ass日本风韵熟妇pics男人扒开女人屁屁桶到爽|扒开胸露出奶头亲吻视频|邻居少妇的诱惑|人人妻在线播放|日日摸夜夜摸狠狠摸婷婷|制服 丝袜 人妻|激情熟妇中文字幕|看黄色欧美特一级|日本av人妻系列|高潮对白av,丰满岳妇乱熟妇之荡,日本丰满熟妇乱又伦,日韩欧美一区二区三区在线

Leaf area index (LAI) is an important parameter in crop growth monitoring and crop yield estimation. However, optical remote sensing cannot extract the structural information. Light detection and ranging (LIDAR) can provide accurate crop structural information, so LiDAR can make up the shortage of optical remote sensing. Therefore, the purpose of this research is to study the vertical structure information of crops which can be extracted by LiDAR, analyze the correlation of LiDAR vertical metrics and LAI of crop, and estimate LAI of the whole study area. First, the metrics were extracted based on LiDAR data, including mean height above ground of all first returns (Hmean), maximum height above ground of all first returns (Hmax), minimum height above ground of all first returns (Hmin), the percentiles of the canopy height distributions(H25th, H50th, H75th, H90th), laser penetration index (LPI), density of points, porosity and leaf angle. Then, Pearson correlation analysis was used to filter LiDAR metrics which are better related to LAI measured data. Last, regression analysis of selected sensitive parameters was carried out on setting up LiDAR-LAI estimation model, and the LAI estimated result of the whole study area was calculated. The result shows that correlation coefficient between estimated LAI and field measured LAI is 0.79, and RMSE is 0.47. It shows that crop canopy structure parameters extracted by LiDAR can be used to estimate the spatial continuous and large area of LAI of crops.