First Large Extent and High Resolution Cropland and Crop Type Map of Argentina

D. de Abelleyra, S. Verón, S. Banchero, M. J. Mosciaro, T. Propato, A. Ferraina, M. Taffarel, L. Dacunto, A. Franzoni, J. Volante
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引用次数: 4

Abstract

The availability of spatially explicit information about agricultural crops for large regions in Argentina is scarce. In particular, due to temporal dynamics of agricultural production (i.e., changes in planted crops from year to year) and spectral similarities among herbaceous crops it is difficult to generate crop type maps from remote sensing. Large regions with marked climatic variations, like the main agricultural areas of Argentina, represent an additional challenge. Here we generated a map based on supervised classifications using field samples along 14 agricultural zones. Best classification accuracies were obtained by combining seasonal indices (year, summer and winter), with indices that describe the temporal dynamics of vegetation. Accuracy was increased at regions with high and balanced number of samples and with longer growing seasons. The map allows to identify areas with clusters of one, two or three crops and to characterize areas with different spatial distribution between cropland and no cropland areas.
阿根廷首张大范围高分辨率农田和作物类型地图
可获得的关于阿根廷大片地区农作物的空间明确信息很少。特别是,由于农业生产的时间动态(即种植作物每年的变化)和草本作物之间的光谱相似性,很难通过遥感生成作物类型图。气候变化明显的大片地区,如阿根廷的主要农业区,是另一个挑战。在这里,我们使用14个农业区的田间样本生成了基于监督分类的地图。将季节指数(年、夏、冬)与描述植被时间动态的指数相结合,分类精度最高。在样品数量多、数量均衡和生长季节较长的地区,准确性提高。该地图可以识别一种、两种或三种作物聚集的地区,并描绘出有农田和无农田之间空间分布不同的地区的特征。
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