Remote sensing images carry crucial ground information,often involving the spatial distribution and spatiotemporal changes of surface elements.To safeguard this sensitive data,image encryption technology is essential....Remote sensing images carry crucial ground information,often involving the spatial distribution and spatiotemporal changes of surface elements.To safeguard this sensitive data,image encryption technology is essential.In this paper,a novel Fibonacci sine exponential map is designed,the hyperchaotic performance of which is particularly suitable for image encryption algorithms.An encryption algorithm tailored for handling the multi-band attributes of remote sensing images is proposed.The algorithm combines a three-dimensional synchronized scrambled diffusion operation with chaos to efficiently encrypt multiple images.Moreover,the keys are processed using an elliptic curve cryptosystem,eliminating the need for an additional channel to transmit the keys,thus enhancing security.Experimental results and algorithm analysis demonstrate that the algorithm offers strong security and high efficiency,making it suitable for remote sensing image encryption tasks.展开更多
The exploration of building detection plays an important role in urban planning,smart city and military.Aiming at the problem of high overlapping ratio of detection frames for dense building detection in high resoluti...The exploration of building detection plays an important role in urban planning,smart city and military.Aiming at the problem of high overlapping ratio of detection frames for dense building detection in high resolution remote sensing images,we present an effective YOLOv3 framework,corner regression-based YOLOv3(Correg-YOLOv3),to localize dense building accurately.This improved YOLOv3 algorithm establishes a vertex regression mechanism and an additional loss item about building vertex offsets relative to the center point of bounding box.By extending output dimensions,the trained model is able to output the rectangular bounding boxes and the building vertices meanwhile.Finally,we evaluate the performance of the Correg-YOLOv3 on our self-produced data set and provide a comparative analysis qualitatively and quantitatively.The experimental results achieve high performance in precision(96.45%),recall rate(95.75%),F1 score(96.10%)and average precision(98.05%),which were 2.73%,5.4%,4.1%and 4.73%higher than that of YOLOv3.Therefore,our proposed algorithm effectively tackles the problem of dense building detection in high resolution images.展开更多
Quantitative analysis and retrieval is given by the State Key Laboratory of Satellite Ocean Environment Dynamics（SOED）,Second Institute of Oceanography（SIO）,State Oceanic Administration（SOA）,China,from the first...Quantitative analysis and retrieval is given by the State Key Laboratory of Satellite Ocean Environment Dynamics（SOED）,Second Institute of Oceanography（SIO）,State Oceanic Administration（SOA）,China,from the first batch of GF-3 synthetic aperture radar（SAR）data with ocean internal wave features in the Yellow Sea.展开更多
Using 3S technology, relying on earth-space three-dimensional agriculture disaster monitoring network, remote sensing monitoring model for agricultural disaster in Henan Province was established, and agricultural disa...Using 3S technology, relying on earth-space three-dimensional agriculture disaster monitoring network, remote sensing monitoring model for agricultural disaster in Henan Province was established, and agricultural disaster monitoring system plat- form of Henan Province based on multi-souroe satellite data was further constructed, which realizes dynamic monitoring of agricultural disasters in Henan Province （drought, flood, snow cover and straw burning）.展开更多
The objective of this study was to retrieve daily composite soil moisture by jointly using brightness temperature observations from multiple operating satellites for near real-time application with better coverage and...The objective of this study was to retrieve daily composite soil moisture by jointly using brightness temperature observations from multiple operating satellites for near real-time application with better coverage and higher accuracy.Our approach was to first apply the single-channel brightness radiometric algorithm to estimate soil moisture from the respective brightness temperature observations of the SMAP,SMOS,AMSR2,FY3B,and FY3C satellites on the same day and then produce a daily composite dataset by averaging the individual satellite-retrieved soil moisture.We further evaluated our product,the official soil moisture products of the five satellites,and the ensemble mean (i.e.,arithmetic mean) of the five official satellite soil moisture products against ground observations from two networks in Central Tibet and Anhui Province,China.The results show that our product outperforms the individual released products of the five satellites and their ensemble means in the two validation areas.The root mean square error (RMSE ) values of our product were 0.06 and 0.09 m3/m3 in Central Tibet and Anhui Province,respectively.Relative to the ensemble mean of the five satellite products,our product improves the accuracy by 9.1% and 57.7% in Central Tibet and Anhui Province,respectively.This demonstrates that jointly using brightness temperature observations from multiple satellites to retrieve soil moisture not only improves the spatial coverage of daily observations but also produces better daily composite products.展开更多
The structural feature shown on a remote sensing image is a synthetic result ofcombination of the deformations produced during the entire geological history of an area.Therefore, the respective tectonic stress field o...The structural feature shown on a remote sensing image is a synthetic result ofcombination of the deformations produced during the entire geological history of an area.Therefore, the respective tectonic stress field of each of the different stages in the complexdeformation of an area can be reconstructed in three steps: (1) geological structures formed atdifferent times are distinguished in remote sensing image interpretation; (2) structuraldeformation fields at different stages are determined by analyzing relationships betweenmicrostructures (joints and fractures) and the related structures (folds and faults); and (3)tectonic stress fields at different stages are respectively recovered through a study of the featuresof structural deformation fields in different periods. Circular structures and related circlular and radial joints are correlated in space to con-cealed structural rises. The authors propose a new method for establishing a natural model ofthe concealed structural rises and calculating the tectonic stress field by using quantitative dataof the remote sensing information of circular structures and related linear structures.展开更多
In this article, the extension to three dimensions (3D) of the blending technique that has been widely used in two dimensions (2D) to calibrate ocean chlorophyll is presented. The results thus obtained revealed a very...In this article, the extension to three dimensions (3D) of the blending technique that has been widely used in two dimensions (2D) to calibrate ocean chlorophyll is presented. The results thus obtained revealed a very high degree of efficiency when predicting observed values of ocean chlorophyll. The mean squared difference between the predicted and observed values of ocean chlorophyll when 3D technique was used fell far below the tolerance level which was set to the difference between satellite and observed in-situ values. The resulting blended field did not only provide better predictions of the in situ observations in areas where bottle samples cannot be obtained but also provided a smooth variation of the distribution of ocean chlorophyll throughout the year. An added advantage is its computational efficiency since data that would have been treated at least four times would be treated only once. With the advent of these results, it is believed that the modelling of the ocean life cycle will become more realistic.展开更多
Atmospheric ammonia(NH_(3)) is a chemically active trace gas that plays an important role in the atmospheric environment and climate change. Satellite remote sensing is a powerful technique to monitor NH_(3) concentra...Atmospheric ammonia(NH_(3)) is a chemically active trace gas that plays an important role in the atmospheric environment and climate change. Satellite remote sensing is a powerful technique to monitor NH_(3) concentration based on the absorption lines of NH_(3) in the thermal infrared region. In this study, we establish a retrieval algorithm to derive the NH_(3)column from the Hyperspectral Infrared Atmospheric Sounder(HIRAS) onboard the Chinese Feng Yun(FY)-3D satellite and present the first atmospheric NH_(3) column global map observed by the HIRAS instrument. The HIRAS observations can well capture NH_(3) hotspots around the world, e.g., India, West Africa, and East China, where large NH_(3) emissions exist. The HIRAS NH_(3) columns are also compared to the space-based Infrared Atmospheric Sounding Interferometer(IASI)measurements, and we find that the two instruments observe a consistent NH_(3) global distribution, with correlation coefficient(R) values of 0.28–0.73. Finally, some remaining issues about the HIRAS NH_(3) retrieval are discussed.展开更多
Residents along the shoreline of the Orashi River have yearly been displaced and recorded loss of lives,farmland,and infrastructures.The Government’s approach has been the provision of relief materials to...Residents along the shoreline of the Orashi River have yearly been displaced and recorded loss of lives,farmland,and infrastructures.The Government’s approach has been the provision of relief materials to the victims instead of implementing adequate control measures.This research employs Shuttle Radar Topographic Mission and Google Earth imagery in developing a 3D floodplain map using ArcGIS software.The result indicates the drainage system in the study area is dendritic with catchment of 79 subbasins and 76 pour point implying the area is floodplain.Incorporating the 3D slope which reveals that>8 and<8 makes up 1.15%and 98.85%of the study area respectively confirms the area is a floodplain.Aspect indicate west-facing slope are dark blue,3D hillshade indicate yellow is very low area and the high area is pink and also the buffer analysis result reveals waterbodies reflecting blue with an estimated area of 1.88 km2,yellow indicate 0.79 km2 of the shoreline,red indicate 0.81 km2 of the minor floodplain and pink contain 0.82 km2 with the length of 32.82 km.The result from google earth image in 2007 indicate absent of settlement,2013 indicate minimal settlement and 2020 indicate major settlement in the study area when correlated with 3D Floodplain mapping before and during the flood in other to analyze and manage flooding for further purpose and the majority of the area are under seize with flood like in 2020.Therefore,Remote Sensing and GIS techniques are useful for Floodplain mapping,risk analysis for control measures for better flood management.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.91948303)。
文摘Remote sensing images carry crucial ground information,often involving the spatial distribution and spatiotemporal changes of surface elements.To safeguard this sensitive data,image encryption technology is essential.In this paper,a novel Fibonacci sine exponential map is designed,the hyperchaotic performance of which is particularly suitable for image encryption algorithms.An encryption algorithm tailored for handling the multi-band attributes of remote sensing images is proposed.The algorithm combines a three-dimensional synchronized scrambled diffusion operation with chaos to efficiently encrypt multiple images.Moreover,the keys are processed using an elliptic curve cryptosystem,eliminating the need for an additional channel to transmit the keys,thus enhancing security.Experimental results and algorithm analysis demonstrate that the algorithm offers strong security and high efficiency,making it suitable for remote sensing image encryption tasks.
基金National Natural Science Foundation of China(No.41871305)National Key Research and Development Program of China(No.2017YFC0602204)+2 种基金Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)(No.CUGQY1945)Open Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education and the Fundamental Research Funds for the Central Universities(No.GLAB2019ZR02)Open Fund of Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Natural Resources,China(No.KF-2020-05-068)。
文摘The exploration of building detection plays an important role in urban planning,smart city and military.Aiming at the problem of high overlapping ratio of detection frames for dense building detection in high resolution remote sensing images,we present an effective YOLOv3 framework,corner regression-based YOLOv3(Correg-YOLOv3),to localize dense building accurately.This improved YOLOv3 algorithm establishes a vertex regression mechanism and an additional loss item about building vertex offsets relative to the center point of bounding box.By extending output dimensions,the trained model is able to output the rectangular bounding boxes and the building vertices meanwhile.Finally,we evaluate the performance of the Correg-YOLOv3 on our self-produced data set and provide a comparative analysis qualitatively and quantitatively.The experimental results achieve high performance in precision(96.45%),recall rate(95.75%),F1 score(96.10%)and average precision(98.05%),which were 2.73%,5.4%,4.1%and 4.73%higher than that of YOLOv3.Therefore,our proposed algorithm effectively tackles the problem of dense building detection in high resolution images.
基金The National Key R&D Program of China under contract No.2016YFC1401007the National Natural Science Foundation of China under contract Nos 41406203 and 41621064the National High Resolution Project of China under contract No.41-Y20A14-9001-15/16
文摘Quantitative analysis and retrieval is given by the State Key Laboratory of Satellite Ocean Environment Dynamics（SOED）,Second Institute of Oceanography（SIO）,State Oceanic Administration（SOA）,China,from the first batch of GF-3 synthetic aperture radar（SAR）data with ocean internal wave features in the Yellow Sea.
基金Supported by Key Scientific and Technological Project of Henan Province(082102140009)~~
文摘Using 3S technology, relying on earth-space three-dimensional agriculture disaster monitoring network, remote sensing monitoring model for agricultural disaster in Henan Province was established, and agricultural disaster monitoring system plat- form of Henan Province based on multi-souroe satellite data was further constructed, which realizes dynamic monitoring of agricultural disasters in Henan Province （drought, flood, snow cover and straw burning）.
基金supported by the National Key Research and Development Program of China(Grant No.2016YFC0402701)the National Natural Science Foundation of China(Grants No.51879067 and 51579131)+4 种基金the Natural Science Foundation of Jiangsu Province(Grant No.BK20180022)the Six Talent Peaks Project in Jiangsu Province(Grant No.NY-004)the Fundamental Research Funds for the Central Universities of China(Grants No.2018842914 and 2018B04714)the China National Flash Flood Disaster Prevention and Control Project(Grant No.126301001000150068)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX18_0572)
文摘The objective of this study was to retrieve daily composite soil moisture by jointly using brightness temperature observations from multiple operating satellites for near real-time application with better coverage and higher accuracy.Our approach was to first apply the single-channel brightness radiometric algorithm to estimate soil moisture from the respective brightness temperature observations of the SMAP,SMOS,AMSR2,FY3B,and FY3C satellites on the same day and then produce a daily composite dataset by averaging the individual satellite-retrieved soil moisture.We further evaluated our product,the official soil moisture products of the five satellites,and the ensemble mean (i.e.,arithmetic mean) of the five official satellite soil moisture products against ground observations from two networks in Central Tibet and Anhui Province,China.The results show that our product outperforms the individual released products of the five satellites and their ensemble means in the two validation areas.The root mean square error (RMSE ) values of our product were 0.06 and 0.09 m3/m3 in Central Tibet and Anhui Province,respectively.Relative to the ensemble mean of the five satellite products,our product improves the accuracy by 9.1% and 57.7% in Central Tibet and Anhui Province,respectively.This demonstrates that jointly using brightness temperature observations from multiple satellites to retrieve soil moisture not only improves the spatial coverage of daily observations but also produces better daily composite products.
基金This study was sponsored by The Open Research Laboratory of Quantitative Prediction,Exploration and Assessment of Mineral Resources,MGMR,China.
文摘The structural feature shown on a remote sensing image is a synthetic result ofcombination of the deformations produced during the entire geological history of an area.Therefore, the respective tectonic stress field of each of the different stages in the complexdeformation of an area can be reconstructed in three steps: (1) geological structures formed atdifferent times are distinguished in remote sensing image interpretation; (2) structuraldeformation fields at different stages are determined by analyzing relationships betweenmicrostructures (joints and fractures) and the related structures (folds and faults); and (3)tectonic stress fields at different stages are respectively recovered through a study of the featuresof structural deformation fields in different periods. Circular structures and related circlular and radial joints are correlated in space to con-cealed structural rises. The authors propose a new method for establishing a natural model ofthe concealed structural rises and calculating the tectonic stress field by using quantitative dataof the remote sensing information of circular structures and related linear structures.
文摘In this article, the extension to three dimensions (3D) of the blending technique that has been widely used in two dimensions (2D) to calibrate ocean chlorophyll is presented. The results thus obtained revealed a very high degree of efficiency when predicting observed values of ocean chlorophyll. The mean squared difference between the predicted and observed values of ocean chlorophyll when 3D technique was used fell far below the tolerance level which was set to the difference between satellite and observed in-situ values. The resulting blended field did not only provide better predictions of the in situ observations in areas where bottle samples cannot be obtained but also provided a smooth variation of the distribution of ocean chlorophyll throughout the year. An added advantage is its computational efficiency since data that would have been treated at least four times would be treated only once. With the advent of these results, it is believed that the modelling of the ocean life cycle will become more realistic.
基金supported by the Feng Yun Application Pioneering Project (FY-APP-2022.0502)the National Natural Science Foundation of China (Grant No. 42205140)。
文摘Atmospheric ammonia(NH_(3)) is a chemically active trace gas that plays an important role in the atmospheric environment and climate change. Satellite remote sensing is a powerful technique to monitor NH_(3) concentration based on the absorption lines of NH_(3) in the thermal infrared region. In this study, we establish a retrieval algorithm to derive the NH_(3)column from the Hyperspectral Infrared Atmospheric Sounder(HIRAS) onboard the Chinese Feng Yun(FY)-3D satellite and present the first atmospheric NH_(3) column global map observed by the HIRAS instrument. The HIRAS observations can well capture NH_(3) hotspots around the world, e.g., India, West Africa, and East China, where large NH_(3) emissions exist. The HIRAS NH_(3) columns are also compared to the space-based Infrared Atmospheric Sounding Interferometer(IASI)measurements, and we find that the two instruments observe a consistent NH_(3) global distribution, with correlation coefficient(R) values of 0.28–0.73. Finally, some remaining issues about the HIRAS NH_(3) retrieval are discussed.
文摘Residents along the shoreline of the Orashi River have yearly been displaced and recorded loss of lives,farmland,and infrastructures.The Government’s approach has been the provision of relief materials to the victims instead of implementing adequate control measures.This research employs Shuttle Radar Topographic Mission and Google Earth imagery in developing a 3D floodplain map using ArcGIS software.The result indicates the drainage system in the study area is dendritic with catchment of 79 subbasins and 76 pour point implying the area is floodplain.Incorporating the 3D slope which reveals that>8 and<8 makes up 1.15%and 98.85%of the study area respectively confirms the area is a floodplain.Aspect indicate west-facing slope are dark blue,3D hillshade indicate yellow is very low area and the high area is pink and also the buffer analysis result reveals waterbodies reflecting blue with an estimated area of 1.88 km2,yellow indicate 0.79 km2 of the shoreline,red indicate 0.81 km2 of the minor floodplain and pink contain 0.82 km2 with the length of 32.82 km.The result from google earth image in 2007 indicate absent of settlement,2013 indicate minimal settlement and 2020 indicate major settlement in the study area when correlated with 3D Floodplain mapping before and during the flood in other to analyze and manage flooding for further purpose and the majority of the area are under seize with flood like in 2020.Therefore,Remote Sensing and GIS techniques are useful for Floodplain mapping,risk analysis for control measures for better flood management.
