High-quality height reference data are embedded in the accuracy verification processes of most remote sensing terrain applications.The Ice,Cloud,and Land elevation Satellite 2(ICESat-2)/ATL08 terrain product has shown...High-quality height reference data are embedded in the accuracy verification processes of most remote sensing terrain applications.The Ice,Cloud,and Land elevation Satellite 2(ICESat-2)/ATL08 terrain product has shown promising results for estimating ground heights,but it has not been fully evaluated.Hence,this study aims to assess and enhance the accuracy of the ATL08 terrain product as a height reference for the newest versions of the Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER),the Shuttle Radar Topography Mission(SRTM),and TanDEM-X(TDX)DEMs over vegetated mountainous areas.We used uncertainty-based filtering method for the ATL08 strong and weak beams to enhance their accuracy.Then,the results were evaluated against a reference airborne LiDAR digital terrain model(DTM),by selecting 10,000 points over the entire area and comparing the accuracy of ASTER,SRTM,and TDX DEMs assessed by the LiDAR DTM to the accuracy of the ASTER,SRTM,and TDX DEMs assessed by the ATL08 strong beams,weak beams,and all beams.We also detected the impact of the terrain aspect,slope,and land cover types on the accuracy of the ATL08 terrain elevations and their relationship with height errors and uncertainty.Our findings show the accuracy of the ATL08 strong beams was enhanced by 43.91%;while the weak beams accuracy was enhanced by 74.05%.Furthermore,slope strongly influenced ATL08 height errors and height uncertainty;especially on the weak beams.The errors induced by the slope significantly decreased when the uncertainty levels were reduced to<20 m.The evaluations of ASTER,SRTM,and TDX DEMs by ATL08 strong and weak beams are close to those assessed by LiDAR DTM points within 0.6 m for the strong beams.These findings indicate that ATL08 strong beams can be used as a height reference over vegetated mountainous regions.展开更多
Many existing efforts have taken advantage of large-scale spatial-temporal data to partition cities via constructed human interaction networks.However,few studies focus on communities emerging between adjacent cities ...Many existing efforts have taken advantage of large-scale spatial-temporal data to partition cities via constructed human interaction networks.However,few studies focus on communities emerging between adjacent cities in big urban agglomerations,which we call“cross-city”communities.In this study,we introduce a novel framework to detect cross-city communities in urban agglomerations under different scales leveraging a large number of fine-grained mobile signaling data aiming to break the original administrative boundaries.Taking the Pearl River Delta(PRD)urban agglomeration in China as study area,we investigate the existence of potential communities at three scales,i.e.city-group level,city level and sub-city level.The partition results are expected to benefit transportation planning,urban zoning and administrative boundary re-delineation.The results from our study highlight the necessity of considering cross-city communities and their scale effects when examining urban spatial interactions.展开更多
基金supported in part by the National Natural Science Foundation of China under grant of 42090012in part by the project supported by the Open Fund of Hubei Luojia Laboratory(220100009)+3 种基金in part by 03 special research and 5G project of Jiangxi province in China(20212ABC03A09)Zhuhai industry university research cooperation project of China(ZH22017001210098PWC)Sichuan Science and Technology Program(2022YFN0031)Zhizhuo Research Fund on Spatial-Temporal Artificial Intelligence(Grant No.ZZJJ202202).
文摘High-quality height reference data are embedded in the accuracy verification processes of most remote sensing terrain applications.The Ice,Cloud,and Land elevation Satellite 2(ICESat-2)/ATL08 terrain product has shown promising results for estimating ground heights,but it has not been fully evaluated.Hence,this study aims to assess and enhance the accuracy of the ATL08 terrain product as a height reference for the newest versions of the Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER),the Shuttle Radar Topography Mission(SRTM),and TanDEM-X(TDX)DEMs over vegetated mountainous areas.We used uncertainty-based filtering method for the ATL08 strong and weak beams to enhance their accuracy.Then,the results were evaluated against a reference airborne LiDAR digital terrain model(DTM),by selecting 10,000 points over the entire area and comparing the accuracy of ASTER,SRTM,and TDX DEMs assessed by the LiDAR DTM to the accuracy of the ASTER,SRTM,and TDX DEMs assessed by the ATL08 strong beams,weak beams,and all beams.We also detected the impact of the terrain aspect,slope,and land cover types on the accuracy of the ATL08 terrain elevations and their relationship with height errors and uncertainty.Our findings show the accuracy of the ATL08 strong beams was enhanced by 43.91%;while the weak beams accuracy was enhanced by 74.05%.Furthermore,slope strongly influenced ATL08 height errors and height uncertainty;especially on the weak beams.The errors induced by the slope significantly decreased when the uncertainty levels were reduced to<20 m.The evaluations of ASTER,SRTM,and TDX DEMs by ATL08 strong and weak beams are close to those assessed by LiDAR DTM points within 0.6 m for the strong beams.These findings indicate that ATL08 strong beams can be used as a height reference over vegetated mountainous regions.
基金supported in part by the Guangxi science and technology program(GuiKe 2021AB30019)Sichuan Science and Technology Program(2022YFN0031,2023YFN0022,and 2023YFS0381)+2 种基金Hubei key R&D plan(2022BAA048)Zhuhai industry university research cooperation project of China(ZH22017001210098PWC)Shanxi Science and Technology Program(202201150401020).
文摘Many existing efforts have taken advantage of large-scale spatial-temporal data to partition cities via constructed human interaction networks.However,few studies focus on communities emerging between adjacent cities in big urban agglomerations,which we call“cross-city”communities.In this study,we introduce a novel framework to detect cross-city communities in urban agglomerations under different scales leveraging a large number of fine-grained mobile signaling data aiming to break the original administrative boundaries.Taking the Pearl River Delta(PRD)urban agglomeration in China as study area,we investigate the existence of potential communities at three scales,i.e.city-group level,city level and sub-city level.The partition results are expected to benefit transportation planning,urban zoning and administrative boundary re-delineation.The results from our study highlight the necessity of considering cross-city communities and their scale effects when examining urban spatial interactions.
