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Automated geometric correction of multispectral images from High Resolution CCD Camera (HRCC) on-board CBERS-2 and CBERS-2B |
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| Institution: | 1. Electrical Engineering and Computer Science Department, South Dakota State University, SDEH 213, Box 2222, Brookings, SD 57007, United States;2. Microsoft Corporation, Bing Imagery Technologies R&D, Boulder, CO 80302, United States;1. School of Engineering and ICT, University of Tasmania, Private Bag 65, Sandy Bay, Tasmania 7001, Australia;2. Discipline of Geography and Spatial Sciences, School of Land and Food, University of Tasmania, Private Bag 76, Sandy Bay, Tasmania 7001, Australia;3. School of Physical Sciences, University of Tasmania, Private Bag 37, Sandy Bay, Tasmania 7001, Australia;4. Forestry Tasmania, 79 Melville St, Hobart, TAS 7000, Australia;1. The Galilee Society, the Arab National Society for Health Research & Services, Shefa-Amr, Israel;2. Nursing Department, Zefat Academic College, 11 Jerusalem St., PO Box 160, Zefat 13206, Israel;1. Departamento de Ingeniería Gráfica y Geomática, Escuela Técnica Superior de Ingenieros Agrónomos y Montes, Universidad de Córdoba, Campus Rabanales, N-IV, km 396, Córdoba 14071, Spain;2. División de Estudios de Posgrado e Investigación – Ingeniería Ambiental, Instituto Tecnológico de Culiacán, Juan de Dios Batíz 310, Col. Guadalupe, 80220, Culiacán, Sinaloa, Mexico;1. FAENG, UFMS – Universidade Federal de Mato Grosso do Sul, Campus Universitário, 79070-900 Campo Grande, Brazil;2. Department of Cartography, UNESP – Univ Estadual Paulista, Rua Roberto Simonsen 305, 19060-900 Presidente Prudente, Brazil;1. Laboratory for Analysis of the Biosphere (LAB), Dpt. of Environmental Sciences and Renewable Natural Resources, University of Chile, Av. Santa Rosa 11315, La Pintana, Santiago, Chile;2. Geomatics and Landscape Ecology Lab, Forestry and Nature Conservation Faculty, University of Chile, Av. Santa Rosa 11315, La Pintana, Santiago, Chile;3. Spatial Operation Group, Chilean Air Force, Volcán Osorno s/n, El Bosque, Santiago, Chile |
| Abstract: | China–Brazil Earth Resource Satellite (CBERS) imagery is identified as one of the potential data sources for monitoring Earth surface dynamics in the event of a Landsat data gap. Currently available multispectral images from the High Resolution CCD (Charge Coupled Device) Camera (HRCC) on-board CBERS satellites (CBERS-2 and CBERS-2B) are not precisely geo-referenced and orthorectified. The geometric accuracy of the HRCC multispectral image product is found to be within 2–11 km. The use of CBERS-HRCC multispectral images to monitor Earth surface dynamics therefore necessitates accurate geometric correction of these images. This paper presents an automated method for geo-referencing and orthorectifying the multispectral images from the HRCC imager on-board CBERS satellites. Landsat Thematic Mapper (TM) Level 1T (L1T) imagery provided by the U.S. Geological Survey (USGS) is employed as reference for geometric correction. The proposed method introduces geometric distortions in the reference image prior to registering it with the CBERS-HRCC image. The performance of the geometric correction method was quantitatively evaluated using a total of 100 images acquired over the Andes Mountains and the Amazon rainforest, two areas in South America representing vastly different landscapes. The geometrically corrected HRCC images have an average geometric accuracy of 17.04 m (CBERS-2) and 16.34 m (CBERS-2B). While the applicability of the method for attaining sub-pixel geometric accuracy is demonstrated here using selected images, it has potential for accurate geometric correction of the entire archive of CBERS-HRCC multispectral images. |
| Keywords: | CBERS Orthorectification Geometric correction Geo-referencing Image registration Multi-temporal change |
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