基于无人机影像的林地单株立木自动化提取研究——以丹霞山湿地保护区为例

利用无人机技术可以快速获取林业自然保护区高分辨率遥感影像,无人机影像在林业资源调查与监测中具备传统卫星影像无可比拟的优势。本研究以丹霞山湿地自然保护区为研究对象,基于无人机遥感影像,提出了一种人工林地单株立木自动化提取方法。研究采用遥感影像多尺度分割算法,对研究区无人机遥感影像进行多尺度分割,然后通过构建林地特征信息模型,实现对案例区人工林地单株立木自动化提取。结果表明：该方法在丹霞山湿地保护区人工林地自动化提取中具有较高的可行性,Kappa系数达到了0.979,总体分类精度达到了98.40%,能够满足人工林地提取的需要。该方法省去了人工林地分类前的人工干预和先验知识输入,大幅度提高了无人机影像在林地资源调查应用中的工作效率,为精准林业调查提供了一种新方法。

Automatic Extraction of Individual Tree in Forest Land Based on UAV Remote Sensing Images: Taking Danxia Mountain Wetland Reserve as an Example

UAV technology can be used to quickly acquire high resolution remote sensing images of forest nature reserve. In forestry resource investigation and monitoring, UAV images have more advantages than traditional satellite images. This study took Danxia Mountain Wetland Nature Reserve as the research object and proposed an automatic extraction method of individual forest tree based on UAV images. A multi-scale segmentation algorithm for UAV remote sensing image was adopted. Then, through constructing the characteristic information model of forest land, the automatic extraction of individual tree in artificial forest land in the study area was realized. The results showed that the proposed method had high feasibility in automatic extraction of artificial forest land in Danxia Mountain Wetland Nature Reserve. The Kappa coefficient was 0.979, and the overall accuracy of classification extraction reached 98.40%, which could meet the needs of artificial forest land extraction. This method can eliminate the human intervention and prior knowledge before the classification of artificial forest land, greatly improve the efficiency of UAV images in the investigation and monitoring of forest land resources, and provide a new way for accurate forest survey.