کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8876091 | 1623712 | 2017 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Developing crop specific area frame stratifications based on geospatial crop frequency and cultivation data layers
ترجمه فارسی عنوان
کشف الگوهای کشش محدوده خاص محصول براساس فرکانس محصول جغرافیایی و لایه داده های کشت
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کلمات کلیدی
لایه داده کاشت گیاه لایه داده های فرکانس کاشت محصول، طبقه بندی خودکار، طبقه بندی ویژه محصولات طبقه بندی چند محصول،
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم کشاورزی و بیولوژیک (عمومی)
چکیده انگلیسی
Area Sampling Frames (ASFs) are the basis of many statistical programs around the world. To improve the accuracy, objectivity and efficiency of crop survey estimates, an automated stratification method based on geospatial crop planting frequency and cultivation data is proposed. This paper investigates using 2008-2013 geospatial corn, soybean and wheat planting frequency data layers to create three corresponding single crop specific and one multi-crop specific South Dakota (SD) U.S. ASF stratifications. Corn, soybeans and wheat are three major crops in South Dakota. The crop specific ASF stratifications are developed based on crop frequency statistics derived at the primary sampling unit (PSU) level based on the Crop Frequency Data Layers. The SD corn, soybean and wheat mean planting frequency strata of the single crop stratifications are substratified by percent cultivation based on the 2013 Cultivation Layer. The three newly derived ASF stratifications provide more crop specific information when compared to the current National Agricultural Statistics Service (NASS) ASF based on percent cultivation alone. Further, a multi-crop stratification is developed based on the individual corn, soybean and wheat planting frequency data layers. It is observed that all four crop frequency based ASF stratifications consistently predict corn, soybean and wheat planting patterns well as verified by the 2014 Farm Service Agency (FSA) Common Land Unit (CLU) and 578 administrative data. This demonstrates that the new stratifications based on crop planting frequency and cultivation are crop type independent and applicable to all major crops. Further, these results indicate that the new crop specific ASF stratifications have great potential to improve ASF accuracy, efficiency and crop estimates.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Integrative Agriculture - Volume 16, Issue 2, February 2017, Pages 312-323
Journal: Journal of Integrative Agriculture - Volume 16, Issue 2, February 2017, Pages 312-323
نویسندگان
Claire G. Boryan, Zhengwei Yang, Patrick Willis, Liping Di,