New method for cotton fractional vegetation cover extraction based on UAV RGB images

作     者：Huanbo Yang Yubin Lan Liqun Lu Daocai Gong Jianchi Miao Jing Zhao 

作者机构：School of Agricultural and Food EngineeringShandong University of TechnologyZibo 255000ShandongChina International Precision Agriculture Aviation Application Technology Research CenterShandong University of TechnologyZibo 255000ShandongChina School of Transportation and Vehicle EngineeringShandong University of TechnologyZibo 255000ShandongChina 

出 版 物：《International Journal of Agricultural and Biological Engineering》 (国际农业与生物工程学报（英文）)

年 卷 期：2022年第15卷第4期

页      面：172-180页

核心收录：

学科分类：1002[医学-临床医学] 100201[医学-内科学(含：心血管病、血液病、呼吸系病、消化系病、内分泌与代谢病、肾病、风湿病、传染病)] 10[医学] 

基　　金：The authors gratefully acknowledge the financial support provided by Top Talents Program for One Case One Discussion of Shandong Province,China Agriculture Research System(Grant No.CARS-15-22) Natural Science Foundation of Shandong Province(Grant No.ZR2021MD091) 

主　　题：cotton UAV visible light images fractional vegetation cover vegetation index threshold method TRVI TBVI 

摘      要：As the key principle of precision farming,the distribution of fractional vegetation cover is the basis of crop management within the field *** estimate crop FVC rapidly at the farm scale,high temporal-spatial resolution imagery obtained by unmanned aerial vehicle(UAV)was *** verify the application potential of consumer-grade UAV RGB imagery in estimated FVC,blue-green characteristic vegetation index(TBVI)and red-green vegetation index(TRVI)were proposed in this study according to the differences of the gray value among cotton vegetation,soil and shadow in the ***,two new constructed indices and several published indices were used to extract visible light images and generate greyscale images for each of the visible light vegetation ***,the thresholds of cotton vegetation and non-vegetation pixels were established based on the vegetation index threshold method which combines support vector machine classification and vegetation ***,the accuracy difference in vegetation information extraction between the newly constructed and several published indices was *** results show that the accuracy of the information extracted by TRVI is higher than that of subdivision index of other visible light(FVC extraction precision in the first bud stage of cotton:R2=0.832,RMSE=2.307,nRMSE=4.405%;FVC extraction precision in the bud stage of cotton:R2=0.981,RMSE=1.393,nRMSE=1.984%;FVC extraction precision in the flowering stage of cotton:R2=0.893,RMSE=2.101,nRMSE=2.422%;FVC extraction precision in the boll stage of cotton:R2=0.958,RMSE=1.850,nRMSE=2.050%).