高分辨率航片小班区划与树种判读  

Sub-compartment Division and Interpretation of Tree Species Based on High-resolution Aerial Photos

作　　者：熊昊 庞勇[1] 李春干[2] 代华兵 XIONG Hao;PANG Yong;LI Chungan;DAI Huabing(Institute of Forest Resource Information Techniques,Chinese Academy of Forestry,Beijing 100091;Forestry College of Guangxi University,Nanning 530004;Guangxi Forest Inventory and Planning Institute,Nanning 530011)

机构地区：[1]中国林业科学研究院资源信息研究所,北京100091 [2]广西大学林学院,南宁530004 [3]广西林业勘测设计院,南宁530011

出　　处：《林业资源管理》2020年第1期143-150,共8页Forest Resources Management

基　　金：国家自然科学基金“基于高分辨率遥感数据的森林生物多样性监测”(31570546);亚太森林恢复与可持续管理网络项目“Regional Forest Observations for Sustainable Forest Management”(2018P1-CAF)。

摘　　要：以广西壮族自治区南宁市高峰林场为研究区,采用CAF-LiCHy系统获取的20cm空间分辨率的CCD影像进行森林资源二类调查小班区划与树种判读技术研究。对研究区常见树种建立高分辨率航片树种解译标志,结合上一期二类调查的小班区划结果,使用目视解译的方法重新区划了小班边界,并根据解译标志完成了小班优势树种判读,使用实地调查数据进行精度验证表明,目视解译总体精度为92.11%,Kappa系数为0.90。结果表明,高分辨率航片在小班区划和优势树种判读中具有很好的应用潜力。This paper studied the sub-compartment division and tree species interpretation techniques of forest resources management inventory in Guangxi Gaofeng Forest Farm.The 0.2 m spatial resolution CCD data were used,which were obtained by CAF-LiCHy Airborne Observation System.The interpretation signatures of common tree species were built.The sub-compartment boundaries were divided using visual interpretation,combined with the division results from previous forest inventory.Then,the dominant species was interpreted based on the interpretation signatures and the results were verified by filed data.According to the accuracy verification,the overall accuracy is 92.11% and Kappa coefficient is 0.90.The results indicate that high spatial resolution remote sensing data have high potential in sub-compartment division and tree species interpretation.

关 键 词：高分辨率航片 森林资源二类调查 目视解译 森林航测 森林经理 

分 类 号：S757[农业科学—森林经理学] S771.5[农业科学—林学]