农业机械学报2018，Vol.49Issue(5)：218-225,8.DOI:10.6041/j.issn.1000-1298.2018.05.025
基于时序光谱和高分纹理分析的制种玉米田遥感识别
Seed Maize Field Identification Based on Analysis of Remote Sensing Timing Spectrum and High Resolution Texture
摘要
Abstract
Using remote sensing technology to rapidly and accurately differentiate the seed maize fields and grain maize fields is the urgent need of seed production and market supervision,and also is an important aspect of the research on the classification and planting mode of crops by using remote sensing to monitor.Based on the spectral and texture differences of seed maize and other crops in the high resolution remote sensing image,the multi-source remote sensing data were used,including GF-1 WFV multi-spectral image,Landsat80LI image and GF-2 PMS full-color image to extract the seed maize fields as research target,the vegetation index system of crop multi-temporal spectral characteristics was proposed,which multidimensionally reflected different spectral differences between crops;and adding the image rotation invariant processing before the texture detection,to solve the problem of crop field texture direction in remote sensing image;finally,the identification method system of seed maize fields based on multi-temporal spectral feature and LBP-GLCM texture feature in high spatial resolution remote sensing image were established.Qitai County,Xinjiang Uygur Autonomous Region was taken as the study area to verify,based on the above method and the random forest classifier,the overall accuracy was 90.57％,the Kappa coefficient was 0.79.The accuracy of the classification results of seed maize field was 99.20％,and the mapping accuracy was 86.68％,which basically satisfied the needs of seed maize recognition requirements.The research result not only provided a method for the monitoring of hybrid maize seed production in China,but also provided a technical reference for monitoring and supervision of hybrid seed field with the same planting system.关键词
制种玉米田/多源遥感/植被指数/LBP-GLCM纹理/随机森林Key words
seed maize fields/multi-source remote sensing/vegetation index/LBP-GLCM texture/random forest分类
农业科技引用本文复制引用
张超,乔敏,刘哲,刘帝佑,金虹杉,朱德海..基于时序光谱和高分纹理分析的制种玉米田遥感识别[J].农业机械学报,2018,49(5):218-225,8.基金项目
国家高技术研究发展计划(863计划)项目(2013AA10230103) （863计划）
