Mapping crop phenology using NDVI time-series derived from HJ-1 A/B data |
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| Institution: | 1. Institute of Applied Remote Sensing & Information Technology, Zhejiang University, Hangzhou 310058, China;2. Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Natural Resources and Environmental Science, Zhejiang University, Hangzhou 310058, China;3. Key Laboratory of Agricultural Remote Sensing and Information System, Zhejiang Province, Hangzhou 310058, China;4. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences/Key Laboratory of Resources Remote Sensing and Digital Agriculture, Ministry of Agriculture, Beijing 100081, China;5. Geospatial Science Center of Excellence (GSCE), South Dakota State University, Brookings, SD 57007, USA;6. Lancaster Environment Centre, Lancaster University, Lancaster, UK;7. Hubei Meteorological Information and Technology Support Center, Wuhan 430074, China;8. College of Urban and Environmental Science, Northwest University, Xi’an 710127, China;1. Centre for Hydrographic Studies, CEDEX, Spain;2. Center for Spatial Technologies and Remote Sensing (CSTARS), Department of Land, Air, and Water Resources, University of California, Davis, United States;3. The National Distance Education University, UNED, Spain;4. Departamento de Silvopascicultura, ETSIM, Universidad Politécnica de Madrid, Spain;1. Geospatial Laboratory for Environmental Dynamics, University of Idaho, Moscow, ID 83844-1133, USA;2. McCall Outdoor Science School, University of Idaho, McCall, ID 83638, USA;3. USDA-ARS, Pullman, WA 99163, USA;1. Institute of Crop Science and Resource Conservation, University of Bonn, Katzenburgweg 5, D-53115 Bonn, Germany;2. Center for Development Research (ZEF), Walter-Flex-Straße 3, 53113 Bonn, Germany;3. Leibniz Centre for Agricultural Landscape Research, Institute of Landscape Systems Analysis, D-15374 Müncheberg, Germany |
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| Abstract: | With the availability of high frequent satellite data, crop phenology could be accurately mapped using time-series remote sensing data. Vegetation index time-series data derived from AVHRR, MODIS, and SPOT-VEGETATION images usually have coarse spatial resolution. Mapping crop phenology parameters using higher spatial resolution images (e.g., Landsat TM-like) is unprecedented. Recently launched HJ-1 A/B CCD sensors boarded on China Environment Satellite provided a feasible and ideal data source for the construction of high spatio-temporal resolution vegetation index time-series. This paper presented a comprehensive method to construct NDVI time-series dataset derived from HJ-1 A/B CCD and demonstrated its application in cropland areas. The procedures of time-series data construction included image preprocessing, signal filtering, and interpolation for daily NDVI images then the NDVI time-series could present a smooth and complete phenological cycle. To demonstrate its application, TIMESAT program was employed to extract phenology parameters of crop lands located in Guanzhong Plain, China. The small-scale test showed that the crop season start/end derived from HJ-1 A/B NDVI time-series was comparable with local agro-metrological observation. The methodology for reconstructing time-series remote sensing data had been proved feasible, though forgoing researches will improve this a lot in mapping crop phenology. Last but not least, further studies should be focused on field-data collection, smoothing method and phenology definitions using time-series remote sensing data. |
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| Keywords: | HJ-1 A/B NDVI time-series S-G filter Interpolation Phenology parameters |
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