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首页> 外文期刊>International journal of remote sensing >Aboveground biomass patterns across treeless northern landscapes
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Aboveground biomass patterns across treeless northern landscapes

机译：跨行程北方景观的地上生物量图案

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摘要

Aboveground vegetation biomass in northern treeless landscapes - peatlands and Arctic tundra - has been modelled with spectral information derived from optical remote sensing in several studies. However, synthesized overviews of biomass patterns across circumpolar sites have been limited. Based on data from eight study sites in Europe, Siberia and Canada, we ask (1) how biomass is divided between plant functional types (PFTs) and (2) how well biomass patterns can be detected with widely available, moderate spatial resolution (3-10 m) satellite imagery and topographic data. We explain biomass patterns using random forest regressions with the predictors being spectral bands and indices calculated from multi-temporal Sentinel-2 and PlanetScope imagery and topographic information calculated from ArcticDEM data. Our results indicate that there are notable differences in vegetation composition between northern landscapes with mosses, graminoids and deciduous shrubs being the most dominant PFTs. Remote sensing data detects biomass patterns, but regression performance varies between sites (explained variance 36-70%, normalized root mean square error 9-19%). There is also variability between sites whether Sentinel-2 or PlanetScope data is more suitable to detect biomass patterns and which the most important predictors are. Topographic information has a minor or negligible importance in most of the sites. Our results suggest that there is no easily generalizable relationship between satellite-derived vegetation greenness and biomass.
机译：在北部的北部景观的地上植被生物量 - 泥炭地和北极苔原 - 已经采用了几项研究中的光学遥感的光谱信息进行了建模。然而，跨越Circumpolar位点的生物质图案的合成概述受到限制。根据欧洲，西伯利亚和加拿大的八个研究网站的数据，我们问（1）生物量如何在植物功能类型（PFT）之间分开，（2）可以通过广泛可用，适度的空间分辨率（3 -10 m）卫星图像和地形数据。我们用随机森林回归来解释生物量模式，其中具有从多时间哨声-2和从Arcticdem数据计算的多时间哨声图像和行星扫描图像和地形信息计算的频谱频带和索引。我们的结果表明，北部景观与苔藓，禾本科和落叶灌木是最占优势的PFT的植被组成有显着差异。遥感数据检测生物质模式，但回归性能在站点之间变化（解释方差36-70％，归一化的根均线误差9-19％）。位点之间还有可变性的Sentinel-2或行星扫描数据更适合检测生物质图案以及最重要的预测因子。地形信息在大多数地点都有一个次要或可忽视的重要性。我们的研究结果表明，卫星衍生的植被绿色和生物量之间没有易于普遍的关系。

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  • 来源
    《International journal of remote sensing》 |2021年第12期|4532-4557|共26页
  • 作者

    Rasanen Aleksi; Wagner Julia; Hugelius Gustaf; Virtanen Tarmo;

  • 作者单位

    Univ Helsinki Fac Biol & Environm Sci Ecosyst & Environm Res Programme Helsinki Finland;

    Stockholm Univ Dept Phys Geog Stockholm Sweden;

    Stockholm Univ Dept Phys Geog Stockholm Sweden|Stockholm Univ Bolin Ctr Climate Res Stockholm Sweden;

    Univ Helsinki Fac Biol & Environm Sci Ecosyst & Environm Res Programme Helsinki Finland;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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