利用Sentinel-2卫星数据对俄罗斯中部森林草原废弃农田的光谱反射分析

IF 1.1 Q4 OPTICS
E. Terekhin
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引用次数: 0

摘要

本文基于Sentinel-2数据,研究了森林-草原区农化后景观的光谱响应。这项研究是在中Chernozem地区的领土上进行的。在大多数Sentinel-2波段上,在废弃农用地上形成的森林类型对光谱响应有统计学显著影响。落叶阔叶林和针叶林废弃地的反射率在大多数波段上差异有统计学意义。混交林废弃地的反射率与其他类型的后农业景观没有统计学上的显著差异。在大多数Sentinel-2波段,废弃土地的反射率与其森林覆盖呈负相关。在所有后农业景观类型的红色(波段4)和SWIR(波段11、12)范围内,与森林覆盖的相关性最强。在相同的波段内,大多数后农业景观的森林覆盖等级之间存在统计学上的显著差异。已建立的模式使得利用红色波段(波段4)和SWIR MSI波段(波段11、12)的反射率来评估后农业景观的森林覆盖成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spectral reflectance analysis of abandoned agricultural lands in the Central Russian forest-steppe using Sentinel-2 satellite data
The article considers the spectral response of post-agrogenic landscapes in the forest-steppe zone based on Sentinel-2 data. The study was carried out on the territory of the Central Chernozem region. The type of forest that forms on abandoned agricultural land has a statistically significant effect on the spectral response in most Sentinel-2 bands. The reflectance of abandoned lands with deciduous and coniferous species is statistically significantly different in most bands. The reflectance of abandoned lands with mixed forests does not differ statistically significantly from other types of post-agrogenic landscapes. The reflectance of abandoned lands is inversely related to their forest cover in most Sentinel-2 bands. The strongest correlation with forest cover is typical for red (Band 4) and SWIR (Band 11, 12) ranges for all post-agrogenic landscape types. In the same bands, there are statistically significant differences between most of forest cover gradations of post-agrogenic landscapes. The established patterns make it possible to use the reflectance in the red (Band 4) and SWIR MSI bands (11, 12) to assess the forest cover of post-agrogenic landscapes.
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来源期刊
Computer Optics
Computer Optics OPTICS-
CiteScore
4.20
自引率
10.00%
发文量
73
审稿时长
9 weeks
期刊介绍: The journal is intended for researchers and specialists active in the following research areas: Diffractive Optics; Information Optical Technology; Nanophotonics and Optics of Nanostructures; Image Analysis & Understanding; Information Coding & Security; Earth Remote Sensing Technologies; Hyperspectral Data Analysis; Numerical Methods for Optics and Image Processing; Intelligent Video Analysis. The journal "Computer Optics" has been published since 1987. Published 6 issues per year.
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