机译:高光谱和LiDAR数据融合用于云影混合遥感场景分类
School of Geographical Sciences, Guangzhou University, Guangzhou, China;
Department of Telecommunications and Information Processing, Ghent University, Ghent, Belgium;
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, and the Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan, China;
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, and the Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan, China;
Vision Laboratory, University of Antwerp, Antwerp, Belgium;
School of Automation Science and Engineering, South China University of Technology, Guangzhou, China;
Department of Telecommunications and Information Processing, Ghent University, Ghent, Belgium;
Laser radar; Training; Clouds; Feature extraction; Earth; Hyperspectral sensors;
机译:高光谱和LIDAR遥感数据融合用于复杂林区分类
机译:利用多特征学习融合高光谱和LiDAR遥感数据
机译:利用机载超光谱和激光雷达遥感数据对冠状树种进行分类
机译:高光谱和LIDAR遥感数据的融合,用于复杂林区的分类
机译:新罕布什尔州怀特山脉的森林结构的远程检测:波形激光雷达和高光谱遥感数据的整合。
机译:通过剩余网络融合高光谱CASI和空气传播的LIDAR数据的地面对象分类
机译:高光谱和激光雷达遥感数据的分类器融合以改善土地覆被分类
机译:利用LIDaR测深法对遥感海洋颜色数据解释和高光谱图像融合的查找表(LUT)方法的不断发展。