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基于随机森林的耕地利用效率测度模型构建及其应用

1. 1. 华中科技大学公共管理学院,武汉 430074
2. 华中师范大学公共管理学院,武汉 430079
• 收稿日期:2018-11-12 修回日期:2019-03-18 出版日期:2019-06-20 发布日期:2019-06-20
• 作者简介:

作者简介：陈丹玲（1993- ）,女,江苏徐州人,博士研究生,研究方向为土地利用与管理。E-mail: hustcdl93@163.com

• 基金资助:
国家自然科学基金项目（71673096）;国家社会科学基金项目（16CGL054）

Measurement of cultivated land utilization efficiency: Construction and application of random forest

Dan-ling CHEN1(), Xin-hai LU2(), Bing KUANG2

1. 1. College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China
2. College of Public Administration, Central China Normal University, Wuhan 430079, China
• Received:2018-11-12 Revised:2019-03-18 Online:2019-06-20 Published:2019-06-20

Abstract:

Setting up a suitable quantitative analysis model is a basic work for scientific grasp of cultivated land utilization efficiency and its distribution pattern, and can provide reasonable decision-making basis for sustainable utilization of cultivated land then realizing the coordinated development of cultivated resources and environment. In order to effectively describe the complexity, dynamics and heterogeneity characteristics of cultivated land use system, a random forest (RF) model for measuring cultivated land utilization efficiency is constructed by applying random sampling Bootstrap to build a classification tree reasonably. Then by taking 172 cities in the major grain producing areas of China as an example, the RF model was trained to measure the cultivated land utilization efficiency in 2003-2015 compared with Back Propagation Neural Network and Entropy weight to verify the consistency, representative and superiority of RF. The results show that: (1) RF model has fewer parameters and simpler implementation. It can simulate the complex relations among the evaluation indexes, which makes it convenient to analyze the value of each index. (2) For efficiency measurement results of the same space unit, RF > BPNN > EW, the overall distribution pattern of the cultivated land utilization efficiency in RF and BPNN is similar while a great difference exists in EW. (3) Judged from the matching degree of evaluation results to reality and the accuracy parameters, the measurement results are reasonable and in accordance with the facts in RF, which reflected its high applicability and reliability. At the same time, compared with the other two commonly used models, RF can reduce the dimensions of input vectors and the computing complexity, then raise the training efficiency. The correlation coefficient R of RF is 0.8685, MRPD is 2.3533, with the minimum MMSE and MMAE being 0.0174 and 0.0211, respectively, which is more suitable for the study of the cultivated land utilization efficiency with complex nonlinear characteristics, and this method has explored a new way for evaluating cultivated land utilization efficiency.