| 基于时序光谱和高分纹理分析的制种玉米田遥感识别 |
| |
| 引用本文： | 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. |
| |
| 作者姓名： | 张超 乔敏 刘哲 刘帝佑 金虹杉 朱德海 |
| |
| 作者单位： | 中国农业大学信息与电气工程学院;国土资源部农用地质量与监控重点实验室 |
| |
| 基金项目： | 国家高技术研究发展计划（863计划）项目（2013AA10230103） |
| |
| 摘 要： | 根据制种玉米与其他作物在中高分辨率遥感影像上的光谱和纹理差异,利用多源遥感数据,以提取制种玉米种植田为研究目标,提出了作物多时相光谱特征分析的植被指数体系,多维度反映了作物不同光谱差异;在纹理检测前加入图像旋转不变处理,解决了遥感影像中作物田纹理方向问题;最后构建了多时相光谱特征和高空间分辨率遥感影像LBP-GLCM纹理特征的制种玉米田识别方法体系。以新疆霍城县为研究区,利用上述方法体系结合随机森林分类器,通过实验得到分类总体精度为90.57%,Kappa系数为0.79,制种玉米田分类结果用户精度为99.20%,制图精度为86.68%,基本满足对制种玉米田的识别需求。
|
| 关 键 词： | 制种玉米田 多源遥感 植被指数 LBP-GLCM纹理 随机森林 |
| 收稿时间： | 2017/11/10 0:00:00 |
Seed Maize Field Identification Based on Analysis of Remote Sensing Timing Spectrum and High Resolution Texture |
| |
| ZHANG Chao,QIAO Min,LIU Zhe,LIU Diyou,JIN Hongshan and ZHU Dehai.Seed Maize Field Identification Based on Analysis of Remote Sensing Timing Spectrum and High Resolution Texture[J].Transactions of the Chinese Society of Agricultural Machinery,2018,49(5):218-225. |
| |
| Authors: | ZHANG Chao QIAO Min LIU Zhe LIU Diyou JIN Hongshan and ZHU Dehai |
| |
| Institution: | China Agricultural University,China Agricultural University,China Agricultural University,China Agricultural University,China Agricultural University and China Agricultural University |
| |
| 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, Landsat8 OLI 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. |
| |
| Keywords: | seed maize fields multi-source remote sensing vegetation index LBP-GLCM texture random forest |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《农业机械学报》浏览原始摘要信息 |
| 点击此处可从《农业机械学报》下载免费的PDF全文 |
|
