期刊论文

Extraction of paddy rice based on convolutional neural network using multi-source remote sensing data

中文

自然资源遥感

2097-034X

2020

32

04

97-104

10.6046/gtzyyg.2020.04.14

国家自然科学基金项目“洞庭湖湿地NPP反演模型优化及其时空变化驱动机制研究”（编号:41901385）资助；

本校为第一机构

水稻是中国种植面积最广泛的粮食作物之一,适时、准确的水稻识别与监测对于国家粮食安全和农用地空间格局演变具有重要意义。基于水稻物候关键期的多时相Sentinel-2A光谱数据、植被指数、植被丰度以及基于Landsat8反演得到的地表温度(land surface temperature,LST),采用卷积神经网络(convolutional neural network,CNN)、支持向量机(support vector machine,SVM)和随机森林(random forest,RF)算法对高异质化的长株潭核心区的水稻进行了提取,并得到了对应的水稻填图。研究结果显示,利用多时相多源遥感数据通过CNN算法能够有效提取高异质化程度区域的水稻信息,水稻分类总体精度(overall accuracy...

Rice is one of the most widely planted food crops in China.Therefore,timely and accurate rice identification and monitoring is of great significance to the national food security and the evolution of agricultural land spatial pattern.In this study,multi-temporal Sentinel-2A multispectral images,vegetation indices,vegetation abundance and Landsat 8 derived LST on the critical period of rice phenology were used.The CNN,SVM and RF classifiers were applied to extracting the paddy rice and finally the paddy rice map was obtained.The result shows that using multi-temporal and multi-source remote sen...