首页> 外文会议>IEEE International Geoscience and Remote Sensing Symposium >DERIVING 2011 CULTIVATED LAND COVER DATA SETS USING USDA NATIONAL AGRICULTURAL STATISTICS SERVICE HISTORIC CROPLAND DATA LAYERS
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DERIVING 2011 CULTIVATED LAND COVER DATA SETS USING USDA NATIONAL AGRICULTURAL STATISTICS SERVICE HISTORIC CROPLAND DATA LAYERS

机译:推出2011年耕地覆盖数据集,使用美国农业部国家农业统计服务历史田间统计数据层

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This paper describes the method used to derive 30 meter resolution 2011 US cultivated data sets based on multi-year National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) data. This paper presents different sets of rules (models) to build the cultivated data sets, and a comparison of the resulting cultivated data set accuracies to the accuracies of the original CDL input data. Nine models to create 2011 cultivated data sets for nine US states are tested. Each model provides a set of rules for merging pixels of multi-year (2007-2011) CDL data. The cultivated data accuracy was assessed against in situ 2011 Farm Service Agency (FSA) Common Land Unit (CLU) data. It was found that accuracies were close among the cultivated data generated using the different models. The strongest models for all states achieved overall (producer and user) accuracies greater than 94% for cultivated and non cultivated categories.
机译:本文介绍了用于推导30米的2011年美国培育数据集的方法,基于多年国家农业统计服务(NASS)裁剪数据层(CDL)数据。本文介绍了不同规则(模型)以构建培养的数据集,并比较由此产生的培养数据设定精度到原始CDL输入数据的精度。测试了九种美国各州的2011年培育数据集的九种模型。每个模型都提供了一组用于合并多年(2007-2011)CDL数据的像素的规则。培养的数据准确性被评估,原位2011年农场服务机构(FSA)共同的土地单位(CLU)数据。发现精度在使用不同模型产生的培养数据中近距离。所有国家最强大的型号(生产者和用户)均可达到耕种和非培育类别的高于94%的精度。

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