文献类型：期刊文献

中文题名：基于近地遥感的林木参数精细获取进展简述

英文题名：Brief Review on the Progress in Fine-scale Acquisition of Forest Parameters based on Near-ground Remote Sensing

作者：柴国奇[1] 杨彦臣[1] 王磊[2] 马勇[3] 田昕[1]

第一作者：柴国奇

机构：[1]中国林业科学研究院资源信息研究所,北京100091;[2]中国科学技术交流中心,北京100045;[3]海南省地球观测重点实验室,中国科学院空天信息研究院海南研究院,海南三亚572029

年份：2025

卷号：40

期号：4

起止页码：1015-1025

中文期刊名：遥感技术与应用

外文期刊名：Remote Sensing Technology and Application

收录：;北大核心:【北大核心2023】；

基金：海南省科技专项(ZDYF2021SHFZ260)。

语种：中文

中文关键词：林木参数;地面观测;近地观测;高分辨率影像;LiDAR点云

外文关键词：Forest parameters;Ground-based observations;Near-earth observations;High-resolution imagery;LiDAR point cloud

分类号：S712;TP79

摘要：林木树冠自动分割、胸径、树高、冠幅、冠面积、材积等精细林木参数快速准确提取是森林生产力和碳储量等参数高精度估算的基础。近地遥感技术可以快速高效获取多视角高分辨率数据,具有高精度自动获取林木参数的潜力。对国内外利用地面和有/无人遥感技术开展森林精细调查的情况进行总结,全面阐述基于近地遥感的林木参数精细获取研究现状,重点讨论不同近地遥感平台多光谱和激光雷达数据中获取森林参数的效果与能力,并对比其应用场景和优劣性。近地遥感技术具备低成本、高效获取森林精细参数的能力,可为森林管理培育和经营决策、加快推进美丽中国建设提供重要技术支持。
Automatic crown segmentation,rapid and accurate extraction of diameter at breast height,tree height,crown width and crown area are the basis for high-precision estimation of forest productivity and carbon stocks.Near-ground remote sensing technology allow rapid and efficient acquisition of high-resolution data from multiple views,which have the potential for high-precision acquisition of forest parameters.Summary of domestic and international forest fine survey using ground and manned/unmanned aircraft remote sensing technology.Comprehensive description of the current status of research on fine acquisition of forest parameters based on near-ground remote sensing.Discussions focus on the algorithms for acquiring forest parameters based on near-ground remote sensing platform multispectral and LiDAR data,and compare their application scenarios and advantages and disadvantages.Near-ground remote sensing technology possesses the capability to acquire detailed forest parameters with low costs and high efficiency,providing crucial technical support for forest management,cultivation,operational decision-making,and accelerating the advancement of building a Beautiful China.