Qinghong Sheng, Rui Ren, Weilan Xu, Hui Xiao, Bo Wang, Ran Hong
A star sensor is a high-precision satellite attitude measurement device. Since its observation information has only two-dimensional direction vectors, when a star sensor is used for attitude determination the dimension of the observation information is less than the number of attitude angles determined, so mainstream algorithms usually only guarantee the accuracy of the pitch angle and the roll angle. In view of the lack of depth information in the observation's imaging geometric condition, this article proposes a spinor-based attitude determination model, which describes a straight line passing through two stars with the spinor and maps the depth information of the straight line with the pitch, to establish an imaging geometry model of the spinor coplanar condition. Experiments show that the yaw-angle attitude accuracy of the method is an order of magnitude better than that of mainstream algorithms, and the accuracy of the three attitude angles reaches the arc-second level.
{"title":"Spinor-Based Attitude Determination with Star Sensor Considering Depth","authors":"Qinghong Sheng, Rui Ren, Weilan Xu, Hui Xiao, Bo Wang, Ran Hong","doi":"10.14358/pers.87.8.551","DOIUrl":"https://doi.org/10.14358/pers.87.8.551","url":null,"abstract":"A star sensor is a high-precision satellite attitude measurement device. Since its observation information has only two-dimensional direction vectors, when a star sensor is used for attitude determination the dimension of the observation information is less than the number of attitude\u0000 angles determined, so mainstream algorithms usually only guarantee the accuracy of the pitch angle and the roll angle. In view of the lack of depth information in the observation's imaging geometric condition, this article proposes a spinor-based attitude determination model, which describes\u0000 a straight line passing through two stars with the spinor and maps the depth information of the straight line with the pitch, to establish an imaging geometry model of the spinor coplanar condition. Experiments show that the yaw-angle attitude accuracy of the method is an order of magnitude\u0000 better than that of mainstream algorithms, and the accuracy of the three attitude angles reaches the arc-second level.","PeriodicalId":49702,"journal":{"name":"Photogrammetric Engineering and Remote Sensing","volume":"17 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75421340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Grids and Datums Update: This month we look at the Republic of Yemen","authors":"C. Mugnier","doi":"10.14358/pers.87.8.547","DOIUrl":"https://doi.org/10.14358/pers.87.8.547","url":null,"abstract":"","PeriodicalId":49702,"journal":{"name":"Photogrammetric Engineering and Remote Sensing","volume":"345 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76391315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Buildings are considered prominent objects for understanding the pattern of growth in an urban setting. Remote sensing technology plays a vital role in facilitating data generation pertaining to various urban applications. Digital surface models represent the elevation of the earth surface features, and can be obtained from stereo images, radar, laser scanning, and so on. Photogrammetric techniques applied to optical stereo satellite images are economical and fast ways to generate height information of buildings. In this work, a quantitative and qualitative analysis of digital surface models generated from Cartosat-1 stereo images is compared with openly available data. The study finds that it is possible to acquire about 50 percent of building heights with acceptable error limits. The experimental results indicate that the quality of height information is suitable for applications to assess urban development at a macro scale, but not for individual building-level modeling.
{"title":"Digital Building-Height Preparation from Satellite Stereo Images","authors":"P. S. Prakash, B. Aithal","doi":"10.14358/pers.87.8.557","DOIUrl":"https://doi.org/10.14358/pers.87.8.557","url":null,"abstract":"Buildings are considered prominent objects for understanding the pattern of growth in an urban setting. Remote sensing technology plays a vital role in facilitating data generation pertaining to various urban applications. Digital surface models represent the elevation of the earth\u0000 surface features, and can be obtained from stereo images, radar, laser scanning, and so on. Photogrammetric techniques applied to optical stereo satellite images are economical and fast ways to generate height information of buildings. In this work, a quantitative and qualitative analysis\u0000 of digital surface models generated from Cartosat-1 stereo images is compared with openly available data. The study finds that it is possible to acquire about 50 percent of building heights with acceptable error limits. The experimental results indicate that the quality of height information\u0000 is suitable for applications to assess urban development at a macro scale, but not for individual building-level modeling.","PeriodicalId":49702,"journal":{"name":"Photogrammetric Engineering and Remote Sensing","volume":"32 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82489446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Image segmentation is a critical procedure in object-based identification and classification of remote sensing data. However, optimal scale-parameter selection presents a challenge, given the presence of complex landscapes and uncertain feature changes. This study proposes a local optimal segmentation approach that considers both intersegment heterogeneity and intrasegment homogeneity, uses the standard deviation and local Moran's index to explore each optimal segment across different scale parameters, and combines the optimal segments into a single layer. The optimal segment is measured by using high-spatial-resolution images. Results show that our approach out-performs and generates less error than the global optimal segmentation approach. The variety of land cover types or intrasegment homogeneity leads to segment matching with the geo-objects on different scales. Local optimal segmentation demonstrates sensitivity to land cover discrepancy and provides good performance on cross-scale segmentation.
{"title":"Optimizing the Segmentation of a High-Resolution Image by Using a Local Scale Parameter","authors":"Lei Zhang, Hongchao Liu, Xiaosong Li, Xinyu Qian","doi":"10.14358/pers.87.7.503","DOIUrl":"https://doi.org/10.14358/pers.87.7.503","url":null,"abstract":"Image segmentation is a critical procedure in object-based identification and classification of remote sensing data. However, optimal scale-parameter selection presents a challenge, given the presence of complex landscapes and uncertain feature changes. This study proposes a local optimal\u0000 segmentation approach that considers both intersegment heterogeneity and intrasegment homogeneity, uses the standard deviation and local Moran's index to explore each optimal segment across different scale parameters, and combines the optimal segments into a single layer. The optimal segment\u0000 is measured by using high-spatial-resolution images. Results show that our approach out-performs and generates less error than the global optimal segmentation approach. The variety of land cover types or intrasegment homogeneity leads to segment matching with the geo-objects on different scales.\u0000 Local optimal segmentation demonstrates sensitivity to land cover discrepancy and provides good performance on cross-scale segmentation.","PeriodicalId":49702,"journal":{"name":"Photogrammetric Engineering and Remote Sensing","volume":"21 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88349435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"GIS Tips & Tricks—Have you ever used the PLSS in your GIS","authors":"Alma M. Karlin","doi":"10.14358/pers.87.7.469","DOIUrl":"https://doi.org/10.14358/pers.87.7.469","url":null,"abstract":"","PeriodicalId":49702,"journal":{"name":"Photogrammetric Engineering and Remote Sensing","volume":"35 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73669817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Focus on Geodatabases in ArcGIS Pro","authors":"David W. Allen, Matthew Gerike","doi":"10.14358/pers.87.7.468","DOIUrl":"https://doi.org/10.14358/pers.87.7.468","url":null,"abstract":"","PeriodicalId":49702,"journal":{"name":"Photogrammetric Engineering and Remote Sensing","volume":"29 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82989160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Three-dimensional reconstruction from a single image has excellent future prospects. The use of neural networks for three-dimensional reconstruction has achieved remarkable results. Most of the current point-cloud-based three-dimensional reconstruction networks are trained using nonreal data sets and do not have good generalizability. Based on the Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago ()data set of large-scale scenes, this article proposes a method for processing real data sets. The data set produced in this work can better train our network model and realize point cloud reconstruction based on a single picture of the real world. Finally, the constructed point cloud data correspond well to the corresponding three-dimensional shapes, and to a certain extent, the disadvantage of the uneven distribution of the point cloud data obtained by light detection and ranging scanning is overcome using the proposed method.
{"title":"Three-Dimensional Reconstruction of Single Input Image Based on Point Cloud","authors":"Yu Hou, Ruifeng Zhai, Xueyan Li, Junfeng Song, Xuehan Ma, Shuzhao Hou, Shuxu Guo","doi":"10.14358/pers.87.7.479","DOIUrl":"https://doi.org/10.14358/pers.87.7.479","url":null,"abstract":"Three-dimensional reconstruction from a single image has excellent future prospects. The use of neural networks for three-dimensional reconstruction has achieved remarkable results. Most of the current point-cloud-based three-dimensional reconstruction networks are trained using nonreal\u0000 data sets and do not have good generalizability. Based on the Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago ()data set of large-scale scenes, this article proposes a method for processing real data sets. The data set produced in this work can better train\u0000 our network model and realize point cloud reconstruction based on a single picture of the real world. Finally, the constructed point cloud data correspond well to the corresponding three-dimensional shapes, and to a certain extent, the disadvantage of the uneven distribution of the point cloud\u0000 data obtained by light detection and ranging scanning is overcome using the proposed method.","PeriodicalId":49702,"journal":{"name":"Photogrammetric Engineering and Remote Sensing","volume":"135 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89074176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Akib Javed, Q. Cheng, Hao Peng, O. Altan, Yan Li, I. Ara, Enamul Huq, Yeamin Ali, Nayyer Saleem
Urban spectral indices have made promising improvements in the last two decades in urban land use land cover studies through mapping, estimation, change detection, time-series analyzing, urban dynamics, monitoring, modeling, and so on. Remote sensing spectral indices are unsupervised, unbiased, rapid, scalable, and quantitative in information extraction. Hence, we aimed to summarize the most relevant urban spectral indices by focusing on multispectral, thermal, and nighttime lights indices. We use the search terms "urban index", "built-up index", "normalized difference built-up area (NDBI )", "impervious surface index", and "spectral urban index" to collect relevant literature from the "Web of Science Core Collection" database. We found that all urban spectral indices developed since 2003, except NDBI. This review will help understand the applications of urban spectral indices, the selection of indices based on available spectral bands, and their merits and demerits.
近二十年来，城市光谱指数在城市土地利用、土地覆被研究中通过制图、估算、变化检测、时间序列分析、城市动态、监测、建模等方面取得了可喜的进展。遥感光谱指数在信息提取方面具有无监督、无偏、快速、可扩展、定量等特点。因此，我们的目标是总结最相关的城市光谱指数，重点关注多光谱、热和夜间灯光指数。我们使用“城市指数”、“建成区指数”、“归一化差异建成区(NDBI)”、“不透水面指数”和“光谱城市指数”等关键词从“Web of Science Core Collection”数据库中检索相关文献。我们发现，除NDBI外，所有城市光谱指数都是自2003年以来发展起来的。本文综述了城市光谱指数的应用、基于现有光谱波段的指数选择及其优缺点。
{"title":"Review of Spectral Indices for Urban Remote Sensing","authors":"Akib Javed, Q. Cheng, Hao Peng, O. Altan, Yan Li, I. Ara, Enamul Huq, Yeamin Ali, Nayyer Saleem","doi":"10.14358/pers.87.7.513","DOIUrl":"https://doi.org/10.14358/pers.87.7.513","url":null,"abstract":"Urban spectral indices have made promising improvements in the last two decades in urban land use land cover studies through mapping, estimation, change detection, time-series analyzing, urban dynamics, monitoring, modeling, and so on. Remote sensing spectral indices are unsupervised,\u0000 unbiased, rapid, scalable, and quantitative in information extraction. Hence, we aimed to summarize the most relevant urban spectral indices by focusing on multispectral, thermal, and nighttime lights indices. We use the search terms \"urban index\", \"built-up index\", \"normalized difference\u0000 built-up area (NDBI )\", \"impervious surface index\", and \"spectral urban index\" to collect relevant literature from the \"Web of Science Core Collection\" database. We found that all urban spectral indices developed since 2003, except NDBI. This review will help understand the applications of\u0000 urban spectral indices, the selection of indices based on available spectral bands, and their merits and demerits.","PeriodicalId":49702,"journal":{"name":"Photogrammetric Engineering and Remote Sensing","volume":"51 201 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83286199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mujie Li, Zezhong Zheng, Mingcang Zhu, Yue He, Jun Xia, Xueye Chen, Q. Peng, Yong He, Xiang Zhang, Pengshan Li
The spatiotemporal evolution of an impervious surface (IS) is significant for urban planning. In this paper, the IS was extracted and its spatiotemporal evolution for the Chengdu urban area was analyzed based on Landsat imagery. Our experimental results indicated that convolutional neural networks achieved the better performance with an overall accuracy of 98.32%, Kappa coefficient of 0.98, and Macro F1 of 98.28%, and the farmland was replaced by IS from 2001 to 2017, and the IS area (ISA) increased by 51.24 km2; that is, the growth rate was up to 13.8% in sixteen years. According to the landscape metrics, the IS expanded and agglomerated into large patches from small fragmented ones. In addition, the gross domestic product change of the secondary industry was similar to the change of ISA between 2001 and 2017. Thus, the spatiotemporal evolution of IS was associated with the economic development of the Chengdu urban area in the past sixteen years.
{"title":"The Spatiotemporal Evolution of Urban Impervious Surface for Chengdu, China","authors":"Mujie Li, Zezhong Zheng, Mingcang Zhu, Yue He, Jun Xia, Xueye Chen, Q. Peng, Yong He, Xiang Zhang, Pengshan Li","doi":"10.14358/pers.87.7.491","DOIUrl":"https://doi.org/10.14358/pers.87.7.491","url":null,"abstract":"The spatiotemporal evolution of an impervious surface (IS) is significant for urban planning. In this paper, the IS was extracted and its spatiotemporal evolution for the Chengdu urban area was analyzed based on Landsat imagery. Our experimental results indicated that convolutional\u0000 neural networks achieved the better performance with an overall accuracy of 98.32%, Kappa coefficient of 0.98, and Macro F1 of 98.28%, and the farmland was replaced by IS from 2001 to 2017, and the IS area (ISA) increased by 51.24 km2; that is, the growth rate was up to 13.8% in\u0000 sixteen years. According to the landscape metrics, the IS expanded and agglomerated into large patches from small fragmented ones. In addition, the gross domestic product change of the secondary industry was similar to the change of ISA between 2001 and 2017. Thus, the spatiotemporal evolution\u0000 of IS was associated with the economic development of the Chengdu urban area in the past sixteen years.","PeriodicalId":49702,"journal":{"name":"Photogrammetric Engineering and Remote Sensing","volume":"67 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76070767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Thenkabail, I. Aneece, P. Teluguntla, A. Oliphant
{"title":"Hyperspectral Narrowband Data Propel Gigantic Leap in the Earth Remote Sensing","authors":"P. Thenkabail, I. Aneece, P. Teluguntla, A. Oliphant","doi":"10.14358/PERS.87.7.461","DOIUrl":"https://doi.org/10.14358/PERS.87.7.461","url":null,"abstract":"","PeriodicalId":49702,"journal":{"name":"Photogrammetric Engineering and Remote Sensing","volume":"77 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79544494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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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