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全球土地覆盖产品中树木覆盖的表示:以芬兰为例。

Representation of tree cover in global land cover products: Finland as a case study area.

机构信息

School of Engineering, Department of Built Environment, Aalto University, P.O. Box 14100, 00076, Aalto, Finland.

School of Electrical Engineering, Department of Electronics and Nanoengineering, Aalto University, P.O. Box 14100, 00076, Aalto, Finland.

出版信息

Environ Monit Assess. 2021 Feb 12;193(3):121. doi: 10.1007/s10661-021-08898-2.

Abstract

Forest extent mapping is required for climate modeling and monitoring changes in ecosystem state. Different global land cover (LC) products employ simple tree cover (referred also as "forest cover" or even "vegetation cover") definitions to differentiate forests from non-forests. Since 1990, a large number of forest extent maps have become available. Although many studies have compared forest extent data, they often use old data (i.e., around the year 2000). In this study, we assessed tree cover representations of three different annual, global LC products (MODIS VCF (MOD44B, Collection 6 (C6)), MCD12Q1 (C6), and CCI LC (v.2.1.1)) using the Finnish Multi-Source National Forest Inventory (MS-NFI) data for the year 2017. In addition, we present an intercomparison approach for analyzing spatial representations of coniferous and deciduous species. Intercomparison of different LC products is often overlooked due to challenges involved in non-standard and overlapping LC class definitions. Global LC products are used for monitoring changes in land use and land cover and modeling of surface fluxes. Given that LC is a major driver of global change through modifiers such as land surface albedo, more attention should be paid to spatial mapping of coniferous and deciduous species. Our results show that tree cover was either overestimated or underestimated depending on the LC product, and classification accuracy varied between 42 and 75%. Intercomparison of the LC products showed large differences in conifer and deciduous species spatial distributions. Spatial mapping of coniferous and deciduous tree covers was the best represented by the CCI LC product as compared with the reference MS-NFI data.

摘要

森林范围测绘对于气候建模和监测生态系统状态变化至关重要。不同的全球土地覆盖(LC)产品采用简单的树木覆盖(也称为“森林覆盖”甚至“植被覆盖”)定义来区分森林和非森林。自 1990 年以来,已经有大量的森林范围地图可供使用。尽管许多研究比较了森林范围数据,但它们通常使用旧数据(即,2000 年左右)。在本研究中,我们使用芬兰多源国家森林清查(MS-NFI)数据(2017 年)评估了三种不同的年度全球 LC 产品(MODIS VCF(MOD44B,第 6 版(C6))、MCD12Q1(C6)和 CCI LC(v.2.1.1))的树木覆盖表示。此外,我们提出了一种分析针叶树和阔叶树种空间表示的比较方法。由于涉及到非标准和重叠的 LC 类定义,不同 LC 产品的比较通常被忽视。全球 LC 产品用于监测土地利用和土地覆盖的变化以及地表通量的建模。鉴于 LC 通过土地表面反照率等修饰剂成为全球变化的主要驱动因素,应该更加关注针叶树和阔叶树种的空间测绘。我们的结果表明,树木覆盖要么被高估,要么被低估,这取决于 LC 产品,分类精度在 42%至 75%之间变化。LC 产品的比较表明,针叶树和阔叶树物种的空间分布存在很大差异。与参考 MS-NFI 数据相比,CCI LC 产品在针叶树和阔叶树覆盖的空间测绘方面表现最佳。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dca2/7880955/3bc2adaef4cb/10661_2021_8898_Fig1_HTML.jpg

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