Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture
Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture
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恢复作物成分的预测分布：方法及其在肯塔基州农业中的应用
作者：
GwanSeon Kim;M. Nemati;Steven Buck;Nicholas Pates;T. Mark
本文提出了一种利用农田数据层和田级边界的多项Logit(MNL)模型来估计作物转移概率的新应用，并利用该模型生成了肯塔基州五种主要作物的总种植面积的预测分布。这些预报分布具有广泛的应用范围，除了在6月份种植面积调查之前提供中期种植面积估计外，还可以告知生产者将新作物纳入土地利用轮作的能力、对特定地点资本和投入分配的投资以及营养物质流失导致不利水质事件的可能性。
This paper proposes a novel application of the multinomial logit (MNL) model using Cropland Data Layer and field-level boundaries to estimate crop transition probabilities, which are used to generate forecast distributions of total acreage for five major crops produced in the state of Kentucky. These forecasts distributions have a wide range of applications that, besides providing interim acreage estimates ahead of the June Acreage Survey, can inform the ability of producers to incorporate new crops in the land-use rotation, investments in location-specific capital and input distribution as well informing the likelihood of adverse water quality events from nutrient run-off.