机译:一种有效的机载激光雷达与共同注册数据融合的土地覆被分类方法
School of Instrumentation Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China Computational Vision Group, School of Systems Engineering, University of Reading,Reading, United Kingdom RG6 6AU;
Computational Vision Group, School of Systems Engineering, University of Reading,Reading, United Kingdom RG6 6AU;
School of Instrumentation Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;
School of Instrumentation Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;
机译:使用GF-2图像和基于随机森林的机载激光雷达数据进行土地覆盖分类
机译:基于像素的决策树和基于对象的支持向量机方法在航空影像和机载激光雷达数据土地覆盖分类中的比较
机译:机载LiDAR强度数据的辐射校正和归一化,以改善土地覆盖物分类
机译:机载激光雷达数据融合航空光学图像进行土地覆盖分类
机译:利用多波长机载极化激光雷达进行植被分类的新数据处理方法。
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:利用不同光谱指数进行土地覆盖分类和土地/水图制作的机载多光谱激光雷达数据
机译:从机载激光雷达地形数据推导城市有效气动表面粗糙度