基于Sentinel-2的复杂山区常用植被指数地形效应分析

doi:10.13292/j.1000-4890.202304.014

生态学杂志 ›› 2023, Vol. 42 ›› Issue (4): 956-965.doi: 10.13292/j.1000-4890.202304.014

基于Sentinel-2的复杂山区常用植被指数地形效应分析

陈怡欣^1,2,3,莫登奎^1,2,3,严恩萍^1,2,3*

(¹中南林业科技大学林学院，长沙 410004； ²湖南省林业遥感大数据与生态安全重点实验室，长沙 410004； ³国家林业与草原局南方森林资源管理与监测重点实验室，长沙 410004)

出版日期:2023-04-03 发布日期:2023-04-06

Analysis on topographic effects of commonly used vegetation indices in complex mountain area based on Sentinel-2 data.

CHEN Yixin^1,2,3, MO Dengkui^1,2,3, YAN Enping^1,2,3*

(¹College of Forestry, Central South University of Forestry and Technology, Changsha 410004, China; ²Hunan Provincial Key Laboratory of Forestry Remote Sensing Big Data and Ecological Security, Changsha 410004, China; ³South Key Laboratory of Forest Resources Management and Monitoring, National Forestry and Grassland Administration, Changsha 410004, China).

Online:2023-04-03 Published:2023-04-06

摘要/Abstract

摘要： 结合典型地形校正模型，比较复杂山区不同植被指数的地形效应去除效果，能够为地表植被的准确评估提供科学依据。本文以湖南省炎陵县的Sentinel-2影像为数据源，采用C模型、SCS+C模型以及Teillet-回归模型对比值型植被指数(NDVI和SR)和非比值型植被指数(MNDVI和RSR)进行地形校正，从视觉效果、相关性、坡度、坡向、植被覆盖度方面分析4种植被指数的地形效应去除效果。结果表明：（1）植被指数的波段比形式能够有效抑制地形引起的噪声。坡度<15°时，植被指数的地形效应均有不同程度的抑制；坡度>15°时，MNDVI的校正效果最好，RSR次之，NDVI和SR容易出现过度校正。（2）3种地形校正模型均能削弱复杂山区植被指数的地形效应，特别是坡度>15°时，C模型效果最好，SCS+C模型次之，Teillet模型效果较差。（3）MNDVI指数结合地形校正模型，能够有效抑制复杂山区地形效应的影响，提高植被覆盖度的估算精度。其中，坡度<25°时，Teillet模型效果最好；坡度>25°时，C模型效果最好。

关键词: 植被指数, 地形效应, 地形校正, Sentinel-2, 复杂山区

Abstract: Using typical topographic correction models to compare the removal effectiveness of topographic effect on different vegetation indices under complex mountain conditions can provide a scientific basis for accurate assessment of vegetation. Taking Sentinel-2 images of Yanling County, Hunan Province as data source, C model, SCS+C model, and Teillet-regression model were used for topographic correction of the band-ratio vegetation indices (NDVI and SR) and non-band-ratio vegetation indices (MNDVI and RSR), aiming to analyze the removal effectiveness of topographic effect on the four vegetation indices from five aspects: visual effects, correlation, slope, aspect, and vegetation coverage. The results showed that: (1) The band-ratio vegetation indices effectively suppressed the noise caused by terrain. When the slope was less than 15°, the topographic effects of vegetation indices were suppressed to different degrees. When the slope was greater than 15°, topographic correction was the most effective on MNDVI, followed by RSR, while NDVI and SR were prone to over-correction. (2) All the three topographic correction models could reduce the topographic effects of the vegetation indices in rugged terrain areas, especially when the slope was greater than 15°. The C model was the most effective, followed by the SCS+C model, and the Teillet model was the least effective. (3) MNDVI after topographic correction effectively restrained the influence of complex mountain topographic effects and improved the estimation accuracy of vegetation coverage. When slope was less than 25°, the Teillet model was the most effective. When slope was greater than 25°, the C model was the most effective.

Key words: vegetation index, topographic effect, topographic correction, Sentinel-2, complex mountain.

陈怡欣, 莫登奎, 严恩萍. 基于Sentinel-2的复杂山区常用植被指数地形效应分析[J]. 生态学杂志, 2023, 42(4): 956-965.

CHEN Yixin, MO Dengkui, YAN Enping. Analysis on topographic effects of commonly used vegetation indices in complex mountain area based on Sentinel-2 data.[J]. Chinese Journal of Ecology, 2023, 42(4): 956-965.

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基于Sentinel-2的复杂山区常用植被指数地形效应分析

Analysis on topographic effects of commonly used vegetation indices in complex mountain area based on Sentinel-2 data.

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