Spatial Optimization of Agricultural Land Use Based on Cross-Entropy Method

An integrated optimization model was developed for the spatial distribution of agricultural crops in order to efficiently utilize agricultural water and land resources simultaneously. The model is based on the spatial distribution of crop suitability, spatial distribution of population density, and...

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Main Authors: Lina Hao, Xiaoling Su, Vijay P. Singh, Olusola O. Ayantobo
Format: Article
Language:English
Published: MDPI AG 2017-11-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/19/11/592
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spelling doaj-ba5d2a358f89434796d18e22272ba8572020-11-25T00:49:50ZengMDPI AGEntropy1099-43002017-11-01191159210.3390/e19110592e19110592Spatial Optimization of Agricultural Land Use Based on Cross-Entropy MethodLina Hao0Xiaoling Su1Vijay P. Singh2Olusola O. Ayantobo3College of Water Resources and Architectural Engineering, Northwest A & F University, Yangling 712100, ChinaCollege of Water Resources and Architectural Engineering, Northwest A & F University, Yangling 712100, ChinaDepartment of Biological & Agricultural Engineering and Zachry Department of Civil Engineering, Texas A & M University, College Station, TX 77843-2117, USACollege of Water Resources and Architectural Engineering, Northwest A & F University, Yangling 712100, ChinaAn integrated optimization model was developed for the spatial distribution of agricultural crops in order to efficiently utilize agricultural water and land resources simultaneously. The model is based on the spatial distribution of crop suitability, spatial distribution of population density, and agricultural land use data. Multi-source remote sensing data are combined with constraints of optimal crop area, which are obtained from agricultural cropping pattern optimization model. Using the middle reaches of the Heihe River basin as an example, the spatial distribution of maize and wheat were optimized by minimizing cross-entropy between crop distribution probabilities and desired but unknown distribution probabilities. Results showed that the area of maize should increase and the area of wheat should decrease in the study area compared with the situation in 2013. The comprehensive suitable area distribution of maize is approximately in accordance with the distribution in the present situation; however, the comprehensive suitable area distribution of wheat is not consistent with the distribution in the present situation. Through optimization, the high proportion of maize and wheat area was more concentrated than before. The maize area with more than 80% allocation concentrates on the south of the study area, and the wheat area with more than 30% allocation concentrates on the central part of the study area. The outcome of this study provides a scientific basis for farmers to select crops that are suitable in a particular area.https://www.mdpi.com/1099-4300/19/11/592cross-entropy minimizationland suitability evaluationspatial optimization
collection DOAJ
language English
format Article
sources DOAJ
author Lina Hao
Xiaoling Su
Vijay P. Singh
Olusola O. Ayantobo
spellingShingle Lina Hao
Xiaoling Su
Vijay P. Singh
Olusola O. Ayantobo
Spatial Optimization of Agricultural Land Use Based on Cross-Entropy Method
Entropy
cross-entropy minimization
land suitability evaluation
spatial optimization
author_facet Lina Hao
Xiaoling Su
Vijay P. Singh
Olusola O. Ayantobo
author_sort Lina Hao
title Spatial Optimization of Agricultural Land Use Based on Cross-Entropy Method
title_short Spatial Optimization of Agricultural Land Use Based on Cross-Entropy Method
title_full Spatial Optimization of Agricultural Land Use Based on Cross-Entropy Method
title_fullStr Spatial Optimization of Agricultural Land Use Based on Cross-Entropy Method
title_full_unstemmed Spatial Optimization of Agricultural Land Use Based on Cross-Entropy Method
title_sort spatial optimization of agricultural land use based on cross-entropy method
publisher MDPI AG
series Entropy
issn 1099-4300
publishDate 2017-11-01
description An integrated optimization model was developed for the spatial distribution of agricultural crops in order to efficiently utilize agricultural water and land resources simultaneously. The model is based on the spatial distribution of crop suitability, spatial distribution of population density, and agricultural land use data. Multi-source remote sensing data are combined with constraints of optimal crop area, which are obtained from agricultural cropping pattern optimization model. Using the middle reaches of the Heihe River basin as an example, the spatial distribution of maize and wheat were optimized by minimizing cross-entropy between crop distribution probabilities and desired but unknown distribution probabilities. Results showed that the area of maize should increase and the area of wheat should decrease in the study area compared with the situation in 2013. The comprehensive suitable area distribution of maize is approximately in accordance with the distribution in the present situation; however, the comprehensive suitable area distribution of wheat is not consistent with the distribution in the present situation. Through optimization, the high proportion of maize and wheat area was more concentrated than before. The maize area with more than 80% allocation concentrates on the south of the study area, and the wheat area with more than 30% allocation concentrates on the central part of the study area. The outcome of this study provides a scientific basis for farmers to select crops that are suitable in a particular area.
topic cross-entropy minimization
land suitability evaluation
spatial optimization
url https://www.mdpi.com/1099-4300/19/11/592
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AT xiaolingsu spatialoptimizationofagriculturallandusebasedoncrossentropymethod
AT vijaypsingh spatialoptimizationofagriculturallandusebasedoncrossentropymethod
AT olusolaoayantobo spatialoptimizationofagriculturallandusebasedoncrossentropymethod
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