Spatial heterogeneity of keyhole imagery coverage in China and imagery dataset cost estimation
Abstract Keyhole imagery documented global surface from 1960 to 1980s and has contributed to earth surface change research, while evaluation of its’ coverage spatial heterogeneity is rare. In this work the boundary vectors with attributes of all freely Keyhole images within China were obtained from...
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-81566-w |
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| author | Hao Li Weiqi Yao Mengru Zhang Xiaoyue Yang Qian Wang |
| author_facet | Hao Li Weiqi Yao Mengru Zhang Xiaoyue Yang Qian Wang |
| author_sort | Hao Li |
| collection | DOAJ |
| description | Abstract Keyhole imagery documented global surface from 1960 to 1980s and has contributed to earth surface change research, while evaluation of its’ coverage spatial heterogeneity is rare. In this work the boundary vectors with attributes of all freely Keyhole images within China were obtained from USGS website to automatically investigate the spatial coverage characteristics using the ArcPy library in Python. Images were categorized into meter-level (C1), five-meter-level (C2), and ten-meter-level (C3). The resolution and spatial coverage distribution of Keyhole imagery at national and provincial levels were investigated using geostatistical and statistical methods. Combining coverage area of free imagery and the costs of non-free imagery, the cost of Keyhole datasets construction was calculated. The results indicated: (1) the coverage of C1, C2, and C3 across China was 58%, 95%, and 76%, respectively. The average number of coverages were 4.9, 4.5, and 3.6 times, respectively, with variation coefficients of 0.7, 1.3, and 1.3. All of C1, C2, and C3 imageries exhibited significant global and local spatial clustering characteristics. (3) The acquisition costs for datasets with triple coverage of C1, C2, and C3 imagery in China were 103, 103, and 23 thousand dollars, respectively. We demonstrated how the large data amount Keyhole imagery that could not analyzed manually were automatically reorganized using the metadata, to facilitate the spatial distribution and cost estimation analysis. |
| format | Article |
| id | doaj-art-41114c69fa9244968a46dc7a3c01a8b5 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-41114c69fa9244968a46dc7a3c01a8b52025-01-05T12:18:57ZengNature PortfolioScientific Reports2045-23222025-01-0115111410.1038/s41598-024-81566-wSpatial heterogeneity of keyhole imagery coverage in China and imagery dataset cost estimationHao Li0Weiqi Yao1Mengru Zhang2Xiaoyue Yang3Qian Wang4School of Geography and Environment, Liaocheng UniversitySchool of Geography and Environment, Liaocheng UniversitySchool of Geography and Environment, Liaocheng UniversitySchool of Geography and Environment, Liaocheng UniversitySchool of Geography and Environment, Liaocheng UniversityAbstract Keyhole imagery documented global surface from 1960 to 1980s and has contributed to earth surface change research, while evaluation of its’ coverage spatial heterogeneity is rare. In this work the boundary vectors with attributes of all freely Keyhole images within China were obtained from USGS website to automatically investigate the spatial coverage characteristics using the ArcPy library in Python. Images were categorized into meter-level (C1), five-meter-level (C2), and ten-meter-level (C3). The resolution and spatial coverage distribution of Keyhole imagery at national and provincial levels were investigated using geostatistical and statistical methods. Combining coverage area of free imagery and the costs of non-free imagery, the cost of Keyhole datasets construction was calculated. The results indicated: (1) the coverage of C1, C2, and C3 across China was 58%, 95%, and 76%, respectively. The average number of coverages were 4.9, 4.5, and 3.6 times, respectively, with variation coefficients of 0.7, 1.3, and 1.3. All of C1, C2, and C3 imageries exhibited significant global and local spatial clustering characteristics. (3) The acquisition costs for datasets with triple coverage of C1, C2, and C3 imagery in China were 103, 103, and 23 thousand dollars, respectively. We demonstrated how the large data amount Keyhole imagery that could not analyzed manually were automatically reorganized using the metadata, to facilitate the spatial distribution and cost estimation analysis.https://doi.org/10.1038/s41598-024-81566-wKeyhole imagery1960 ~ 1980sAutomationResolutionSpatial distribution characteristics |
| spellingShingle | Hao Li Weiqi Yao Mengru Zhang Xiaoyue Yang Qian Wang Spatial heterogeneity of keyhole imagery coverage in China and imagery dataset cost estimation Scientific Reports Keyhole imagery 1960 ~ 1980s Automation Resolution Spatial distribution characteristics |
| title | Spatial heterogeneity of keyhole imagery coverage in China and imagery dataset cost estimation |
| title_full | Spatial heterogeneity of keyhole imagery coverage in China and imagery dataset cost estimation |
| title_fullStr | Spatial heterogeneity of keyhole imagery coverage in China and imagery dataset cost estimation |
| title_full_unstemmed | Spatial heterogeneity of keyhole imagery coverage in China and imagery dataset cost estimation |
| title_short | Spatial heterogeneity of keyhole imagery coverage in China and imagery dataset cost estimation |
| title_sort | spatial heterogeneity of keyhole imagery coverage in china and imagery dataset cost estimation |
| topic | Keyhole imagery 1960 ~ 1980s Automation Resolution Spatial distribution characteristics |
| url | https://doi.org/10.1038/s41598-024-81566-w |
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