Multi-temporal Interferometric Synthetic Aperture Radar(MT-InSAR) is one of the most powerful Earth observation techniques, especially useful for measuring highly detailed ground deformation over large ground areas. M...Multi-temporal Interferometric Synthetic Aperture Radar(MT-InSAR) is one of the most powerful Earth observation techniques, especially useful for measuring highly detailed ground deformation over large ground areas. Much research has been carried out to apply MT-InSAR to monitor ground and infrastructure deformation in urban areas related to land reclamation, underground construction and groundwater extraction.This paper reviews the progress in the research and identifies challenges in applying the technology, including the inconsistency in coherent point identification when different approaches are used, the reliability issue in parameter estimation, difficulty in accurate geolocation of measured points, the one-dimensional line-of-sight nature of InSAR measurements, the inability of making complete measurements over an area due to geometric distortions, especially the shadowing effects, the challenges in processing large SAR datasets, the decrease of the number of coherent points with the increase of the length of SAR time series, and the difficulty in quality control of MT-InSAR results.展开更多
Constrained by complex imaging mechanism and extraordinary visual appearance,change detection with synthetic aperture radar(SAR)images has been a difficult research topic,especially in urban areas.Although existing st...Constrained by complex imaging mechanism and extraordinary visual appearance,change detection with synthetic aperture radar(SAR)images has been a difficult research topic,especially in urban areas.Although existing studies have extended from bi-temporal data pair to multi-temporal datasets to derive more plentiful information,there are still two problems to be solved in practical applications.First,change indicators constructed from incoherent feature only cannot characterize the change objects accurately.Second,the results of pixel-level methods are usually presented in the form of the noisy binary map,making the spatial change not intuitive and the temporal change of a single pixel meaningless.In this study,we propose an unsupervised man-made objects change detection framework using both coherent and incoherent features derived from multi-temporal SAR images.The coefficients of variation in timeseries incoherent features and the man-made object index(MOI)defined with coherent features are first combined to identify the initial change pixels.Afterwards,an improved spatiotemporal clustering algorithm is developed based on density-based spatial clustering of applications with noise(DBSCAN)and dynamic time warping(DTW),which can transform the initial results into noiseless object-level patches,and take the cluster center as a representative of the man-made object to determine the change pattern of each patch.An experiment with a stack of 10 TerraSAR-X images in Stripmap mode demonstrated that this method is effective in urban scenes and has the potential applicability to wide area change detection.展开更多
Affected by the natural environmental and human activity factors,significant seasonal differences appear on the regional scattering characteristic and ground deformation of saline soil.Interferometric decorrelation du...Affected by the natural environmental and human activity factors,significant seasonal differences appear on the regional scattering characteristic and ground deformation of saline soil.Interferometric decorrelation due to season replacement limits the conventional multi-temporal interferometric synthetic aperture radar(MT-InSAR)technique and its application in such areas.To extend the monitoring capability in the salt desert area,we select a vast basin of saline soil around Howz-e-Soltan Salt Lake of Iran as the study area and present an improved MTInSAR for experimental research.Based on 131 C-band Sentinel-1 A images collected between October 2014 to July 2020,1896 refined interferograms in total are selected from all interferogram candidates.Interferometric coherence analysis shows that the coherence in the saline soil area has an apparent seasonal variation,and the soil moisture affected by the precipitation may be the main factor that leads to the seasonal variation.Subsequently,the deformation characteristics of saline soil under different environmental conditions and human activity factors are compared and analyzed in detail.Related deformation mechanisms of different saline soil types are initially revealed by combining interferometric coherence,meteorological data,and engineering geological characteristics of saline soil.Related results would provide reference for the large-scale infrastructure construction engineering in similar saline soil areas.展开更多
Synthetic aperture radar(SAR) is able to detect surface changes in urban areas with a short revisit time, showing its capability in disaster assessment and urbanization monitoring.Most presented change detection metho...Synthetic aperture radar(SAR) is able to detect surface changes in urban areas with a short revisit time, showing its capability in disaster assessment and urbanization monitoring.Most presented change detection methods are conducted using couples of SAR amplitude images. However, a prior date of surface change is required to select a feasible image pair. We propose an automatic spatio-temporal change detection method by identifying the temporary coherent scatterers. Based on amplitude time series, χ^(2)-test and iterative single pixel change detection are proposed to identify all step-times: the moments of the surface change. Then the parameters, e.g., deformation velocity and relative height, are estimated and corresponding coherent periods are identified by using interferometric phase time series. With identified temporary coherent scatterers, different types of temporal surface changes can be classified using the location of the coherent periods and spatial significant changes are identified combining point density and F values. The main advantage of our method is automatically detecting spatio-temporal surface changes without prior information. Experimental results by the proposed method show that both appearing and disappearing buildings with their step-times are successfully identified and results by ascending and descending SAR images show a good agreement.展开更多
基金The National Natural Science Foundation of China(41774023)The Research Grants Council(RGC)of Hong Kong(PolyU152232/17E,PolyU152164/18E),The Faculty of Construction and Environment(ZZGD)+1 种基金The Research Institute for Sustainable Urban Development(RISUD)(1-BBWB)The TerraSAR-X Science plan(GEO3603)。
文摘Multi-temporal Interferometric Synthetic Aperture Radar(MT-InSAR) is one of the most powerful Earth observation techniques, especially useful for measuring highly detailed ground deformation over large ground areas. Much research has been carried out to apply MT-InSAR to monitor ground and infrastructure deformation in urban areas related to land reclamation, underground construction and groundwater extraction.This paper reviews the progress in the research and identifies challenges in applying the technology, including the inconsistency in coherent point identification when different approaches are used, the reliability issue in parameter estimation, difficulty in accurate geolocation of measured points, the one-dimensional line-of-sight nature of InSAR measurements, the inability of making complete measurements over an area due to geometric distortions, especially the shadowing effects, the challenges in processing large SAR datasets, the decrease of the number of coherent points with the increase of the length of SAR time series, and the difficulty in quality control of MT-InSAR results.
基金supported by the National Natural Science Foundation of China(41774006)the Comparative Study of Geo-environment and Geohazards in the Yangtze River Delta and the Red River Delta Projectthe Shanghai Science and Technology Development Foundation(20dz1201200)。
文摘Constrained by complex imaging mechanism and extraordinary visual appearance,change detection with synthetic aperture radar(SAR)images has been a difficult research topic,especially in urban areas.Although existing studies have extended from bi-temporal data pair to multi-temporal datasets to derive more plentiful information,there are still two problems to be solved in practical applications.First,change indicators constructed from incoherent feature only cannot characterize the change objects accurately.Second,the results of pixel-level methods are usually presented in the form of the noisy binary map,making the spatial change not intuitive and the temporal change of a single pixel meaningless.In this study,we propose an unsupervised man-made objects change detection framework using both coherent and incoherent features derived from multi-temporal SAR images.The coefficients of variation in timeseries incoherent features and the man-made object index(MOI)defined with coherent features are first combined to identify the initial change pixels.Afterwards,an improved spatiotemporal clustering algorithm is developed based on density-based spatial clustering of applications with noise(DBSCAN)and dynamic time warping(DTW),which can transform the initial results into noiseless object-level patches,and take the cluster center as a representative of the man-made object to determine the change pattern of each patch.An experiment with a stack of 10 TerraSAR-X images in Stripmap mode demonstrated that this method is effective in urban scenes and has the potential applicability to wide area change detection.
基金supported by the National Natural Science Foundation of China(41771402,41804009)the National Key R&D Program of China(2017YFB0502700)Sichuan Science and Technology Program(2018JY0564,2019ZDZX0042,2020JDTD0003)。
文摘Affected by the natural environmental and human activity factors,significant seasonal differences appear on the regional scattering characteristic and ground deformation of saline soil.Interferometric decorrelation due to season replacement limits the conventional multi-temporal interferometric synthetic aperture radar(MT-InSAR)technique and its application in such areas.To extend the monitoring capability in the salt desert area,we select a vast basin of saline soil around Howz-e-Soltan Salt Lake of Iran as the study area and present an improved MTInSAR for experimental research.Based on 131 C-band Sentinel-1 A images collected between October 2014 to July 2020,1896 refined interferograms in total are selected from all interferogram candidates.Interferometric coherence analysis shows that the coherence in the saline soil area has an apparent seasonal variation,and the soil moisture affected by the precipitation may be the main factor that leads to the seasonal variation.Subsequently,the deformation characteristics of saline soil under different environmental conditions and human activity factors are compared and analyzed in detail.Related deformation mechanisms of different saline soil types are initially revealed by combining interferometric coherence,meteorological data,and engineering geological characteristics of saline soil.Related results would provide reference for the large-scale infrastructure construction engineering in similar saline soil areas.
基金supported by the National Natural Science Foundation of China (42074022)。
文摘Synthetic aperture radar(SAR) is able to detect surface changes in urban areas with a short revisit time, showing its capability in disaster assessment and urbanization monitoring.Most presented change detection methods are conducted using couples of SAR amplitude images. However, a prior date of surface change is required to select a feasible image pair. We propose an automatic spatio-temporal change detection method by identifying the temporary coherent scatterers. Based on amplitude time series, χ^(2)-test and iterative single pixel change detection are proposed to identify all step-times: the moments of the surface change. Then the parameters, e.g., deformation velocity and relative height, are estimated and corresponding coherent periods are identified by using interferometric phase time series. With identified temporary coherent scatterers, different types of temporal surface changes can be classified using the location of the coherent periods and spatial significant changes are identified combining point density and F values. The main advantage of our method is automatically detecting spatio-temporal surface changes without prior information. Experimental results by the proposed method show that both appearing and disappearing buildings with their step-times are successfully identified and results by ascending and descending SAR images show a good agreement.
