The recent ten years witnessed the great achievements on rich applications of Geospatial Big Data across a variety of disciplines.For example,a huge number of Landsat images are utilized in mapping high-resolution glo...The recent ten years witnessed the great achievements on rich applications of Geospatial Big Data across a variety of disciplines.For example,a huge number of Landsat images are utilized in mapping high-resolution global forest cover and the global forest changes in the twenty-first century are explored(Hansen et al.2013),which is impossible without the support of geospatial big data and the related automatic processing techniques.Based on the huge enterprise registration data in China,the economic and social development situations and trends are revealed by the non-statistic data and novel approaches(Li et al.2018).City-wide fine-grained urban population distribution at building level is achieved by integrating and fusing multisource geospatial big data(Yao et al.2017),which is usually not desired in traditional research.Geospatial Big Data provides a new transforming paradigm of scientific research especially at the crossroads of broad disciplines,including but not limited to the humanities,the physical sciences,engineering,and so on.展开更多
After the set-up of a spatial data infrastructure(SDI)and a national information infrastructure(NII)in many countries,the provision of geo-services became one of the most important and attractive tasks.With the integr...After the set-up of a spatial data infrastructure(SDI)and a national information infrastructure(NII)in many countries,the provision of geo-services became one of the most important and attractive tasks.With the integration of global positioning system(GPS),geographic information system(GIS)and remote sensing(RS),we can,in principle,answer any geo-spatial related question:when and where what object has which changes?An intelligent geo-service agent could provide end-users with the most necessary information in the shortest time and at the lowest cost.Unfortunately there is still a long way to go to achieve such goals.The central component in such geo-services is the integration of the spatial information system with a computing grid via wire-and wireless communication networks.This paper will mainly discuss the grid technology and its integration with spatial information technology,expounding potential problems and possible resolutions.A novel categorising of information grids in the context of geospatial information is proposed:generalised and specialised spatial information grids.展开更多
This paper is intended to report on the progresses made during the Dragon-4 project Three and Four-Dimensional Topographic Measurement and Validation(ID:32278),sub-project Multi-baseline SAR Processing for 3 D/4 D Rec...This paper is intended to report on the progresses made during the Dragon-4 project Three and Four-Dimensional Topographic Measurement and Validation(ID:32278),sub-project Multi-baseline SAR Processing for 3 D/4 D Reconstruction(ID:322782).The work here reported focuses on two important aspects of SAR remote sensing of tropical forests,namely the retrieval of forest biomass and the assessment of effects due to changing weather conditions.Recent studies have shown that by using SAR tomography the backscattered power at 30 m layer above the ground is linearly correlated to the forest Above Ground Biomass(AGB).However,the two parameters that determine this linear relationship might vary for different tropical forest sites.For purpose of solving this problem,we investigate the possibility of using Li DAR derived AGB to help training the two parameters.Experimental results obtained by processing data from the Tropi SAR campaign support the feasibility of the proposed concept.This analysis is complemented by an assessment of the impact of changing weather conditions on tomographic imaging,for which we simulate BIOMASS repeat pass tomography using ground-based Tropi SCAT data with a revisit time of 3 days and rainy days included.The resulting backscattered power variation at 30 m is within 1.5 d B.For this forest site,this error is translated into an AGB error of about 50~80 t/hm^(2),which is 20%or less of forest AGB.展开更多
Big data have 4V characteristics of volume, variety, velocity, and veracity, which authentically calls for big data analytics. However, what are the dominant characteristics of big data analysis? Here, the analytics i...Big data have 4V characteristics of volume, variety, velocity, and veracity, which authentically calls for big data analytics. However, what are the dominant characteristics of big data analysis? Here, the analytics is related to the entire methodology rather than the individual specific analysis. In this paper, six techniques concerning big data analytics are proposed, which include: (1) Ensemble analysis related to a large volume of data, (2) Association analysis related to unknown data sampling, (3) High-dimensional analysis related to a variety of data, (4) Deep analysis related to the veracity of data, (5) Precision analysis related to the veracity of data, and (6) Divide-and-conquer analysis related to the velocity of data.The essential of big data analytics is the structural analysis of big data in an optimal criterion of physics, computation, and human cognition. fundamentally, two theoretical challenges, ie the violation of independent and identical distribution, and the extension of general set-theory, are posed. In particular, we have illustrated three kinds of association in geographical big data, ie geometrical associations in space and time, spatiotemporal correlations in statistics, and space-time relations in semantics. furthermore, we have illustrated three kinds of spatiotemporal data analysis, ie measurement (observation) adjustment of geometrical quantities, human spatial behavior analysis with trajectories, data assimilation of physical models and various observations, from which spatiotemporal big data analysis may be largely derived.展开更多
A concept of statistical multiresolution analysis in amplitude-frequency domain is proposed, which is to employ the wavelet transform on the statistical character of a signal in amplitude domain. In terms of the theor...A concept of statistical multiresolution analysis in amplitude-frequency domain is proposed, which is to employ the wavelet transform on the statistical character of a signal in amplitude domain. In terms of the theorem of generalized ergodicity, an algorithm to estimate the transform coefficients based on the amplitude statistical multiresolution analysis (AMA) is presented. The principle of applying the AMA to Synthetic Aperture Radar (SAR) image processing is described, and the good experimental results imply that the AMA is an efficient tool for processing of speckled signals modeled by the multiplicative noise.展开更多
Instance segmentation in aerial images is an important and challenging task.Most of the existing methods have adapted instance segmentation algorithms developed for natural images to aerial images.However,these method...Instance segmentation in aerial images is an important and challenging task.Most of the existing methods have adapted instance segmentation algorithms developed for natural images to aerial images.However,these methods easily suffer from performance degradation in aerial images,due to the scale variations,large aspect ratios,and arbitrary orientations of instances caused by the bird’s-eye view of aerial images.To address this issue,we propose an elliptic centerness(EC)for instance segmentation in aerial images,which can assign the proper centerness values to the intricate aerial instances and thus mitigate the performance degradation.Specifically,we introduce ellipses to fit the various contours of aerial instances and measure these fitted ellipses by two-dimensional anisotropic Gaussian distribution.Armed with EC,we develop a one-stage aerial instance segmentation network.Extensive experiments on a commonly used dataset,the instance segmentation in aerial images dataset(iSAID),demonstrate that our proposed method can achieve a remarkable performance of instance segmentation while introducing negligible computational cost.展开更多
A spatial web portal(SWP)provides a web-based gateway to discover,access,manage,and integrate worldwide geospatial resources through the Internet and has the access characteristics of regional to global interest and s...A spatial web portal(SWP)provides a web-based gateway to discover,access,manage,and integrate worldwide geospatial resources through the Internet and has the access characteristics of regional to global interest and spiking.Although various technologies have been adopted to improve SWP performance,enabling high-speed resource access for global users to better support Digital Earth remains challenging because of the computing and communication intensities in the SWP operation and the dynamic distribution of end users.This paper proposes a cloud-enabled framework for high-speed SWP access by leveraging elastic resource pooling,dynamic workload balancing,and global deployment.Experimental results demonstrate that the new SWP framework outperforms the traditional computing infrastructure and better supports users of a global system such as Digital Earth.Reported methodologies and framework can be adopted to support operational geospatial systems,such as monitoring national geographic state and spanning across regional and global geographic extent.展开更多
We explored the potential of the environment and disaster monitoring and forecasting small satellite constellations (HJ-1A/1B satellites) charge-coupled device (CCD) imagery (spatial resolution of 30 m, revisit time o...We explored the potential of the environment and disaster monitoring and forecasting small satellite constellations (HJ-1A/1B satellites) charge-coupled device (CCD) imagery (spatial resolution of 30 m, revisit time of 2 days) in the monitoring of total suspended sediment (TSS) concentrations in dynamic water bodies using Poyang Lake, the largest freshwater lake in China, as an example. Field surveys conducted during October 17-26, 2009 showed a wide range of TSS concentration (3-524 mg/L). Atmospheric correction was implemented using the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) module in ENVI with the aid of aerosol information retrieved from concurrent Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) surveys, which worked well at the CCD bands with relatively high reflectance. A practical exponential retrieval algorithm was created between satellite remote sensing reflectance and in-situ measured TSS concentration. The retrieved results for the whole water area matched the in-situ data well at most stations. The retrieval errors may be related to the problem of scale matching and mixed pixel. In three selected subregions of Poyang Lake, the distribution trend of retrieved TSS was consistent with that of the field investigation. It was shown that HJ-1A/1B CCD imagery can be used to estimate TSS concentrations in Poyang Lake over synoptic scales after applying an appropriate atmospheric correction method and retrieval algorithm.展开更多
Since the twenty-first century,with the rapid development of high-resolution earth observation satellites,the earth observation satellite system has developed from the initial single satellite observation model to the...Since the twenty-first century,with the rapid development of high-resolution earth observation satellites,the earth observation satellite system has developed from the initial single satellite observation model to the current satellite constellation formed by light and small satellites observation model.All-weather and all-directional fine earth observation can now be realized.In the future,the satellite constellation,communication satellites,navigation satellites,and aircrafts are linked through dynamic linking network to form an air-space information network to realize real-time services of intelligent air-space information.To further enhance the perception,cognition,and quick response ability of the network,we propose the concept and model of the Earth Observation Brain(EOB)−the intelligent earth system based on events perception in this paper.Then,some key technologies needed to be solved in the EOB are also described.An application example is illustrated to show the process of perception and cognition in the primary stage of the EOB.In the future,EOB can observe what change of what object,the when and where to push these right information to mobile terminal of right people at the right time and right place.Global users can obtain any data,information,and knowledge in real-time through the EOB.展开更多
Unmanned aerial vehicle(UAV)-based imaging systems have many superiorities compared with other platforms,such as high flexibility and low cost in collecting images,providing wide application prospects.However,the acqu...Unmanned aerial vehicle(UAV)-based imaging systems have many superiorities compared with other platforms,such as high flexibility and low cost in collecting images,providing wide application prospects.However,the acquisition of the UAV-based image commonly results in very high resolution and very large-scale images,which poses great challenges for subsequent applications.Therefore,an efficient representation of large-scale UAV images is necessary for the extraction of the required information in a reasonable time.In this work,we proposed a multi-scale hierarchical representation,i.e.binary partition tree,for analyzing large-scale UAV images.More precisely,we first obtained an initial partition of images by an oversegmentation algorithm,i.e.the simple linear iterative clustering.Next,we merged the similar superpixels to build an object-based hierarchical structure by fully considering the spectral and spatial information of the superpixels and their topological relationships.Moreover,objects of interest and optimal segmentation were obtained using object-based analysis methods with the hierarchical structure.Experimental results on processing the post-seismic UAV images of the 2013 Ya’an earthquake and the mosaic of images in the South-west of Munich demonstrate the effectiveness and efficiency of our proposed method.展开更多
Benggang is a typical fragmented erosional landscape in southern and southeastern China,posing sig-nificant risk to the local residents and economic development.Therefore,an efficient and accurate fine-grained segment...Benggang is a typical fragmented erosional landscape in southern and southeastern China,posing sig-nificant risk to the local residents and economic development.Therefore,an efficient and accurate fine-grained segmentation method is crucial for monitoring the Benggang areas.In this paper,we propose a deep learning-based automatic segmentation method for Benggang by integrating high-resolution Digital Orthophoto Map(DOM)and Digital Surface Model(DSM)data.The DSM data is used to extract slope maps,aiming to capture primary morphological features.The proposed method consists of a dual-stream convolutional encoder-decoder network in which multiple cascaded convolutional layers and a skip connection scheme are used to extract morphological and visual features of the Benggang areas.The rich discriminative information in the DOM and slope data is fused by a channel exchanging mechanism that dynamically exchanges the most discriminative features from either the DOM or DSM stream ac-cording to their importance at the channel level.Evaluation experiments were conducted on a chal-lenging dataset collected from Guangdong Province,China,and the results show that the proposed channel exchanging network based deep fusion method achieves 84.62%IoU in Benggang segmentation,outperforming several existing unimodal or multimodal baselines.The proposed multimodal segmen-tation method greatly improves the efficiency of large-scale discovery of Benggang,and thus is important for the management and restoration of Benggang in southern and southeastern China,as well as the monitoring of other similar erosional landscapes.展开更多
China has experienced unprecedented urbanization in the past decades,resulting in dramatic changes in the physical,limnological,and hydrological characteristics of lakes in urban landscapes.However,the spatiotemporal ...China has experienced unprecedented urbanization in the past decades,resulting in dramatic changes in the physical,limnological,and hydrological characteristics of lakes in urban landscapes.However,the spatiotemporal dynamics in distribution and abundance of urban lakes in China remain poorly understood.Here,we characterized the spatiotemporal change patterns of urban lakes in China’s major cities between 1990 and 2015 using remote-sensing data and landscape metrics.The results showed that the urban lake landscape patterns have experienced drastic changes over the past 25 years.The total surface area of the urban lakes has decreased by 17,620.02 ha,a decrease of 24.22%,with a significant increase in the landscape fragmentation and a reduction in shape complexity.We defined three lake-shrinkage types and found that vanishment was the most common lake-shrinkage pattern,followed by edge-shrinkage and tunneling in terms of lake area.Moreover,we also found that urban sprawl was the dominant driver of the lake shrinkage,accounting for 67.89%of the total area loss,and the transition from lakes to cropland was also an important factor(19.86%).This study has potential for providing critical baseline information for government decision-making in lake resources management and urban landscape design.展开更多
Long-term navigation ability based on consumer-level wearable inertial sensors plays an essential role towards various emerging fields, for instance, smart healthcare, emergency rescue, soldier positioning et al. The ...Long-term navigation ability based on consumer-level wearable inertial sensors plays an essential role towards various emerging fields, for instance, smart healthcare, emergency rescue, soldier positioning et al. The performance of existing long-term navigation algorithm is limited by the cumulative error of inertial sensors, disturbed local magnetic field, and complex motion modes of the pedestrian. This paper develops a robust data and physical model dual-driven based trajectory estimation(DPDD-TE) framework, which can be applied for long-term navigation tasks. A Bi-directional Long Short-Term Memory(Bi-LSTM) based quasi-static magnetic field(QSMF) detection algorithm is developed for extracting useful magnetic observation for heading calibration, and another Bi-LSTM is adopted for walking speed estimation by considering hybrid human motion information under a specific time period. In addition, a data and physical model dual-driven based multi-source fusion model is proposed to integrate basic INS mechanization and multi-level constraint and observations for maintaining accuracy under long-term navigation tasks, and enhanced by the magnetic and trajectory features assisted loop detection algorithm. Real-world experiments indicate that the proposed DPDD-TE outperforms than existing algorithms, and final estimated heading and positioning accuracy indexes reaches 5° and less than 2 m under the time period of 30 min, respectively.展开更多
The indoor positioning system is now an important technique as part of the Internet-of-Things(IoT)ecosystem.Among indoor positioning techniques,multiple Wi-Fi Access Points(APs)-based positioning systems have been res...The indoor positioning system is now an important technique as part of the Internet-of-Things(IoT)ecosystem.Among indoor positioning techniques,multiple Wi-Fi Access Points(APs)-based positioning systems have been researched a lot.There is a lack of research focusing on the scene where only one Wi-Fi AP is available.This work proposes a hybrid indoor positioning system that takes advantage of the Fine-Timing Measurements(FTM)technique that is part of the IEEE 802.11mc standard,introduced back in 2016.The system uses one single Wi-Fi FTM AP and takes advantage of the built-in inertial sensors of the smartphone to estimate the device’s position.We explore both Loosely Coupled(LC)and Tightly Coupled(TC)integration schemes for the sensors’data fusion.Experimental results show that the proposed methods can achieve an average positioning accuracy of about 1 m without knowing the initial position.Compared with the LC integration method,the median error accuracy of the proposed TC fusion algorithm has improved by more than 52%and 67%,respectively,in the two experiments we set up.展开更多
Land surface water mapping is one of the most important remote-sensing applications.However,water areas are spectrally similar and overlapped with shadow,making accurate water extraction from remote-sensing images sti...Land surface water mapping is one of the most important remote-sensing applications.However,water areas are spectrally similar and overlapped with shadow,making accurate water extraction from remote-sensing images still a challenging problem.This paper develops a novel water index named as NDWI-MSI,combining a new normalized difference water index(NDWI)and a recently developed morphological shadow index(MSI),to delineate water bodies from eight-band WorldView-2 imagery.The newly available bands(e.g.coastal,yellow,red-edge,and near-infrared 2)of WorldView-2 imagery provide more potential for constructing new NDWIs derived from various band combinations.Through our testing,a new NDWI is defined in this study.In addition,MSI,a recently developed automatic shadow extraction index from high-resolution imagery can be used to indicate shadow areas.The NDWI-MSI is created by combining NDWI and MSI,which is able to highlight water bodies and simultaneously suppress shadow areas.In experiments,it is shown that the new water index can achieve better performance than traditional NDWI,and even supervised classifiers,for example,maximum likelihood classifier,and support vector machine.展开更多
The paper gives an overview of the current status of education in geoinformatics in China.First,the paper provides a brief introduction to the history of geoinformatics education in China and a general review of the s...The paper gives an overview of the current status of education in geoinformatics in China.First,the paper provides a brief introduction to the history of geoinformatics education in China and a general review of the scientific and technological development.It then presents how the development affects the education and training in China.In the paper,universities and institutes in China that can award academic degrees related to geoinformatics are summarized,and undergraduate majors are briefly introduced.Next,the paper reports the work having been done by the national expert group on Surveying and Mapping,including the revision of discipline catalog and guide for graduate education and requirements.A list of typical curricula in geoinformatics education is suggested.Activities on promoting the graduate student exchange platform are presented.Finally,a case study of geoinformatics education in Wuhan University is discussed.展开更多
Big data is a highlighted challenge for many fields with the rapid expansion of large-volume, complex, and fast-growing sources of data. Mining from big data is required for exploring the essence of data and providing...Big data is a highlighted challenge for many fields with the rapid expansion of large-volume, complex, and fast-growing sources of data. Mining from big data is required for exploring the essence of data and providing meaningful information. To this end, we have previously introduced the theory of physical field to explore relations between objects in data space and proposed a framework of data field to discover the underlying distribution of big data. This paper concerns an overview of big data mining by the use of data field. It mainly discusses the theory of data field and different aspects of applications including feature selection for high-dimensional data, clustering, and the recognition of facial expression in human-computer interaction. In these applications, data field is employed to capture the intrinsic distribution of data objects for selecting meaningful features, fast clustering, and describing variation of facial expression. It is expected that our contributions would help overcome the problems in accordance with big data.展开更多
TerraSAR-X(TSX)can acquire high-resolution SAR images and due to its high orbit precision as well as its ability to acquire data from different off-nadir viewing angles,the high-precision stereo geolocation can be obt...TerraSAR-X(TSX)can acquire high-resolution SAR images and due to its high orbit precision as well as its ability to acquire data from different off-nadir viewing angles,the high-precision stereo geolocation can be obtained.In this study,we investigate the absolute geolocation accuracy of TSX high-resolution images in Wuhan,China.We present a direct stereo SAR geolocation method and analyze the 2D and 3D geoposition accuracy of two corner reflectors.The sub-meter localization accuracy was achieved using only atmospheric correction information available in the TSX metadata.展开更多
Single SAR image direct positioning is to determine the ground coordinate for each pixel in the SAR image assisted with a reference DEM.During this procedure,an iterative procedure is essentially needed to solve the u...Single SAR image direct positioning is to determine the ground coordinate for each pixel in the SAR image assisted with a reference DEM.During this procedure,an iterative procedure is essentially needed to solve the uncertainty in elevation of each pixel in the SAR image.However,such an iterative procedure may suffer from the problem of divergence in shaded and serious layover areas.To investigate this problem,we performed a theoretical analysis on the convergence conditions that has not been intensively studied till now.The Range-Doppler(RD)model was simplified and then the general surface is degenerated into a planar surface.Mathematical deduction was then carried out to derive the convergence conditions and the impact factors for the convergence speed were evaluated.The theoretical findings were validated by experiments for both simulated and real scenarios.展开更多
Specific features of tile access patterns can be applied in a cache replacement strategy to a limited distributed high-speed cache for the cloud-based networked geographic information services(NGISs),aiming to adapt t...Specific features of tile access patterns can be applied in a cache replacement strategy to a limited distributed high-speed cache for the cloud-based networked geographic information services(NGISs),aiming to adapt to changes in the access distribution of hotspots.By taking advantage of the spatiotemporal locality,the sequential features in tile access patterns,and the cache reading performance in the burst mode,this article proposes a tile sequence replacement method,which involves structuring a Least Recently Used(LRU)stack into three portions for the different functions in cache replacement and deriving an expression for the temporal locality and popularity of the relevant tile to facilitate the replacement process.Based on the spatial characteristics of both the tiles and the cache burst mode with regard to reading data,the proposed method generates multiple tile sequences to reflect spatiotemporal locality in tile access patterns.Then,we measure the caching value by a technique based on a weighted-based method.This technique draws on the recent access popularity and low caching costs of tile sequences,with the aim of balancing the temporal and spatial localities in tile access.It ranks tile sequences in a replacement queue to adapt to the changes in accessed hotspots while reducing the replacement frequency.Experimental results show that the proposed method effectively improves the hit rate and utilization rate for a limited distributed cache while achieving satisfactory response performance and high throughput for users in an NGIS.Therefore,it can be adapted to handle numerous data access requests in NGISs in a cloud-based environment.展开更多
文摘The recent ten years witnessed the great achievements on rich applications of Geospatial Big Data across a variety of disciplines.For example,a huge number of Landsat images are utilized in mapping high-resolution global forest cover and the global forest changes in the twenty-first century are explored(Hansen et al.2013),which is impossible without the support of geospatial big data and the related automatic processing techniques.Based on the huge enterprise registration data in China,the economic and social development situations and trends are revealed by the non-statistic data and novel approaches(Li et al.2018).City-wide fine-grained urban population distribution at building level is achieved by integrating and fusing multisource geospatial big data(Yao et al.2017),which is usually not desired in traditional research.Geospatial Big Data provides a new transforming paradigm of scientific research especially at the crossroads of broad disciplines,including but not limited to the humanities,the physical sciences,engineering,and so on.
文摘After the set-up of a spatial data infrastructure(SDI)and a national information infrastructure(NII)in many countries,the provision of geo-services became one of the most important and attractive tasks.With the integration of global positioning system(GPS),geographic information system(GIS)and remote sensing(RS),we can,in principle,answer any geo-spatial related question:when and where what object has which changes?An intelligent geo-service agent could provide end-users with the most necessary information in the shortest time and at the lowest cost.Unfortunately there is still a long way to go to achieve such goals.The central component in such geo-services is the integration of the spatial information system with a computing grid via wire-and wireless communication networks.This paper will mainly discuss the grid technology and its integration with spatial information technology,expounding potential problems and possible resolutions.A novel categorising of information grids in the context of geospatial information is proposed:generalised and specialised spatial information grids.
文摘This paper is intended to report on the progresses made during the Dragon-4 project Three and Four-Dimensional Topographic Measurement and Validation(ID:32278),sub-project Multi-baseline SAR Processing for 3 D/4 D Reconstruction(ID:322782).The work here reported focuses on two important aspects of SAR remote sensing of tropical forests,namely the retrieval of forest biomass and the assessment of effects due to changing weather conditions.Recent studies have shown that by using SAR tomography the backscattered power at 30 m layer above the ground is linearly correlated to the forest Above Ground Biomass(AGB).However,the two parameters that determine this linear relationship might vary for different tropical forest sites.For purpose of solving this problem,we investigate the possibility of using Li DAR derived AGB to help training the two parameters.Experimental results obtained by processing data from the Tropi SAR campaign support the feasibility of the proposed concept.This analysis is complemented by an assessment of the impact of changing weather conditions on tomographic imaging,for which we simulate BIOMASS repeat pass tomography using ground-based Tropi SCAT data with a revisit time of 3 days and rainy days included.The resulting backscattered power variation at 30 m is within 1.5 d B.For this forest site,this error is translated into an AGB error of about 50~80 t/hm^(2),which is 20%or less of forest AGB.
基金This study is supported jointly by the Fundamental Research Funds for the Central Universities, the Key Project of National Natural Science Foundation of China [grant number 41331175, and the LIESMARS Special Research Funding
文摘Big data have 4V characteristics of volume, variety, velocity, and veracity, which authentically calls for big data analytics. However, what are the dominant characteristics of big data analysis? Here, the analytics is related to the entire methodology rather than the individual specific analysis. In this paper, six techniques concerning big data analytics are proposed, which include: (1) Ensemble analysis related to a large volume of data, (2) Association analysis related to unknown data sampling, (3) High-dimensional analysis related to a variety of data, (4) Deep analysis related to the veracity of data, (5) Precision analysis related to the veracity of data, and (6) Divide-and-conquer analysis related to the velocity of data.The essential of big data analytics is the structural analysis of big data in an optimal criterion of physics, computation, and human cognition. fundamentally, two theoretical challenges, ie the violation of independent and identical distribution, and the extension of general set-theory, are posed. In particular, we have illustrated three kinds of association in geographical big data, ie geometrical associations in space and time, spatiotemporal correlations in statistics, and space-time relations in semantics. furthermore, we have illustrated three kinds of spatiotemporal data analysis, ie measurement (observation) adjustment of geometrical quantities, human spatial behavior analysis with trajectories, data assimilation of physical models and various observations, from which spatiotemporal big data analysis may be largely derived.
文摘A concept of statistical multiresolution analysis in amplitude-frequency domain is proposed, which is to employ the wavelet transform on the statistical character of a signal in amplitude domain. In terms of the theorem of generalized ergodicity, an algorithm to estimate the transform coefficients based on the amplitude statistical multiresolution analysis (AMA) is presented. The principle of applying the AMA to Synthetic Aperture Radar (SAR) image processing is described, and the good experimental results imply that the AMA is an efficient tool for processing of speckled signals modeled by the multiplicative noise.
基金This work was supported by the Fundamental Research Funds for the Central Universities(grant number:2042021kf0040).
文摘Instance segmentation in aerial images is an important and challenging task.Most of the existing methods have adapted instance segmentation algorithms developed for natural images to aerial images.However,these methods easily suffer from performance degradation in aerial images,due to the scale variations,large aspect ratios,and arbitrary orientations of instances caused by the bird’s-eye view of aerial images.To address this issue,we propose an elliptic centerness(EC)for instance segmentation in aerial images,which can assign the proper centerness values to the intricate aerial instances and thus mitigate the performance degradation.Specifically,we introduce ellipses to fit the various contours of aerial instances and measure these fitted ellipses by two-dimensional anisotropic Gaussian distribution.Armed with EC,we develop a one-stage aerial instance segmentation network.Extensive experiments on a commonly used dataset,the instance segmentation in aerial images dataset(iSAID),demonstrate that our proposed method can achieve a remarkable performance of instance segmentation while introducing negligible computational cost.
基金Research reported is partially supported by NSF[grant numbers PLR-1349259 and IIP-1338925],FGDC[grant number G13PG00091],and NASA[grant number NNG12PP37I].
文摘A spatial web portal(SWP)provides a web-based gateway to discover,access,manage,and integrate worldwide geospatial resources through the Internet and has the access characteristics of regional to global interest and spiking.Although various technologies have been adopted to improve SWP performance,enabling high-speed resource access for global users to better support Digital Earth remains challenging because of the computing and communication intensities in the SWP operation and the dynamic distribution of end users.This paper proposes a cloud-enabled framework for high-speed SWP access by leveraging elastic resource pooling,dynamic workload balancing,and global deployment.Experimental results demonstrate that the new SWP framework outperforms the traditional computing infrastructure and better supports users of a global system such as Digital Earth.Reported methodologies and framework can be adopted to support operational geospatial systems,such as monitoring national geographic state and spanning across regional and global geographic extent.
基金Supported by the National Basic Research Program of China(973Program)(No.2011CB707106)the National Natural Science Foundation of China(Nos.41071261,41023001,41021061,40906092,40971193,41101415)+3 种基金the Opening Foundation of Institute of Remote Sensing and Earth Sciences,Hangzhou Normal University(No.PDKF2010YG06)the Fundamental Research Funds for the Central Universities,the China Postdoctoral Science Foundation(No.20100480861)LIESMARS Special Research Funding,the Natural Science Foundation of Hubei Province,China(No.2009CDB107)the Natural Science Foundation of Zhejiang Province,China(No.Y5090143)
文摘We explored the potential of the environment and disaster monitoring and forecasting small satellite constellations (HJ-1A/1B satellites) charge-coupled device (CCD) imagery (spatial resolution of 30 m, revisit time of 2 days) in the monitoring of total suspended sediment (TSS) concentrations in dynamic water bodies using Poyang Lake, the largest freshwater lake in China, as an example. Field surveys conducted during October 17-26, 2009 showed a wide range of TSS concentration (3-524 mg/L). Atmospheric correction was implemented using the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) module in ENVI with the aid of aerosol information retrieved from concurrent Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) surveys, which worked well at the CCD bands with relatively high reflectance. A practical exponential retrieval algorithm was created between satellite remote sensing reflectance and in-situ measured TSS concentration. The retrieved results for the whole water area matched the in-situ data well at most stations. The retrieval errors may be related to the problem of scale matching and mixed pixel. In three selected subregions of Poyang Lake, the distribution trend of retrieved TSS was consistent with that of the field investigation. It was shown that HJ-1A/1B CCD imagery can be used to estimate TSS concentrations in Poyang Lake over synoptic scales after applying an appropriate atmospheric correction method and retrieval algorithm.
基金substantially supported by the National Natural Science Foundation of China[grant number 91438203]the National Basic Research Program of China(973 Program)[grant number 2014CB744201].
文摘Since the twenty-first century,with the rapid development of high-resolution earth observation satellites,the earth observation satellite system has developed from the initial single satellite observation model to the current satellite constellation formed by light and small satellites observation model.All-weather and all-directional fine earth observation can now be realized.In the future,the satellite constellation,communication satellites,navigation satellites,and aircrafts are linked through dynamic linking network to form an air-space information network to realize real-time services of intelligent air-space information.To further enhance the perception,cognition,and quick response ability of the network,we propose the concept and model of the Earth Observation Brain(EOB)−the intelligent earth system based on events perception in this paper.Then,some key technologies needed to be solved in the EOB are also described.An application example is illustrated to show the process of perception and cognition in the primary stage of the EOB.In the future,EOB can observe what change of what object,the when and where to push these right information to mobile terminal of right people at the right time and right place.Global users can obtain any data,information,and knowledge in real-time through the EOB.
基金This work was supported in part by the National Key Basic Research and Development Program of China[grant number 2013CB733404]the National Natural Science Foundation of China[grant number 61271401],[grant number 91338113].
文摘Unmanned aerial vehicle(UAV)-based imaging systems have many superiorities compared with other platforms,such as high flexibility and low cost in collecting images,providing wide application prospects.However,the acquisition of the UAV-based image commonly results in very high resolution and very large-scale images,which poses great challenges for subsequent applications.Therefore,an efficient representation of large-scale UAV images is necessary for the extraction of the required information in a reasonable time.In this work,we proposed a multi-scale hierarchical representation,i.e.binary partition tree,for analyzing large-scale UAV images.More precisely,we first obtained an initial partition of images by an oversegmentation algorithm,i.e.the simple linear iterative clustering.Next,we merged the similar superpixels to build an object-based hierarchical structure by fully considering the spectral and spatial information of the superpixels and their topological relationships.Moreover,objects of interest and optimal segmentation were obtained using object-based analysis methods with the hierarchical structure.Experimental results on processing the post-seismic UAV images of the 2013 Ya’an earthquake and the mosaic of images in the South-west of Munich demonstrate the effectiveness and efficiency of our proposed method.
基金funded by Key Research and Development Program of Hubei Province,China under grant 2021BAA186the National Natural Science Foundation of China under grant number 41601298.
文摘Benggang is a typical fragmented erosional landscape in southern and southeastern China,posing sig-nificant risk to the local residents and economic development.Therefore,an efficient and accurate fine-grained segmentation method is crucial for monitoring the Benggang areas.In this paper,we propose a deep learning-based automatic segmentation method for Benggang by integrating high-resolution Digital Orthophoto Map(DOM)and Digital Surface Model(DSM)data.The DSM data is used to extract slope maps,aiming to capture primary morphological features.The proposed method consists of a dual-stream convolutional encoder-decoder network in which multiple cascaded convolutional layers and a skip connection scheme are used to extract morphological and visual features of the Benggang areas.The rich discriminative information in the DOM and slope data is fused by a channel exchanging mechanism that dynamically exchanges the most discriminative features from either the DOM or DSM stream ac-cording to their importance at the channel level.Evaluation experiments were conducted on a chal-lenging dataset collected from Guangdong Province,China,and the results show that the proposed channel exchanging network based deep fusion method achieves 84.62%IoU in Benggang segmentation,outperforming several existing unimodal or multimodal baselines.The proposed multimodal segmen-tation method greatly improves the efficiency of large-scale discovery of Benggang,and thus is important for the management and restoration of Benggang in southern and southeastern China,as well as the monitoring of other similar erosional landscapes.
基金the National Natural Science Foundation of China(Grants No.41522110 and 41771360)the National Key Research and Development Program of China(Grant No.2016YFB0501403)。
文摘China has experienced unprecedented urbanization in the past decades,resulting in dramatic changes in the physical,limnological,and hydrological characteristics of lakes in urban landscapes.However,the spatiotemporal dynamics in distribution and abundance of urban lakes in China remain poorly understood.Here,we characterized the spatiotemporal change patterns of urban lakes in China’s major cities between 1990 and 2015 using remote-sensing data and landscape metrics.The results showed that the urban lake landscape patterns have experienced drastic changes over the past 25 years.The total surface area of the urban lakes has decreased by 17,620.02 ha,a decrease of 24.22%,with a significant increase in the landscape fragmentation and a reduction in shape complexity.We defined three lake-shrinkage types and found that vanishment was the most common lake-shrinkage pattern,followed by edge-shrinkage and tunneling in terms of lake area.Moreover,we also found that urban sprawl was the dominant driver of the lake shrinkage,accounting for 67.89%of the total area loss,and the transition from lakes to cropland was also an important factor(19.86%).This study has potential for providing critical baseline information for government decision-making in lake resources management and urban landscape design.
文摘Long-term navigation ability based on consumer-level wearable inertial sensors plays an essential role towards various emerging fields, for instance, smart healthcare, emergency rescue, soldier positioning et al. The performance of existing long-term navigation algorithm is limited by the cumulative error of inertial sensors, disturbed local magnetic field, and complex motion modes of the pedestrian. This paper develops a robust data and physical model dual-driven based trajectory estimation(DPDD-TE) framework, which can be applied for long-term navigation tasks. A Bi-directional Long Short-Term Memory(Bi-LSTM) based quasi-static magnetic field(QSMF) detection algorithm is developed for extracting useful magnetic observation for heading calibration, and another Bi-LSTM is adopted for walking speed estimation by considering hybrid human motion information under a specific time period. In addition, a data and physical model dual-driven based multi-source fusion model is proposed to integrate basic INS mechanization and multi-level constraint and observations for maintaining accuracy under long-term navigation tasks, and enhanced by the magnetic and trajectory features assisted loop detection algorithm. Real-world experiments indicate that the proposed DPDD-TE outperforms than existing algorithms, and final estimated heading and positioning accuracy indexes reaches 5° and less than 2 m under the time period of 30 min, respectively.
基金supported by the National Key Research and Development Program of China[grant numbers 2016YFB0502200,2016YFB0502201]the NSFC[grant number 91638203]。
文摘The indoor positioning system is now an important technique as part of the Internet-of-Things(IoT)ecosystem.Among indoor positioning techniques,multiple Wi-Fi Access Points(APs)-based positioning systems have been researched a lot.There is a lack of research focusing on the scene where only one Wi-Fi AP is available.This work proposes a hybrid indoor positioning system that takes advantage of the Fine-Timing Measurements(FTM)technique that is part of the IEEE 802.11mc standard,introduced back in 2016.The system uses one single Wi-Fi FTM AP and takes advantage of the built-in inertial sensors of the smartphone to estimate the device’s position.We explore both Loosely Coupled(LC)and Tightly Coupled(TC)integration schemes for the sensors’data fusion.Experimental results show that the proposed methods can achieve an average positioning accuracy of about 1 m without knowing the initial position.Compared with the LC integration method,the median error accuracy of the proposed TC fusion algorithm has improved by more than 52%and 67%,respectively,in the two experiments we set up.
文摘Land surface water mapping is one of the most important remote-sensing applications.However,water areas are spectrally similar and overlapped with shadow,making accurate water extraction from remote-sensing images still a challenging problem.This paper develops a novel water index named as NDWI-MSI,combining a new normalized difference water index(NDWI)and a recently developed morphological shadow index(MSI),to delineate water bodies from eight-band WorldView-2 imagery.The newly available bands(e.g.coastal,yellow,red-edge,and near-infrared 2)of WorldView-2 imagery provide more potential for constructing new NDWIs derived from various band combinations.Through our testing,a new NDWI is defined in this study.In addition,MSI,a recently developed automatic shadow extraction index from high-resolution imagery can be used to indicate shadow areas.The NDWI-MSI is created by combining NDWI and MSI,which is able to highlight water bodies and simultaneously suppress shadow areas.In experiments,it is shown that the new water index can achieve better performance than traditional NDWI,and even supervised classifiers,for example,maximum likelihood classifier,and support vector machine.
基金The work is supported by the National Basic Research Program of China(973 Program)(grant number 2011CB707105)the National Natural Science Foundation of China(grant number 41271397)the Program for New Century Excellent Talents in University(grant number NCET-13-0435).
文摘The paper gives an overview of the current status of education in geoinformatics in China.First,the paper provides a brief introduction to the history of geoinformatics education in China and a general review of the scientific and technological development.It then presents how the development affects the education and training in China.In the paper,universities and institutes in China that can award academic degrees related to geoinformatics are summarized,and undergraduate majors are briefly introduced.Next,the paper reports the work having been done by the national expert group on Surveying and Mapping,including the revision of discipline catalog and guide for graduate education and requirements.A list of typical curricula in geoinformatics education is suggested.Activities on promoting the graduate student exchange platform are presented.Finally,a case study of geoinformatics education in Wuhan University is discussed.
文摘Big data is a highlighted challenge for many fields with the rapid expansion of large-volume, complex, and fast-growing sources of data. Mining from big data is required for exploring the essence of data and providing meaningful information. To this end, we have previously introduced the theory of physical field to explore relations between objects in data space and proposed a framework of data field to discover the underlying distribution of big data. This paper concerns an overview of big data mining by the use of data field. It mainly discusses the theory of data field and different aspects of applications including feature selection for high-dimensional data, clustering, and the recognition of facial expression in human-computer interaction. In these applications, data field is employed to capture the intrinsic distribution of data objects for selecting meaningful features, fast clustering, and describing variation of facial expression. It is expected that our contributions would help overcome the problems in accordance with big data.
基金This work was supported by the National Natural Science Foundation of China[grant number 61331016]and[grant number 41174120].The TerraSAR-X data were provided by DLR via the LAN2245 Project.
文摘TerraSAR-X(TSX)can acquire high-resolution SAR images and due to its high orbit precision as well as its ability to acquire data from different off-nadir viewing angles,the high-precision stereo geolocation can be obtained.In this study,we investigate the absolute geolocation accuracy of TSX high-resolution images in Wuhan,China.We present a direct stereo SAR geolocation method and analyze the 2D and 3D geoposition accuracy of two corner reflectors.The sub-meter localization accuracy was achieved using only atmospheric correction information available in the TSX metadata.
基金The authors would like to thank the German Aerospace Center(DLR)for providing the test data-sets via the DLR AO LAN0793 and LAN0634,and Prof.Miaozhong Xu of LIESMARS for providing the photogrammetric DEM with spatial resolution of 3 mThis work was supported by the National Natural Science Foundation of China[grant number 41271457]the Demonstration System of High Resolution Remote Sensing Applications in Urban Fine Management Area[grant number 06-Y30B04–9002-13/15].
文摘Single SAR image direct positioning is to determine the ground coordinate for each pixel in the SAR image assisted with a reference DEM.During this procedure,an iterative procedure is essentially needed to solve the uncertainty in elevation of each pixel in the SAR image.However,such an iterative procedure may suffer from the problem of divergence in shaded and serious layover areas.To investigate this problem,we performed a theoretical analysis on the convergence conditions that has not been intensively studied till now.The Range-Doppler(RD)model was simplified and then the general surface is degenerated into a planar surface.Mathematical deduction was then carried out to derive the convergence conditions and the impact factors for the convergence speed were evaluated.The theoretical findings were validated by experiments for both simulated and real scenarios.
基金This work was supported by the National Natural Science Foundation of China[grant number 41371370]the National Basic Research Program of China[grant number 2012CB719906].
文摘Specific features of tile access patterns can be applied in a cache replacement strategy to a limited distributed high-speed cache for the cloud-based networked geographic information services(NGISs),aiming to adapt to changes in the access distribution of hotspots.By taking advantage of the spatiotemporal locality,the sequential features in tile access patterns,and the cache reading performance in the burst mode,this article proposes a tile sequence replacement method,which involves structuring a Least Recently Used(LRU)stack into three portions for the different functions in cache replacement and deriving an expression for the temporal locality and popularity of the relevant tile to facilitate the replacement process.Based on the spatial characteristics of both the tiles and the cache burst mode with regard to reading data,the proposed method generates multiple tile sequences to reflect spatiotemporal locality in tile access patterns.Then,we measure the caching value by a technique based on a weighted-based method.This technique draws on the recent access popularity and low caching costs of tile sequences,with the aim of balancing the temporal and spatial localities in tile access.It ranks tile sequences in a replacement queue to adapt to the changes in accessed hotspots while reducing the replacement frequency.Experimental results show that the proposed method effectively improves the hit rate and utilization rate for a limited distributed cache while achieving satisfactory response performance and high throughput for users in an NGIS.Therefore,it can be adapted to handle numerous data access requests in NGISs in a cloud-based environment.
