In the application of persistent scatterer interferometry(PSI),deformation information is extracted from persistent scatterer(PS)points.Thus,the density and position of PS points are critical for PSI.To increase the P...In the application of persistent scatterer interferometry(PSI),deformation information is extracted from persistent scatterer(PS)points.Thus,the density and position of PS points are critical for PSI.To increase the PS density,a time-series InSAR chain termed as"super-resolution persistent scatterer interferometry"(SR-PSI)is proposed.In this study,we investigate certain important properties of SR-PSI.First,we review the main workflow and dataflow of SR-PSI.It is shown that in the implementation of the Capon algorithm,the diagonal loading(DL)approach should be only used when the condition number of the covariance matrix is sufficiently high to reduce the discontinuities between the joint images.We then discuss the density and positioning accuracy of PS when compared with traditional PSI.The theory and experimental results indicate that SR-PSI can increase the PS density in urban areas.However,it is ineffective for the rural areas,which should be an important consideration for the engineering application of SR-PSI.Furthermore,we validate that the positioning accuracy of PS can be improved by SRPSI via simulations.展开更多
The paper addresses range image segmentation, particularly of data recorded by range cameras, such as the Microsoft Kinect and the Mesa Swissranger SR4000. These devices record range images at video frame rates and al...The paper addresses range image segmentation, particularly of data recorded by range cameras, such as the Microsoft Kinect and the Mesa Swissranger SR4000. These devices record range images at video frame rates and allow for acquisition of 3-dimensional measurement sequences that can be used for 3D reconstruction of indoor environments from moving platforms. The role of segmentation is twofold. First the necessary image co-registration can be based on corresponding segments, instead of corresponding point features (which is common practice currently). Secondly, the segments can be used during subsequent object modelling. By realisising that planar regions in disparity images can be modelled as linear functions of the image coordinates, having integer values for both domain and range, the paper introduces a lookup table based implementation of local Hough transform, allowing to obtain good segmentation results at high speeds.展开更多
Federated learning has recently emerged as a privacy-preserving distributed machine learning approach.Federated learning enables collaborative training of multiple clients and entire fleets without sharing the involve...Federated learning has recently emerged as a privacy-preserving distributed machine learning approach.Federated learning enables collaborative training of multiple clients and entire fleets without sharing the involved training datasets.By preserving data privacy,federated learning has the potential to overcome the lack of data sharing in the renewable energy sector which is inhibiting innovation,research and development.Our paper provides an overview of federated learning in renewable energy applications.We discuss federated learning algorithms and survey their applications and case studies in renewable energy generation and consumption.We also evaluate the potential and the challenges associated with federated learning applied in power and energy contexts.Finally,we outline promising future research directions in federated learning for applications in renewable energy.展开更多
The Belt and Road initiative has a significant focus on infrastructure,trade,and economic development across a vast region,and it also provides significant opportunities for sustainable development.The combined pressu...The Belt and Road initiative has a significant focus on infrastructure,trade,and economic development across a vast region,and it also provides significant opportunities for sustainable development.The combined pressure of climate variability,intensified use of resources,and the fragility of ecosystems make it very challenging,however,to achieve future sustainability.To develop the path in a sustainable way,it is important to have a comprehensive understanding of these issues across nations and evaluate them in a scientific and well-informed approach.In this context,the Digital Belt and Road(DBAR)program was initiated as an international venture to share expertise,knowledge,technologies,and data to demonstrate the role of Earth observation science and technology and big Earth data applications to support large-scale development.In this paper,we identify pressing challenges,present the research priorities and foci of the DBAR program,and propose solutions where big Earth data can make significant contributions.This paper calls for further joint actions and collaboration to build a digital silk road in support of sustainable development at national,regional and global levels.展开更多
The region-wide spatial pattern of the drivers of vegetation trends in the African Sahel-Sudano-Guinean region, one of the main drylands of the world, has not been fully investigated. Time-series satellite earth obser...The region-wide spatial pattern of the drivers of vegetation trends in the African Sahel-Sudano-Guinean region, one of the main drylands of the world, has not been fully investigated. Time-series satellite earth observation datasets were used to investigate spatiotemporal patterns of the vegetation greenness changes in the region and then a principal component regression method was applied to identify the region-wide spatial pattern of driving factors. Results find that vegetation greening is widespread in the region, while vegetation browning is more clustered in central West Africa. The dominant drivers of vegetation greenness have a distinct spatial pattern. Climatic factors are the primary drivers, but the impacts of precipitation decrease from north to south, while the impacts of temperature are contrariwise. Coupled with climatic drivers, land cover changes lead to greening trends in the arid zone, especially in the western Sahelian belt. However, the cluster of browning trends in central West Africa can primarily be attributed to the human-induced land cover changes, including an increasing fractional abundance of agriculture. The results highlight the spatial pattern of climatic and anthropic factors driving vegetation greenness changes, which helps natural resources sustainable use and mitigation of climate change and human activities in global dryland ecosystems.展开更多
The High Mountain Asia(HMA)region,ranging from the Hindu Kush and Tien Shan in thewest totheHimalaya inthe southwith an altitude between 2000 and 8844 m,holds the largest reservoir of glaciers and snow outside Earth P...The High Mountain Asia(HMA)region,ranging from the Hindu Kush and Tien Shan in thewest totheHimalaya inthe southwith an altitude between 2000 and 8844 m,holds the largest reservoir of glaciers and snow outside Earth Polar Regions.In the last decades,numerous glaciers and lake areas there have undergone tremendous changes with water redistribution.In order to increase understanding of the pattern of distribution of water resources,and their dynamic changes at the basin scale,a watershed classification based on the water replenishment patterns dataset was constructed.The input dataset are from the Randolph Glacier Inventory V.6.0 and the vector data of rivers and streams.Four datasets were thus obtained:Glacier-fed and Runoff-fed Drainage Area(GRDA),Glacier-fed and Runoff-free Drainage Area(GDA),Glacier-free and Runoff-fed Drainage Area(RDA),and the Glacier-free and Runoff-free Drainage Area(NGRDA),and the numbers of these four types of basins are 87,107,32,and 448 separately.The statistical results show GRDA has the largest surface area,accounting for 82.2%of the total basin area in HMA,mainly in the region of the basin with outflow rivers or streams.Dominated by small basins,the GDA area accounts for the smallest area,only 3.86%and the RDA accounts for 5.62%.For NGRDA,most are with small areas,accounting for 8.32%,and mainly distributes in the closed basin of the Qiangtang Plateau.This dataset provides a fundamental classified data source for research on water resources,climate,ecology,and environment in HMA.The published data are available at https://data.4tu.nl/download/uuid:d07d748f-d10b-4308-9626-199ef05cc9af/and http://www.dx.doi.org/10.11922/sciencedb.923.展开更多
Human activities modulate the impact of environmental forcing in general and of climate in particular.Information on the spatial and temporal patterns of human activities is in high demand,but scarce in sparsely popul...Human activities modulate the impact of environmental forcing in general and of climate in particular.Information on the spatial and temporal patterns of human activities is in high demand,but scarce in sparsely populated and data-poor regions such as Northern Africa.The intensity and spatial distribution of nighttime lights provide useful information on human activities and can be observed by space-borne imaging radiometers.Our study helps to bridge the gap between the DMSP-OLS data available until 2013 and the NPP-VIIRS data available since 2013.The approach to calibrate the OLS data includes three steps:a)inter-calibrate the OLS DN data acquired by different sensors in 1992-2013;b)cali-brate the OLS DN data using VIIRS data in 2013;c)generate syn-thetic OLS radiance data by degrading the VIIRS data in 2013-2020.We generated a)a time series of calibrated OLS nighttime light radiance data(1992-2013);b)mean annual VIIRS radiance on stable lights at the OLS spatial resolution for 2013-2020;c)synthetic OLS radiance data generated using VIIRS radiance data degraded to match the radiometric specifications of OLS for 2013-2020.The evaluation of these data products in 2013 documented their accu-racy and consistency.展开更多
Based on its ability to obtain two-dimensional(2D)high-resolution images in all-time and all-weather conditions,spaceborne synthetic aperture radar(SAR)has become an important remote sensing technique and the study of...Based on its ability to obtain two-dimensional(2D)high-resolution images in all-time and all-weather conditions,spaceborne synthetic aperture radar(SAR)has become an important remote sensing technique and the study of such systems has entered a period of vigorous development.Advanced imaging modes such as radar interferometry,tomography,and multi-static imaging,have been demonstrated.However,current in-orbit spaceborne SARs,which all operate in low Earth orbits,have relatively long revisit times ranging from several days to dozens of days,restricting their temporal sampling rate.Geosynchronous SAR(GEO SAR)is an active research area because it provides significant new capability,especially its much-improved temporal sampling.This paper reviews the research progress of GEO SAR technologies in detail.Two typical orbit schemes are presented,followed by the corresponding key issues,including system design,echo focusing,main disturbance factors,repeat-track interferometry,etc,inherent to these schemes.Both analysis and solution research of the above key issues are described.GEO SAR concepts involving multiple platforms are described,including the GEO SAR constellation,GEO-LEO/airborne/unmanned aerial vehicle bistatic SAR,and formation flying GEO SAR(FF-GEO SAR).Due to the high potential of FF-GEO SAR for three-dimensional(3D)deformation retrieval and coherence-based SAR tomography(TomoSAR),we have recently carried out some research related to FF-GEO SAR.This research,which is also discussed in this paper,includes developing a formation design method and an improved TomoSAR processing algorithm.It is found that GEO SAR will continue to be an active topic in the aspect of data processing and multi-platform concept in the near future.展开更多
基金supported by the National Natural Science Foundation of China(62101284)the State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of Ministry of Natural Resources+4 种基金China Academy of Surveying and Mapping(2021-03-11)the Natural Science Project of Jiangsu Province(21KJB420003)Nanjing University of Posts and Telecommunications Start-up Fund(NY221033,NY220168)the Foundation of Jiangsu Province Shuangchuang Doctor Grant(JSSCBS20210543)Beijing Key Laboratory of Urban Spatial Information Engineering(20210215)。
文摘In the application of persistent scatterer interferometry(PSI),deformation information is extracted from persistent scatterer(PS)points.Thus,the density and position of PS points are critical for PSI.To increase the PS density,a time-series InSAR chain termed as"super-resolution persistent scatterer interferometry"(SR-PSI)is proposed.In this study,we investigate certain important properties of SR-PSI.First,we review the main workflow and dataflow of SR-PSI.It is shown that in the implementation of the Capon algorithm,the diagonal loading(DL)approach should be only used when the condition number of the covariance matrix is sufficiently high to reduce the discontinuities between the joint images.We then discuss the density and positioning accuracy of PS when compared with traditional PSI.The theory and experimental results indicate that SR-PSI can increase the PS density in urban areas.However,it is ineffective for the rural areas,which should be an important consideration for the engineering application of SR-PSI.Furthermore,we validate that the positioning accuracy of PS can be improved by SRPSI via simulations.
文摘The paper addresses range image segmentation, particularly of data recorded by range cameras, such as the Microsoft Kinect and the Mesa Swissranger SR4000. These devices record range images at video frame rates and allow for acquisition of 3-dimensional measurement sequences that can be used for 3D reconstruction of indoor environments from moving platforms. The role of segmentation is twofold. First the necessary image co-registration can be based on corresponding segments, instead of corresponding point features (which is common practice currently). Secondly, the segments can be used during subsequent object modelling. By realisising that planar regions in disparity images can be modelled as linear functions of the image coordinates, having integer values for both domain and range, the paper introduces a lookup table based implementation of local Hough transform, allowing to obtain good segmentation results at high speeds.
基金supported by the Swiss National Science Foundation(Grant No.206342).
文摘Federated learning has recently emerged as a privacy-preserving distributed machine learning approach.Federated learning enables collaborative training of multiple clients and entire fleets without sharing the involved training datasets.By preserving data privacy,federated learning has the potential to overcome the lack of data sharing in the renewable energy sector which is inhibiting innovation,research and development.Our paper provides an overview of federated learning in renewable energy applications.We discuss federated learning algorithms and survey their applications and case studies in renewable energy generation and consumption.We also evaluate the potential and the challenges associated with federated learning applied in power and energy contexts.Finally,we outline promising future research directions in federated learning for applications in renewable energy.
基金the Strategic Priority Research Program of Chinese Academy of Sciences,Project title:CASEarth[XDA19000000]Digital Belt and Road[XDA19030000].
文摘The Belt and Road initiative has a significant focus on infrastructure,trade,and economic development across a vast region,and it also provides significant opportunities for sustainable development.The combined pressure of climate variability,intensified use of resources,and the fragility of ecosystems make it very challenging,however,to achieve future sustainability.To develop the path in a sustainable way,it is important to have a comprehensive understanding of these issues across nations and evaluate them in a scientific and well-informed approach.In this context,the Digital Belt and Road(DBAR)program was initiated as an international venture to share expertise,knowledge,technologies,and data to demonstrate the role of Earth observation science and technology and big Earth data applications to support large-scale development.In this paper,we identify pressing challenges,present the research priorities and foci of the DBAR program,and propose solutions where big Earth data can make significant contributions.This paper calls for further joint actions and collaboration to build a digital silk road in support of sustainable development at national,regional and global levels.
基金the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA19030203)the National Natural Science Foundation of China project(Grant No.41661144022)。
文摘The region-wide spatial pattern of the drivers of vegetation trends in the African Sahel-Sudano-Guinean region, one of the main drylands of the world, has not been fully investigated. Time-series satellite earth observation datasets were used to investigate spatiotemporal patterns of the vegetation greenness changes in the region and then a principal component regression method was applied to identify the region-wide spatial pattern of driving factors. Results find that vegetation greening is widespread in the region, while vegetation browning is more clustered in central West Africa. The dominant drivers of vegetation greenness have a distinct spatial pattern. Climatic factors are the primary drivers, but the impacts of precipitation decrease from north to south, while the impacts of temperature are contrariwise. Coupled with climatic drivers, land cover changes lead to greening trends in the arid zone, especially in the western Sahelian belt. However, the cluster of browning trends in central West Africa can primarily be attributed to the human-induced land cover changes, including an increasing fractional abundance of agriculture. The results highlight the spatial pattern of climatic and anthropic factors driving vegetation greenness changes, which helps natural resources sustainable use and mitigation of climate change and human activities in global dryland ecosystems.
基金This work was implemented in the Key Laboratory of Digital Earth Sciences,Chinese Academy of Sciences,and supported by the Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19070201]the National Key Research and Development Program of China,MARIS Project[2017YFE0111700]the International Cooperation Program of the Chinese Academy of Sciences,[131211KYSB20150035].
文摘The High Mountain Asia(HMA)region,ranging from the Hindu Kush and Tien Shan in thewest totheHimalaya inthe southwith an altitude between 2000 and 8844 m,holds the largest reservoir of glaciers and snow outside Earth Polar Regions.In the last decades,numerous glaciers and lake areas there have undergone tremendous changes with water redistribution.In order to increase understanding of the pattern of distribution of water resources,and their dynamic changes at the basin scale,a watershed classification based on the water replenishment patterns dataset was constructed.The input dataset are from the Randolph Glacier Inventory V.6.0 and the vector data of rivers and streams.Four datasets were thus obtained:Glacier-fed and Runoff-fed Drainage Area(GRDA),Glacier-fed and Runoff-free Drainage Area(GDA),Glacier-free and Runoff-fed Drainage Area(RDA),and the Glacier-free and Runoff-free Drainage Area(NGRDA),and the numbers of these four types of basins are 87,107,32,and 448 separately.The statistical results show GRDA has the largest surface area,accounting for 82.2%of the total basin area in HMA,mainly in the region of the basin with outflow rivers or streams.Dominated by small basins,the GDA area accounts for the smallest area,only 3.86%and the RDA accounts for 5.62%.For NGRDA,most are with small areas,accounting for 8.32%,and mainly distributes in the closed basin of the Qiangtang Plateau.This dataset provides a fundamental classified data source for research on water resources,climate,ecology,and environment in HMA.The published data are available at https://data.4tu.nl/download/uuid:d07d748f-d10b-4308-9626-199ef05cc9af/and http://www.dx.doi.org/10.11922/sciencedb.923.
基金supported by the National Natural Science Foundation of China project(Grant No.41661144022)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA19030203),the Chinese Academy of Sciences President’s International Fellowship Initiative(Grant No.2020VTA0001),and the MOST High-Level Foreign Expert program(Grant No.GL20200161002).
文摘Human activities modulate the impact of environmental forcing in general and of climate in particular.Information on the spatial and temporal patterns of human activities is in high demand,but scarce in sparsely populated and data-poor regions such as Northern Africa.The intensity and spatial distribution of nighttime lights provide useful information on human activities and can be observed by space-borne imaging radiometers.Our study helps to bridge the gap between the DMSP-OLS data available until 2013 and the NPP-VIIRS data available since 2013.The approach to calibrate the OLS data includes three steps:a)inter-calibrate the OLS DN data acquired by different sensors in 1992-2013;b)cali-brate the OLS DN data using VIIRS data in 2013;c)generate syn-thetic OLS radiance data by degrading the VIIRS data in 2013-2020.We generated a)a time series of calibrated OLS nighttime light radiance data(1992-2013);b)mean annual VIIRS radiance on stable lights at the OLS spatial resolution for 2013-2020;c)synthetic OLS radiance data generated using VIIRS radiance data degraded to match the radiometric specifications of OLS for 2013-2020.The evaluation of these data products in 2013 documented their accu-racy and consistency.
基金This work was funded in part by the National Natural Science Foundation of China under Grant Nos.61960206009,61971039,and 61971037the Distinguished Young Scholars of Chongqing(Grant No.cstc2020jcyj-jqX0008)+2 种基金the National Ten Thousand Talents Program‘Young Top Talent’(Grant No.W03070007)the Special Fund for Research on National Major Research Instruments(NSFC Grant Nos.61827901,31727901)the Young Elite Scientists Sponsorship Program by CAST(2017QNRC001).
文摘Based on its ability to obtain two-dimensional(2D)high-resolution images in all-time and all-weather conditions,spaceborne synthetic aperture radar(SAR)has become an important remote sensing technique and the study of such systems has entered a period of vigorous development.Advanced imaging modes such as radar interferometry,tomography,and multi-static imaging,have been demonstrated.However,current in-orbit spaceborne SARs,which all operate in low Earth orbits,have relatively long revisit times ranging from several days to dozens of days,restricting their temporal sampling rate.Geosynchronous SAR(GEO SAR)is an active research area because it provides significant new capability,especially its much-improved temporal sampling.This paper reviews the research progress of GEO SAR technologies in detail.Two typical orbit schemes are presented,followed by the corresponding key issues,including system design,echo focusing,main disturbance factors,repeat-track interferometry,etc,inherent to these schemes.Both analysis and solution research of the above key issues are described.GEO SAR concepts involving multiple platforms are described,including the GEO SAR constellation,GEO-LEO/airborne/unmanned aerial vehicle bistatic SAR,and formation flying GEO SAR(FF-GEO SAR).Due to the high potential of FF-GEO SAR for three-dimensional(3D)deformation retrieval and coherence-based SAR tomography(TomoSAR),we have recently carried out some research related to FF-GEO SAR.This research,which is also discussed in this paper,includes developing a formation design method and an improved TomoSAR processing algorithm.It is found that GEO SAR will continue to be an active topic in the aspect of data processing and multi-platform concept in the near future.
