Institute of Agricultural Remote Sensing and Information Technology, Zhejiang University , Hangzhou, China, National Engineering Research Center for Information Technology in Agriculture Beijing 100097, China;
Institute of Agricultural Remote Sensing and Information Technology, Zhejiang University , Hangzhou, China;
National Engineering Research Center for Information Technology in Agriculture Beijing 100097, China;
National Engineering Research Center for Information Technology in Agriculture Beijing 100097, China;
Institute of Agricultural Remote Sensing and Information Technology, Zhejiang University , Hangzhou, China, National Engineering Research Center for Information Technology in Agriculture Beijing 100097, China;
Institute of Agricultural Remote Sensing and Information Technology, Zhejiang University , Hangzhou, China;
General Planning and Supervision Division china rural technology development center, Ministry of Science and Technology Beijing 100045, China;
wheat; hyperspectral vegetation index; chlorophyll density; artificial neural network; mathematical power regression;
机译:比较宽带和高光谱植被指数的预测能力和稳定性,以估算绿叶面积指数和冠层叶绿素密度
机译:使用高光谱植被指数估算小麦叶片叶绿素含量
机译:高光谱指数的校准和验证,用于估计阔叶林叶绿素含量,每面积叶质量,叶面积指数和叶冠生物量
机译:基于冠层高光谱植被指数的基于人工神经网络的小麦叶绿素密度估算
机译:利用高光谱遥感估算冠层叶绿素。
机译:利用原位高光谱数据评估白粉病胁迫下冬小麦植物水分状况的冠层植被指数
机译:具有高光谱数据的封闭林冠层叶绿素含量估算的窄带光学指数放大和模型反演方法
机译:高光谱植被指数在高叶面积指数温带灌木丛林檐篷变异中的应用。