Modeled conterminous United States Crop Cover datasets for 2012

Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create crop cover maps for the CONUS for years 2000-2013 at 250 meter spatial resolution. The CCM and the maps for years 2008-2013 were assessed for accuracy relative to downscaled NASS CDLs to 250 meter. The CCM performed well against a withheld test dataset with a prediction accuracy of over 90 percent. The assessment of the crop cover maps indicated that the model performed well spatially, placing crop cover pixels within their known domains. However, the model did show a bias toward the “Other” crop cover class which caused frequent misclassifications of pixels around the periphery of large crop cover patches and of pixels that form small, sparsely dispersed crop cover patches.

作物覆盖图已广泛应用于各类研究场景。目前已有多款作物覆盖图针对特定研究需求开发而成。美国国家农业统计服务局（National Agricultural Statistics Service, NASS）农田数据图层（Cropland Data Layers, CDL）是一系列广泛使用的美国本土（conterminous United States, CONUS）作物覆盖图，时间跨度为2008年至2013年。本研究旨在通过基于分类树模型算法构建与NASS CDL风格一致的年度作物覆盖图，将NASS CDL数据集的时间覆盖范围回溯至2000年。我们使用超1100万份作物样本记录训练分类树算法，构建了作物分类模型（Crop Classification Model, CCM）。依托该模型，我们生成了2000年至2013年美国本土范围内、空间分辨率为250米的作物覆盖图。我们将2008年至2013年的NASS CDL降尺度至250米分辨率，以此为基准对CCM及同期生成的作物覆盖图进行精度评估。在保留测试集上，CCM表现优异，预测准确率超过90%。对作物覆盖图的评估结果显示，该模型在空间维度上表现良好，能够将作物覆盖像元准确归类至其已知的覆盖类别域中。但该模型对“其他”作物覆盖类别存在分类偏差，导致大型作物覆盖斑块周边的像元，以及小型、稀疏分散的作物覆盖斑块像元频繁出现错分情况。