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Topic

Environment

Volume

Volume 67 / No. 2 / 2022

Pages : 128-136

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SPECTRAL CHARACTERISTICS ANALYSIS AND EXTRACTION OF MICRO-PATCHES BASED ON THE HYPERSPECTRAL DESERT STEPPE IMAGES

基于高光谱荒漠草原的微斑块光谱特征分析与提取

DOI : https://doi.org/10.35633/inmateh-67-12

Authors

Xinchao GAO

Inner Mongolia Agricultural University

(*) Jianmin DU

Inner Mongolia Agricultural University

Yuge BI

Inner Mongolia Agricultural University

Weiqiang PI

School of Mechanical and Electrical Engineering and Automotive Engineering, Huzhou Vocational and Technical College

Xiangbing ZHU

Inner Mongolia Agricultural University

Yanbin ZHANG

Inner Mongolia Agricultural University

(*) Corresponding authors:

[email protected] |

Jianmin DU

Abstract

In hyperspectral remote sensing images, desert steppe vegetation, bare soil, and rat holes appear as micro-patches. The spectral feature analysis of micro-patches is the basis for identification and classification and also the basis for quantitative remote sensing monitoring of ground objects. Inner Mongolia desert steppe micro-patch as the research object extracts the spectral reflectance of different micro-patches, performs various vegetation index calculations, quantitatively analyzes the spectral characteristics of different micro-patches, and proposes a micro-patch spectral analysis method. Classification of high-resolution hyperspectral images of desert steppe surface micropatches. The results show that: (1) There are pronounced differences in the spectral reflectance of the three types of surface micro-patches. The vegetation has apparent characteristics in the green wave reflection peak and the red wave absorption valley. The spectral reflectance of the bare soil is higher than that of the mouse hole, and the two have been increasing. The trend is increasing slowly; (2) The proposal and application of the MSA index can effectively realize the identification and classification of surface micropatches, and the Kappa coefficient has reached 0.906 through confusion matrix verification. The above spectral analysis method realizes the classification and identification of complex ground objects using near-ground remote sensing images. It provides new ideas and methods for accurate quantitative statistics of desert grassland ecological information.

Abstract in Chinese

高光谱遥感图像中荒漠草原植被、裸土、鼠洞均表现为微斑块,对微斑块进行光谱特征分析是识别分类的基础,同时也是定量遥感监测地物的基础。以内蒙古荒漠草原微斑块为研究对象,提取不同微斑块的光谱反射率,分别进行多种植被指数运算,定量分析不同微斑块的光谱特征,并提出微斑块光谱分析法,实现了对采集的高分辨率的荒漠草原地表微斑块高光谱图像分类研究。结果表明:(1)三类地表微斑块光谱反射率存在明显差异,植被在绿波反射峰与红波吸收谷表现特征明显,裸土的光谱反射率高于鼠洞且二者一直呈上升趋势缓慢增长;(2)MSA指数的提出与应用有效地实现了地表微斑块的识别与分类,经混淆矩阵验证Kappa系数达到0.906。上述光谱分析方法实现了利用近地面遥感图像对复杂地物的分类与识别,为荒漠草原生态信息的精确量化统计提供了新的思路与手段。

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