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.

Highlights

  • IntroductionForest extent mapping is required for land cover (LC) and land use classification, and for monitoring changes (e.g., damage, afforestation, deforestation) in ecosystem state

  • Forest extent mapping is required for land cover (LC) and land use classification, and for monitoring changes in ecosystem state

  • Our results show that tree cover was either overestimated or underestimated depending on the LC product, and classification accuracy varied between 42 and 75%

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Summary

Introduction

Forest extent mapping is required for land cover (LC) and land use classification, and for monitoring changes (e.g., damage, afforestation, deforestation) in ecosystem state. The quantification of global forest resources spatially and temporally relies on the international definition of forest land area by the Food and Agriculture Organization of the United Nations (FAO): a forest is “land spanning more than 0.5 hectares with trees higher than 5 meters and a canopy cover of more than 10 percent, or trees able to reach these thresholds in situ.” (FRA 2015). The International Geosphere-Biosphere Programme (IGBP) employs a tree cover threshold of >60%, and the United Nations Framework Convention on Climate Change (UNFCCC) uses tree cover thresholds of >10% (e.g., FAO international forest definition) and >30% (e.g., FAO global forest ecological zone mapping) to classify an area as a forest. An operational vegetation continuous field (VCF) product (MODIS VCF 2017) from MODIS (i.e., MOD44B) is known to suffer from underestimating high cover and overestimating low cover (e.g., Heiskanen 2008; Sexton et al 2013)

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