectively.
基金supported by the International Science and Technology Cooperation Program of China (Grant No 2008DFA21540)the Chinese Defence Advance Research Program of Science and Technology (Grant No 07K00100KJ) the National Hi-Tech Research and Development Pro-gram of China ("863" Project)
文摘The calibration experiment data at Dunhuang radiometric calibration site in October, 2008 were used to achieve the on-orbit radiometric calibration for HJ-1A hyper spectral imager (HSI). Two other field experiments data were used to validate the Dunhuang calibration results. One field experiment took place in Inner-Mongolia, China in September, 2008, and the other field experiment took place in Lake Frome, Australia in February, 2009. Finally, the ‘confidence interval of calibration error’ concept was put forward for quantitatively computing the calibration coefficient error confidence interval. The results showed that the Dunhuang calibration results in 2008 had high reliability. The confidence intervals of calibration error for all HSI channels were between 2% to 12%, which could satisfy the requirement of the HSI quantitative applications.
基金supported by the Chinese Defence Advance Research Program of Science and Technology (Grant No. 07K00100KJ)the National High Technology Research and Development Program of China ("863"Project) (Grant No. 2006AA12Z113)+1 种基金the International Science and Technology Cooperation Program of China (Grant No. 2008DFA21540)A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)
文摘Radiometric calibration of sensor is the basis of quantitative remote sensing,and uncertainty analysis is critical to ensure the accuracy of cross-calibration.Therefore,firstly,cross-calibration formulas were improved by redefining calibration coefficient and spectral band matching factor.In these formulas,cci was redefined as the calibration coefficient of normalized apparent reflectance,and spectral band matching factor as the ratio of normalized apparent reflectance.Secondly,based on the contrast of ideal and actual conditions in cross-calibration,8 sources of cross-calibration uncertainty were proposed:calibration uncertainty of standard sensor;pixel matching uncertainty;spectral band matching factor uncertainty caused by site altitude setting error,atmospheric parameters setting error,surface spectrum source,surface bidirectional reflectance characteristic,and error of atmospheric radiative transfer model;and uncertainty caused by other factors which were not considered.Finally,the contribution of each uncertainty was further analyzed and discussed for the HJ-1 CCD camera.The results provide many valuable references for evaluating the feasibility of alternative cross-calibration measurements.
基金supported by the 12th and the 11th Five-Year Plan of Civil Aerospace Technology Advanced Research Projects (Grant Nos.O6K00100KJ,Y1K0030044)the China International Science and Technology Cooperation Program (Grant No. 2010DFA21880)
文摘Modeling and analyzing dynamic changes of land thermal radiance scenes play an important role in thermal remote sensing. In this paper, the diurnal variation of ground surface thermal scene is mainly discussed. Firstly, based on the land surface energy balance equation, the diurnal variation of land surface temperatures （LSTs） over bare land covers were simulated by an analyt- ical thermal model with second harmonic terms, and the diurnal LST variation of vegetation canopy was simulated using the Cupid model. Secondly, normalized difference vegetation index （NDVI）, normalized difference water index （NDWI）, and ratio resident-area index （RRI） were used to evaluate the endmember abundance of four land cover types including vegetation, bare soil, impervious and water area, which were calculated from IKONOS visible and near infrared （VNIR） bands. Finally, the thermal radiance scenes at various times and view angles were modeled based on the linear-energy-mixing hypothesis. The re- suits showed that the simulated daily LST variations for vegetated and bare surfaces are correlated with the measured values with a maximum standard deviation of 2.7℃, that land thermal radiant textures with high-resolution are restored from the lin- ear-energy-mixing method, and that the information abundance of the scene are related to the distribution of land cover, the imaging time, and the view angle.
