The inability of a farmer to plant an insured crop by the policy’s final planting date can pose financial challenges for the grower and cause reduced production for a widely impacted region. Prevented planting is primarily caused by excess moisture or rainfall such as the catastrophic flooding and widespread conditions that prevented active field work in the midwestern region of United States in 2019. While the Farm Service Agency reports the number of such “prevent plant” acres each year at the county scale, field-scale maps of prevent plant fields—which would enable analyses related to assessing and mitigating the impact of climate on agriculture—are not currently available. The aim of this study is to demonstrate a method for mapping likely prevent plant fields based on flood mapping and historical cropland maps. We focused on a study region in eastern South Dakota and created flood maps using Landsat 8 and Sentinel 1 images from 2018 and 2019. We used automatic threshold-based change detection using NDVI and NDWI to accentuate changes likely caused by flooding. The NDVI change detection map showed vegetation loss in the eastern parts of the study area while NDWI values showed increased water content, both indicating possible flooding events. The VH polarization of Sentinel 1 was also particularly useful in identifying potential flooded areas as the VH values for 2019 were substantially lower than those of 2018, especially in the northern part of the study area, likely indicating standing water or reduced biomass. We combined the flood maps from Landsat 8 and Sentinel 1 to form a complete flood likelihood map over the entire study area. We intersected this flood map with a map of fallow pixels extracted from the Cropland Data Layer to produce a map of predicted prevent plant acres across several counties in South Dakota. The predicted figures were within 10% error of Farm Service Agency reports, with low errors in the most affected counties in the state such as Beadle, Hanson, and Hand.

中文翻译：

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使用遥感技术绘制 2019 年防止南达科他州种植英亩的位置和范围

如果农民无法在保单的最终种植日期之前种植受保作物，可能会给种植者带来财务挑战，并导致受广泛影响的地区减产。受阻种植主要是由于水分过多或降雨过多造成的，例如 2019 年美国中西部地区发生的灾难性洪水和广泛的条件阻止了积极的田间工作。虽然农场服务局每年报告此类“预防植物”的英亩数在县级范围内，目前还没有可用于评估和减轻气候对农业影响的相关分析的预防植物田的田间规模地图。本研究的目的是展示一种基于洪水绘图和历史农田地图绘制可能阻止植物田的绘图方法。我们专注于南达科他州东部的一个研究区域，并使用 2018 年和 2019 年的 Landsat 8 和 Sentinel 1 图像创建了洪水地图。我们使用 NDVI 和 NDWI 使用基于阈值的自动变化检测来强调可能由洪水引起的变化。NDVI 变化检测图显示研究区东部植被减少，而 NDWI 值显示含水量增加，均表明可能发生洪水事件。Sentinel 1 的 VH 极化对于识别潜在的洪水区域也特别有用，因为 2019 年的 VH 值大大低于 2018 年的值，尤其是在研究区域的北部，可能表明存在积水或生物量减少。我们将 Landsat 8 和 Sentinel 1 的洪水地图结合起来，形成了整个研究区域的完整洪水可能性图。我们将这张洪水地图与从农田数据层中提取的休耕像素地图相交，以生成南达科他州几个县的预测种植面积地图。预测数字与农场服务机构报告的误差在 10% 以内，该州受影响最严重的县（如 Beadle、Hanson 和 Hand）的误差较小。