引用本文:徐猛,陶建斌※,吴琪凡.基于ANN 多源遥感数据融合的耕地种植强度估算方法研究[J].中国农业信息,2019,31(6):47-60
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基于ANN 多源遥感数据融合的耕地种植强度估算方法研究
徐猛, 陶建斌※, 吴琪凡
地理过程分析与模拟湖北省重点实验室/华中师范大学城市与环境科学学院,湖北武汉430079
摘要:
【目的】文章引入“种植强度指数”的概念,对现有评价指标进行改进,利用基于遥感数据的种植强度指数实现耕地集约化利用程度的精细化表达。【方法】该文以湖北省为研究区,融合Landsat 8 遥感数据和MODIS 时间序列植被指数数据,构建了人工神经网络模型估算湖北省耕地种植强度。【结果】利用BP 神经网络提取的研究区耕地种植强度与验证样区耕地种植强度间决定系数达到0.923,证明了该研究方法的可靠性。【结论】人工神经网络模型估算方法得到的高时空融合的种植强度数据集,可为智慧农业提供技术方法和基础数据,对于耕地集约化利用的研究具有重要意义。
关键词:  种植强度;BP 神经网络;多源遥感数据
DOI:10.12105/j.issn.1672-0423.20190606
分类号:
基金项目:国家自然科学基金项目“江汉平原耕地种植强度模拟和优化研究”(41971371)
Estimating cropping intensity of croplands using multisource remote sensing data and ANN
Xu Meng, Tao Jianbin※, Wu Qifan
The College of Urban and Environmental Sciences,Central China Normal University/Key Laboratory of Geographical Processes and Simulation of Geographical Processes,Hubei Wuhan 430079,China
Abstract:
[Purpose]The concept of“ Cropping Intensity” is introduced to improve the existing evaluation indexes,and the Cropping Intensity Index based on remote sensing data is used to refine expression of intensive use of cultivated land.[Method]The Landsat 8 remote sensing data and MODIS time series vegetation index data were combined to construct an artificial neural network(ANN)model to estimate the cropping intensity of cropland in Hubei Province. [Result]The estimation accuracy based on sample area verification reaches 92.3%,which proves the reliability of the method.[Conclusion]The high-temporal fusion cropping intensity data set obtained by the method can provide technical methods and basic data for smart agriculture,which is of great significance for the study of intensive use of cultivated land.
Key words:  cropping intensity;back propagation neural network;multi-source remote sensing data