基于农田实景图像的玉米覆盖度估算模型  

The Estimation Model of Fractional Vegetation Cover of Maize Based on the Real Image of Farmland

作　　者：张东东 周刊社[1] 戴睿 袁雷[1] 王佳锐 边多 Zhang Dongdong;Zhou Kanshe;Dai Rui;Yuan Lei;Wang Jiarui;Bian Duo(Tibet Climate Center,Lhasa 850000;Chinese Academy of Agricultural Engineering Planning&Design,Beijing 100125)

机构地区：[1]西藏自治区气候中心,拉萨850000 [2]农业农村部规划设计研究院,北京100125

出　　处：《中国农学通报》2021年第29期84-91,共8页Chinese Agricultural Science Bulletin

基　　金：第二次青藏高原综合科学考察研究项目“西藏中西部湖泊群变化及川藏铁路工程区域气候预测技术系统”(2019QZKK0105);西藏自治区重点研发计划项目“气候变化背景下西藏高原季节划分及农业气候资源时空变化特征研究”(XZ202001ZY0023N)。

摘　　要：为实时、准确地获取玉米覆盖度,为玉米长势监测提供科学依据,以农田小气候实景站采集的玉米图像为数据源,利用图像处理技术对玉米图像进行分析处理,结合9种图像颜色指数(NDI、ExG、ExR、ExG-ExR、R-G、G-B、VEG、CIVE、(G-B)/|R-G|),构建了基于图像颜色指数的玉米覆盖度估算模型。结果表明:利用图像颜色指数可以有效估算玉米覆盖度,除颜色指数(G-B)/|R-G|外,其他8种颜色指数估算玉米覆盖度的精度均较高,其中,以VEG为变量的玉米覆盖度估算模型精度最高,预测结果的R2为0.993,RMSE和MAE均最小,分别为0.0270、0.0223。该方法可以有效、快速的提取玉米覆盖度。To acquire the fractional vegetation cover(FVC) of maize on real-time, which could provide a scientific basis for maize growth monitoring, we took the image shot by the digital camera installed in automatic weather observation station as data sources, built FVC estimation models using 9 color vegetation indices of images(NDI,ExG, ExR, ExG-ExR, R-G, G-B, VEG, CIVE and(G-B)/|R-G|) extracted by employing image processing technologies. The results showed that these indices could estimate the FVC of maize effectively with high accuracy except the(G-B)/|R-G|, the vegetative(VEG) was the optimal color vegetation index for estimation of maize FVC.The model with VEG as variable had the highest estimation accuracy for maize FVC, with the highest coefficient of determination(R2), and lowest root mean square error(RMSE) and mean absolute error(MAE) of 0.993, 0.0270 and0.0223, respectively. The method could be applied to the extraction of crop FVC effectively.

关 键 词：玉米 覆盖度 数字照片 颜色指数 估算模型 

分 类 号：S566.1[农业科学—作物学]