内蒙古农业大学学报（自然科学版）2026，Vol.47Issue(5)：36-45,10.DOI:10.16853/j.cnki.1009-3575.2026.05.005
内蒙古典型草原布氏田鼠鼠洞无人机遥感识别研究
UAV Remote Sensing Identification of Brandt's Vole Burrows in Typical Grasslands of Inner Mongolia
摘要
Abstract
This study aimed to improve the monitoring efficiency of Brandt's vole(Lasiopodomys brandtii)in the typical grasslands of Inner Mongolia,and to more effectively address the grassland degradation caused by its burrowing activity.Traditional monitoring methods,such as the burrow-plugging method,are time-consuming and labor-intensive,failing to meet practical needs.In response,this study proposed a UAV remote sensing-based method for monitoring the Brandt's vole burrows.In 2023,multispectral imagery was collected via UAV in the typical grasslands of Xilin Gol,Inner Mongolia,and analyzed using object-oriented multi-scale segmentation,vegetation indices,and two supervised classifiers,i.e.,support vector machine(SVM)and K-nearest neighbor(KNN),to automatically identify vole burrows.Under the conditions of using a DJI M300 RTK drone equipped with a RedEdge dual-camera imaging system(Resolu-tion 1 280×960 pixels),the study determined that the optimal segmentation scale for Brandt's vole burrows was 30 cm,with the opti-mized soil-adjusted vegetation index(OSAVI)identified as the best vegetation index.SVM classification based on OSAVI yielded the highest recognition accuracy at 74.29%,with a Kappa coefficient of 0.719 3,outperforming KNN.This study clarified the key parame-ters and optimal supervised classification method for the vole burrow identification,providing a reliable approach for an efficient UAV-based pest monitoring method in grasslands.关键词
无人机遥感技术/监测/布氏田鼠/鼠洞识别Key words
Drone remote sensing technology/Monitoring/Brandt's vole/Burrow identification分类
农业科技引用本文复制引用
刘楠,郭雪佳,褚东阳,林忆馨,李鑫,杨文蕾,叶国辉,付和平,袁帅..内蒙古典型草原布氏田鼠鼠洞无人机遥感识别研究[J].内蒙古农业大学学报（自然科学版）,2026,47(5):36-45,10.基金项目
内蒙古自治区自然科学基金项目(2023MS03025) （2023MS03025）
国家自然科学基金项目(32060256,32060395) （32060256,32060395）
内蒙古自治区科技计划项目(2021GG0108) （2021GG0108）
内蒙古自治区科技重大专项项目(2021ZD0006) （2021ZD0006）
