Pub Date : 2023-09-14DOI: 10.1080/10095020.2023.2255037
Yizhen Meng, Ji Zhou, Frank-Michael Göttsche, Wenbin Tang, João Martins, Lluis Perez-Planells, Jin Ma, Ziwei Wang
The need for cross-comparison and validation of all-weather Land Surface Temperature (LST) products has arisen due to the release of multiple such products aimed at providing comprehensive all-weather monitoring capabilities. In this study, we focus on validating two well-established all-weather LST products (i.e. MLST-AS and TRIMS LST) against in-situ measurements obtained from four high-quality LST validation sites: Evora, Gobabeb, KIT-Forest, and Lake Constance. For the land sites, MLST-AS exhibits better accuracy, with RMSEs ranging from 1.6 K to 2.1 K, than TRIMS LST, the RMSEs of which range from 1.9 K to 3.1 K. Because MLST-AS pixels classified as “inland water” are masked out, the validation over Lake Constance is limited to TRIMS LST: it yields a RMSE of 1.6 K. Furthermore, the validation results show that MLST-AS and TRIMS LST exhibit better accuracy under clear-sky conditions than unclear-sky conditions across all sites. Since the accuracy of the all-weather LST products is considerably affected by the input clear-sky LST products, we further compare the all-weather LST with the corresponding input clear-sky LST to conduct an error source analysis. Considering the clear-sky pixels on MLST-AS directly using the estimates from MLST, the error source analysis is limited to examining TRIMS LST and its input (i.e. MODIS LST). The findings indicate that TRIMS LST is highly correlated with MODIS LST. The investigation and validation of the two selected all-weather LST products objectively evaluate their accuracy and stability, which provides important information for applications of these all-weather LST products.
{"title":"Investigation and validation of two all-weather land surface temperature products with in-situ measurements","authors":"Yizhen Meng, Ji Zhou, Frank-Michael Göttsche, Wenbin Tang, João Martins, Lluis Perez-Planells, Jin Ma, Ziwei Wang","doi":"10.1080/10095020.2023.2255037","DOIUrl":"https://doi.org/10.1080/10095020.2023.2255037","url":null,"abstract":"The need for cross-comparison and validation of all-weather Land Surface Temperature (LST) products has arisen due to the release of multiple such products aimed at providing comprehensive all-weather monitoring capabilities. In this study, we focus on validating two well-established all-weather LST products (i.e. MLST-AS and TRIMS LST) against in-situ measurements obtained from four high-quality LST validation sites: Evora, Gobabeb, KIT-Forest, and Lake Constance. For the land sites, MLST-AS exhibits better accuracy, with RMSEs ranging from 1.6 K to 2.1 K, than TRIMS LST, the RMSEs of which range from 1.9 K to 3.1 K. Because MLST-AS pixels classified as “inland water” are masked out, the validation over Lake Constance is limited to TRIMS LST: it yields a RMSE of 1.6 K. Furthermore, the validation results show that MLST-AS and TRIMS LST exhibit better accuracy under clear-sky conditions than unclear-sky conditions across all sites. Since the accuracy of the all-weather LST products is considerably affected by the input clear-sky LST products, we further compare the all-weather LST with the corresponding input clear-sky LST to conduct an error source analysis. Considering the clear-sky pixels on MLST-AS directly using the estimates from MLST, the error source analysis is limited to examining TRIMS LST and its input (i.e. MODIS LST). The findings indicate that TRIMS LST is highly correlated with MODIS LST. The investigation and validation of the two selected all-weather LST products objectively evaluate their accuracy and stability, which provides important information for applications of these all-weather LST products.","PeriodicalId":48531,"journal":{"name":"Geo-spatial Information Science","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134913042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-12DOI: 10.1080/10095020.2023.2251530
Chaoqian Xu, Yang Jiang, Yang Gao, Yibin Yao
The tropospheric delay has a significant impact on high-accuracy positioning of the Global Navigation Satellite System (GNSS). Traditional solutions have their weaknesses. First, the estimation of tropospheric delay as a state parameter slows the positioning filter’s convergence, especially critical for Precise Point Positioning (PPP). Second, correction-based approaches, including empirical model, meteorological model and GNSS network observations, have their corresponding limitations. The empirical model comprises yearly data-based statistics, which ignores high temporal-variation components, leading to decreased correction accuracy. The meteorological model requires real-time local weather observations. One can enable the network method of the expensive regional infrastructure of GNSS stations, of which performance depends on the rover-network geometry. In this study, we enable a real-time tropospheric regional correction service by polynomial coefficients from the Kalman filtering of multisource data, including the Global Pressure and Temperature 2 wet (GPT2w) model, weather observations from the National Oceanic and Atmospheric Administration (NOAA), and GNSS network observations. After discussing the weighting strategy examined by the regional dataset from Zhejiang Province, we evaluate the performance of the proposed fusion approach with post-processed PPP results as references. We obtained the optimal weightings for the corresponding dataset, and the average accuracy for Zenith Tropospheric Delay (ZTD) is 0.43, and 1.20 cm under static, active, and overall weather conditions, respectively. Compared with the real-time GNSS network ZTD solution, our proposed fusion solution is improved by 48.21%, 55.20%, and 41.70%, respectively. In conclusion, the proposed approach makes the best of three traditional correction-based methods to provide optimized real-time tropospheric service.
{"title":"Tropospheric polynomial coefficients for real-time regional correction by Kalman filtering from multisource data","authors":"Chaoqian Xu, Yang Jiang, Yang Gao, Yibin Yao","doi":"10.1080/10095020.2023.2251530","DOIUrl":"https://doi.org/10.1080/10095020.2023.2251530","url":null,"abstract":"The tropospheric delay has a significant impact on high-accuracy positioning of the Global Navigation Satellite System (GNSS). Traditional solutions have their weaknesses. First, the estimation of tropospheric delay as a state parameter slows the positioning filter’s convergence, especially critical for Precise Point Positioning (PPP). Second, correction-based approaches, including empirical model, meteorological model and GNSS network observations, have their corresponding limitations. The empirical model comprises yearly data-based statistics, which ignores high temporal-variation components, leading to decreased correction accuracy. The meteorological model requires real-time local weather observations. One can enable the network method of the expensive regional infrastructure of GNSS stations, of which performance depends on the rover-network geometry. In this study, we enable a real-time tropospheric regional correction service by polynomial coefficients from the Kalman filtering of multisource data, including the Global Pressure and Temperature 2 wet (GPT2w) model, weather observations from the National Oceanic and Atmospheric Administration (NOAA), and GNSS network observations. After discussing the weighting strategy examined by the regional dataset from Zhejiang Province, we evaluate the performance of the proposed fusion approach with post-processed PPP results as references. We obtained the optimal weightings for the corresponding dataset, and the average accuracy for Zenith Tropospheric Delay (ZTD) is 0.43, and 1.20 cm under static, active, and overall weather conditions, respectively. Compared with the real-time GNSS network ZTD solution, our proposed fusion solution is improved by 48.21%, 55.20%, and 41.70%, respectively. In conclusion, the proposed approach makes the best of three traditional correction-based methods to provide optimized real-time tropospheric service.","PeriodicalId":48531,"journal":{"name":"Geo-spatial Information Science","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135827026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Carbon dioxide (CO2) is one of the main greenhouse gases and has become a major concern as its concentration has been growing in recent years. Satellite remote sensing is an efficient way to monitor CO2 in the atmosphere, and several satellites are already used for CO2 monitoring. It is imperative to investigate the spatial coverage and spatio-temporal trends of satellite products, as well as identify the satellites with higher levels of accuracy. Additionally, examining the disparities between the older and new generations of satellites would be meaningful. Therefore, this paper provides a comprehensive evaluation and inter-comparison for the commonly used satellite column-averaged dry-air mole fraction of CO2 (XCO2) products. Specifically, the temporal trends and monthly coverage of the Greenhouse Gases Observing SATellite (GOSAT), Greenhouse Gases Observing SATellite-2 (GOSAT-2), Orbiting Carbon Observatory-2 (OCO-2), Orbiting Carbon Observatory-3 (OCO-3), and SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) are investigated. The accuracy of these satellite products is evaluated and analyzed based on Total Carbon Column Observing Network (TCCON) data. The results indicate that the XCO2 of all the satellite products show a year-by-year increase, with seasonal periodicity. In terms of overall accuracy, the OCO series satellites exhibit a slightly higher level of accuracy compared to the GOSAT series. The products of the new generation of satellites are less stable than those of the older generation, probably due to the impacts of the inversion algorithm and platforms.
{"title":"Inter-comparison and evaluation of global satellite XCO<sub>2</sub> products","authors":"Hongji Yang, Tongwen Li, Jingan Wu, Lingfeng Zhang","doi":"10.1080/10095020.2023.2252017","DOIUrl":"https://doi.org/10.1080/10095020.2023.2252017","url":null,"abstract":"Carbon dioxide (CO2) is one of the main greenhouse gases and has become a major concern as its concentration has been growing in recent years. Satellite remote sensing is an efficient way to monitor CO2 in the atmosphere, and several satellites are already used for CO2 monitoring. It is imperative to investigate the spatial coverage and spatio-temporal trends of satellite products, as well as identify the satellites with higher levels of accuracy. Additionally, examining the disparities between the older and new generations of satellites would be meaningful. Therefore, this paper provides a comprehensive evaluation and inter-comparison for the commonly used satellite column-averaged dry-air mole fraction of CO2 (XCO2) products. Specifically, the temporal trends and monthly coverage of the Greenhouse Gases Observing SATellite (GOSAT), Greenhouse Gases Observing SATellite-2 (GOSAT-2), Orbiting Carbon Observatory-2 (OCO-2), Orbiting Carbon Observatory-3 (OCO-3), and SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) are investigated. The accuracy of these satellite products is evaluated and analyzed based on Total Carbon Column Observing Network (TCCON) data. The results indicate that the XCO2 of all the satellite products show a year-by-year increase, with seasonal periodicity. In terms of overall accuracy, the OCO series satellites exhibit a slightly higher level of accuracy compared to the GOSAT series. The products of the new generation of satellites are less stable than those of the older generation, probably due to the impacts of the inversion algorithm and platforms.","PeriodicalId":48531,"journal":{"name":"Geo-spatial Information Science","volume":"362 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135825746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-02DOI: 10.1080/10095020.2023.2191649
Jie Yin, Tao Li, Hao Yin, Wenxian Yu, Danping Zou
Integrating Global Navigation Satellite Systems (GNSS) in Simultaneous Localization and Mapping (SLAM) systems draws increasing attention to a global and continuous localization solution. Nonetheless, in dense urban environments, GNSS-based SLAM systems will suffer from the Non-Line-Of-Sight (NLOS) measurements, which might lead to a sharp deterioration in localization results. In this paper, we propose to detect the sky area from the up-looking camera to improve GNSS measurement reliability for more accurate position estimation. We present Sky-GVINS: a sky-aware GNSS-Visual-Inertial system based on a recent work called GVINS. Specifically, we adopt a global threshold method to segment the sky regions and non-sky regions in the fish-eye sky-pointing image and then project satellites to the image using the geometric relationship between satellites and the camera. After that, we reject satellites in non-sky regions to eliminate NLOS signals. We investigated various segmentation algorithms for sky detection and found that the Otsu algorithm reported the highest classification rate and computational efficiency, despite the algorithm’s simplicity and ease of implementation. To evaluate the effectiveness of Sky-GVINS, we built a ground robot and conducted extensive real-world experiments on campus. Experimental results show that our method improves localization accuracy in both open areas and dense urban environments compared to the baseline method. Finally, we also conduct a detailed analysis and point out possible further directions for future research. For detailed information, visit our project website at https://github.com/SJTU-ViSYS/Sky-GVINS.
{"title":"Sky-GVINS: a sky-segmentation aided GNSS-Visual-Inertial system for robust navigation in urban canyons","authors":"Jie Yin, Tao Li, Hao Yin, Wenxian Yu, Danping Zou","doi":"10.1080/10095020.2023.2191649","DOIUrl":"https://doi.org/10.1080/10095020.2023.2191649","url":null,"abstract":"Integrating Global Navigation Satellite Systems (GNSS) in Simultaneous Localization and Mapping (SLAM) systems draws increasing attention to a global and continuous localization solution. Nonetheless, in dense urban environments, GNSS-based SLAM systems will suffer from the Non-Line-Of-Sight (NLOS) measurements, which might lead to a sharp deterioration in localization results. In this paper, we propose to detect the sky area from the up-looking camera to improve GNSS measurement reliability for more accurate position estimation. We present Sky-GVINS: a sky-aware GNSS-Visual-Inertial system based on a recent work called GVINS. Specifically, we adopt a global threshold method to segment the sky regions and non-sky regions in the fish-eye sky-pointing image and then project satellites to the image using the geometric relationship between satellites and the camera. After that, we reject satellites in non-sky regions to eliminate NLOS signals. We investigated various segmentation algorithms for sky detection and found that the Otsu algorithm reported the highest classification rate and computational efficiency, despite the algorithm’s simplicity and ease of implementation. To evaluate the effectiveness of Sky-GVINS, we built a ground robot and conducted extensive real-world experiments on campus. Experimental results show that our method improves localization accuracy in both open areas and dense urban environments compared to the baseline method. Finally, we also conduct a detailed analysis and point out possible further directions for future research. For detailed information, visit our project website at https://github.com/SJTU-ViSYS/Sky-GVINS.","PeriodicalId":48531,"journal":{"name":"Geo-spatial Information Science","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135016018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-03DOI: 10.1080/10095020.2023.2231734
Ed Mikhail
{"title":"Fritz Ackermann: a true and unequalled friend","authors":"Ed Mikhail","doi":"10.1080/10095020.2023.2231734","DOIUrl":"https://doi.org/10.1080/10095020.2023.2231734","url":null,"abstract":"","PeriodicalId":48531,"journal":{"name":"Geo-spatial Information Science","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135717579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-04-03DOI: 10.1080/10095020.2017.1337320
J. van Genderen
In the first issue of this year, our editor-in-chief wrote an inspiring Editorial about the 20 years’ history of this journal. That forms a nice background to this Special Issue, in that he gave a very good overview of the journal’s aims and scope, and an interesting summary of geospatial information science, as well as some challenges for the future. During this 20th anniversary year, we will be producing two Special Issues to mark this auspicious occasion. It is a great pleasure that I am writing this guest editorial for the first of these two Special 20th Anniversary Issues for our journal on the subject of “Perspectives on the nature of geospatial information”. Since the introduction of remote sensing in the 1960s, of GIS in the 1970s, followed by GPS, and geospatial information technology, such technologies now permeate in all aspects of people’s daily lives. The advent of smartphones, social media, the cloud computing, big data, the Internet of Things, artificial intelligence (AI), robotics and automation, virtual reality, and several others have enabled many location-based services and other geospatial services to be used in construction, industry, commerce, agriculture, defense and security, disaster management, agriculture as well as many other application areas. The theme of this Special Issue, “Perspectives on the nature of geospatial information” was especially selected to show the wide range of different perspectives, approaches to, and applications of geospatial information. In this issue, we have included major contributions of the leading geospatial information science practitioners and organizations that have shaped this dynamic field. There are 13 papers in it, with authors coming from 13 countries, showing the truly international nature of this journal. We have some excellent review papers on policy, at the global and national levels, as well as overview/status papers with various perspectives on the nature of geospatial information. These include technical, educational, commercial, industrial, security, scientific perspectives on the nature of geospatial information, as well as on geospatial standards issues, in addition to some application examples. The papers also cover many different parts of the world.
{"title":"Perspectives on the nature of geospatial information","authors":"J. van Genderen","doi":"10.1080/10095020.2017.1337320","DOIUrl":"https://doi.org/10.1080/10095020.2017.1337320","url":null,"abstract":"In the first issue of this year, our editor-in-chief wrote an inspiring Editorial about the 20 years’ history of this journal. That forms a nice background to this Special Issue, in that he gave a very good overview of the journal’s aims and scope, and an interesting summary of geospatial information science, as well as some challenges for the future. During this 20th anniversary year, we will be producing two Special Issues to mark this auspicious occasion. It is a great pleasure that I am writing this guest editorial for the first of these two Special 20th Anniversary Issues for our journal on the subject of “Perspectives on the nature of geospatial information”. Since the introduction of remote sensing in the 1960s, of GIS in the 1970s, followed by GPS, and geospatial information technology, such technologies now permeate in all aspects of people’s daily lives. The advent of smartphones, social media, the cloud computing, big data, the Internet of Things, artificial intelligence (AI), robotics and automation, virtual reality, and several others have enabled many location-based services and other geospatial services to be used in construction, industry, commerce, agriculture, defense and security, disaster management, agriculture as well as many other application areas. The theme of this Special Issue, “Perspectives on the nature of geospatial information” was especially selected to show the wide range of different perspectives, approaches to, and applications of geospatial information. In this issue, we have included major contributions of the leading geospatial information science practitioners and organizations that have shaped this dynamic field. There are 13 papers in it, with authors coming from 13 countries, showing the truly international nature of this journal. We have some excellent review papers on policy, at the global and national levels, as well as overview/status papers with various perspectives on the nature of geospatial information. These include technical, educational, commercial, industrial, security, scientific perspectives on the nature of geospatial information, as well as on geospatial standards issues, in addition to some application examples. The papers also cover many different parts of the world.","PeriodicalId":48531,"journal":{"name":"Geo-spatial Information Science","volume":"138 1","pages":"57 - 58"},"PeriodicalIF":6.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89357957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-03DOI: 10.3724/SP.J.1047.2012.00448
Yuke Zhou, Ting Ma, Chenghu Zhou, Xizhang Gao, Junfu Fan
{"title":"Design and Implement of Parallel Spatial Analysis System Based on MySQL & MPI: Design and Implement of Parallel Spatial Analysis System Based on MySQL & MPI","authors":"Yuke Zhou, Ting Ma, Chenghu Zhou, Xizhang Gao, Junfu Fan","doi":"10.3724/SP.J.1047.2012.00448","DOIUrl":"https://doi.org/10.3724/SP.J.1047.2012.00448","url":null,"abstract":"","PeriodicalId":48531,"journal":{"name":"Geo-spatial Information Science","volume":"512 1","pages":"448-453"},"PeriodicalIF":6.0,"publicationDate":"2012-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78140644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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