Pattern Recognition of Forest Vegetation from Hyperspectral Airborne and Multichannel Satellite Data of High Spatial Resolution: Comparison of Results and Estimation of Their Accuracy

被引：0

作者：

Kozoderov, V. V. ^{[1
]}

Egorov, V. D. ^{[2
]}

机构：

[1] Moscow MV Lomonosov State Univ, Moscow, Russia

[2] Russian Acad Sci, Marchuk Inst Numer Math, Moscow, Russia

来源：

IZVESTIYA ATMOSPHERIC AND OCEANIC PHYSICS | 2020年 / 56卷 / 09期

基金：

俄罗斯基础研究基金会;

关键词：

airborne hyperspectral imagery; multichannel satellite data of high spatial resolution; pattern recognition of forest vegetation;

D O I：

10.1134/S0001433820090133

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

The pattern recognition of a forest surface from remote sensing data (both airborne hyperspectral data and WorldView-2 multichannel satellite data of high spatial resolution) is investigated. Calculations have been performed using both the method developed earlier by the authors and the standard statistical approach. For three fragments of the forest surface, the range of changes in the accuracy of recognition calculations has been estimated for both airborne and satellite data, depending on the use of different databases developed for the recognition system. Some features of the pattern recognition of the underlying surface are discussed on the basis of both hyperspectral airborne data and multichannel satellite data of high spatial resolution.

引用

页码：1146 / 1158

页数：13

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