Determination of the crop row orientations from Formosat-2 multi-temporal and panchromatic images |
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| Institution: | 1. Dept. Geology, Eduardo Mondlane University, CP 257 Maputo, Mozambique;2. Vale Moçambique, Moatize, Tete, Mozambique;1. College of Animal Science and Technology, Northwest A&F University, Shaanxi Key Laboratory of Molecular Biology for Agriculture, Yangling, Shaanxi 712100, China;2. College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China;3. Institute of Beijing Animal Science and Veterinary, Chinese Academy of Agricultural Science, Beijing 100194, China;1. Department of Physics, Civil Aviation Flight University of China, Guanghan, People''s Republic of China;2. Department of Material Science, Sichuan University, Chengdu 61004, People''s Republic of China;1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China;2. Changchun Jingyuetan Remote Sensing Test Site, Chinese Academy of Sciences, Changchun, 130102, China;3. University of Chinese Academy of Sciences, Beijing, 100049, China |
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| Abstract: | This paper presents a technique developed for the retrieval of the orientation of crop rows, over anthropic lands dedicated to agriculture in order to further improve estimate of crop production and soil erosion management. Five crop types are considered: wheat, barley, rapeseed, sunflower, corn and hemp. The study is part of the multi-sensor crop-monitoring experiment, conducted in 2010 throughout the agricultural season (MCM’10) over an area located in southwestern France, near Toulouse. The proposed methodology is based on the use of satellite images acquired by Formosat-2, at high spatial resolution in panchromatic and multispectral modes (with spatial resolution of 2 and 8 m, respectively). Orientations are derived and evaluated for each image and for each plot, using directional spatial filters (45° and 135°) and mathematical morphology algorithms. “Single-date” and “multi-temporal” approaches are considered. The single-date analyses confirm the good performances of the proposed method, but emphasize the limitation of the approach for estimating the crop row orientation over the whole landscape with only one date. The multi-date analyses allow (1) determining the most suitable agricultural period for the detection of the row orientations, and (2) extending the estimation to the entire footprint of the study area. For the winter crops (wheat, barley and rapeseed), best results are obtained with images acquired just after harvest, when surfaces are covered by stubbles or during the period of deep tillage (0.27 > R2 > 0.99 and 7.15° > RMSE > 43.02°). For the summer crops (sunflower, corn and hemp), results are strongly crop and date dependents (0 > R2 > 0.96, 10.22° > RMSE > 80°), with a well-marked impact of flowering, irrigation equipment and/or maximum crop development. Last, the extent of the method to the whole studied zone allows mapping 90% of the crop row orientations (more than 45,000 ha) with an error inferior to 40°, associated to a confidence index ranging from 1 to 5 for each agricultural plot. |
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| Keywords: | Crop monitoring Crop row orientation Mathematical morphology Directional filtering Satellite image Formosat-2 Panchromatic |
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