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首页> 外文期刊>ISPRS Journal of Photogrammetry and Remote Sensing >Determination of the crop row orientations from Formosat-2 multi-temporal and panchromatic images
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Determination of the crop row orientations from Formosat-2 multi-temporal and panchromatic images

机译:从Formosat-2多时相和全色图像确定作物行方向

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摘要

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 > R~2 > 0.99 and 7.15° > RMSE > 43.02°). For the summer crops (sunflower, corn and hemp), results are strongly crop and date dependents (0 > R~2 > 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.
机译:本文提出了一种技术,用于在专门用于农业的人类土地上获取作物行的方向,以进一步改善对作物产量和土壤侵蚀管理的估计。考虑了五种作物类型:小麦,大麦,油菜籽,向日葵,玉米和大麻。该研究是多传感器作物监测实验的一部分,该实验于2010年整个农业季节(MCM'10)在法国西南部图卢兹附近的地区进行。所提出的方法是基于使用由Formosat-2采集的卫星图像,该图像在全色和多光谱模式下具有较高的空间分辨率(分别为2 m和8 m的空间分辨率)。使用方向性空间滤镜(45°和135°)和数学形态学算法,可以导出和评估每个图像和每个图的方向。考虑了“单日期”和“多时间”方法。单日期分析证实了该方法的良好性能,但强调了仅用一个日期来估计整个景观中作物行方向的方法的局限性。多日期分析允许(1)确定最合适的农业时段以检测行方向,并且(2)将估算范围扩展到研究区域的整个足迹。对于冬季作物(小麦,大麦和油菜籽),当收获后,表面覆盖有麦茬或深耕时(0.27> R〜2> 0.99和7.15°> RMSE> 43.02°)。对于夏季作物(向日葵,玉米和大麻),结果与作物和日期密切相关(0> R〜2> 0.96,10.22°> RMSE> 80°),对开花,灌溉设备和/或最大程度地发展作物。最后,该方法在整个研究区域的范围允许绘制90%的农作物行方向(大于45,000公顷),且误差小于40°,与每个农业样地的置信指数范围为1-5。

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