Salko Sini-Selina, Juola Jussi, Burdun Iuliia, Vasander Harri, Rautiainen Miina
School of Engineering Aalto University Espoo Finland.
Department of Forest Sciences University of Helsinki Helsinki Finland.
Ecol Evol. 2023 Jun 13;13(6):e10197. doi: 10.1002/ece3.10197. eCollection 2023 Jun.
Boreal peatlands store ~25 % of global soil organic carbon and host many endangered species; however, they face degradation due to climate change and anthropogenic drainage. In boreal peatlands, vegetation indicates ecohydrological conditions of the ecosystem. Applying remote sensing would enable spatially and temporally continuous monitoring of peatland vegetation. New multi- and hyperspectral satellite data offer promising approaches for understanding the spectral properties of peatland vegetation at high temporal and spectral resolutions. However, using spectral satellite data to their fullest potential requires detailed spectral analyses of dominant species in peatlands. A dominant feature of peatland vegetation is the genus mosses. We investigated how the reflectance spectra of common boreal mosses, collected from waterlogged natural conditions after snowmelt, change when the mosses are desiccated. We conducted a laboratory experiment where the reflectance spectra (350-2500 nm) and the mass of 90 moss samples (representing nine species) were measured repetitively. Furthermore, we examined (i) their inter- and intraspecific spectral differences and (ii) whether the species or their respective habitats could be identified based on their spectral signatures in varying states of drying. Our findings show that the most informative spectral regions to retrieve information about the species and their state of desiccation are in the shortwave infrared region. Furthermore, the visible and near-infrared spectral regions contain less information on species and moisture content. Our results also indicate that hyperspectral data can, to a limited extent, be used to separate mosses belonging to meso- and ombrotrophic habitats. Overall, this study demonstrates the importance of including data especially from the shortwave infrared region (1100-2500 nm) in remote sensing applications of boreal peatlands. The spectral library of mosses collected in this study is available as open data and can be used to develop new methods for remote monitoring of boreal peatlands.
北方泥炭地储存了全球约25%的土壤有机碳,并且是许多濒危物种的栖息地;然而,由于气候变化和人为排水,它们正面临退化。在北方泥炭地,植被反映了生态系统的生态水文状况。应用遥感技术能够对泥炭地植被进行空间和时间上的连续监测。新的多光谱和高光谱卫星数据为以高时间和光谱分辨率了解泥炭地植被的光谱特性提供了有前景的方法。然而,要充分发挥光谱卫星数据的潜力,需要对泥炭地中的优势物种进行详细的光谱分析。泥炭地植被的一个主要特征是苔藓属。我们研究了从融雪后涝渍自然条件下采集的常见北方苔藓在干燥时其反射光谱如何变化。我们进行了一项实验室实验,重复测量了90个苔藓样本(代表9个物种)的反射光谱(350 - 2500纳米)和质量。此外,我们研究了(i)它们种间和种内的光谱差异,以及(ii)是否可以根据它们在不同干燥状态下的光谱特征来识别物种或其各自的栖息地。我们的研究结果表明,用于获取有关物种及其干燥状态信息的最具信息量的光谱区域在短波红外区域。此外,可见光和近红外光谱区域关于物种和水分含量的信息较少。我们的结果还表明,高光谱数据在一定程度上可用于区分属于中营养和雨养营养栖息地的苔藓。总体而言,本研究证明了在北方泥炭地遥感应用中纳入特别是来自短波红外区域(1100 - 2500纳米)数据的重要性。本研究中收集的苔藓光谱库作为开放数据提供,可用于开发北方泥炭地远程监测的新方法。