首页|基于无人机高光谱遥感的典型草原退化指示种识别

基于无人机高光谱遥感的典型草原退化指示种识别

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  • NETL
  • NSTL
  • 万方数据
  • 维普
利用无人机高光谱遥感数据技术快速、准确地提取典型草原植被类型,对动态监测草原生态安全具有重要的意义.为此,在退化较严重的白音锡勒牧场典型草原区,采集了空间分辨率为1.8 cm、光谱分辨率为4nm,共有125个波段(450～950 nm)的高光谱影像.选主要退化指示种—冷蒿为识别 目标,经微分变换和包络线去除等光谱变换处理,进行光谱特征差异分析发现冷蒿与其他绿色植被和背景土壤在500、550、670 nm处有明显的光谱差异,因此选择以上3个波段作为特征波段,构建了支持向量机(SVM)和随机森林(RF)的退化指示物种识别模型,并进行了精度验证.结果显示:SVM和RF的识别精度分别为96.92％和97.34％,Kappa系数分别为0.95和0.96.从结果可知,随机森林模型的识别精度更高,退化指示种的像元空间分布更接近自然状况,可以为监测典型草原退化指示种提供技术支持.
Identification of Typical Grassland Degradation Indicator Species based on UAV Hyperspectral Remote Sensing
The use of UAV hyperspectral remote sensing data technology to quickly and accurately extract typi-cal grassland vegetation types is of great significance for dynamic monitoring of grassland ecological security.In the typical grassland area of Baiyinxile pasture with severe degradation,hyperspectral images with a spatial reso-lution of 1.8 cm and a spectral resolution of 4 nm,with a total of 125 bands(450 nm to 950 nm)were collected.The main degradation indicator species,Artemisia cholerae,was selected as the identification target,and after differential transformation,envelope removaland other spectral transformations,the differences in spectral char-acteristics were analyzed.There are obvious spectral differences at 500 nm、550 nm、670 nm,so the above three bands were selected as characteristic bands,and the degradation indicator species identification model of Sup-port Vector Machine(SVM)and Random Forest(RF)was constructed,and the accuracy was verified.The re-sults show that the recognition accuracy of SVM and RF are 96.92％和97.34％,respectively,and the Kappa coefficients are 0.95 and 0.96,respectively.It can be seen from the results that the identification accuracy of the random forest model is higher,and the pixel spatial distribution of degraded indicator species is closer to the nat-ural state,which can provide technical support for monitoring typical grassland degradation indicator species.

UAVHyperspectral remote sensingTypical grasslandDegenerative indicator species

乌尼乐、包玉龙、布仁图雅、图布新巴雅尔、陶赛喜雅拉图、包玉海、金额尔德木吐

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内蒙古师范大学地理科学学院,内蒙古呼和浩特 010022

内蒙古自治区遥感与地理信息系统重点实验室,内蒙古呼和浩特 010022

内蒙古自治区环境监测总站,内蒙古 呼和浩特 010011

无人机 高光谱遥感 典型草原 退化指示种

内蒙古自治区科技重大专项内蒙古自治区哲学社会科学规划项目内蒙古自治区自然科学基金面上项目内蒙古自治区重点研发与成果转化计划国家自然科学基金地区科学基金

2021ZD0045032022NDA2252021MS040162022YFSH007042261019

2024

10.11873/j.issn.1004-0323.2024.1.0248

遥感技术与应用
中国科学院遥感联合中心

遥感技术与应用

CSTPCD北大核心
影响因子：0.961
ISSN：1004-0323
年,卷(期)：2024.39(1)
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