Mapping of ESA-CCI land cover data to plant functional types for use in the CLASSIC land model

Abstract

Abstract. Plant functional types (PFTs) are used to represent vegetation distribution in land surface models (LSMs). Large differences are found in the geographical distribution of PFTs currently used in various LSMs. These differences arise from the differences in the underlying land cover products but also the methods used to map or reclassify land cover data to the PFTs that a given LSM represents. There are large uncertainties associated with existing PFT mapping methods since they are largely based on expert judgment and therefore are subjective. In this study, we propose a new approach to inform the mapping or the cross-walking process using analyses from sub-pixel fractional error matrices, which allows for a quantitative assessment of the fractional composition of the land cover categories in a dataset. We use the Climate Change Initiative (CCI) land cover product produced by the European Space Agency (ESA). A previous study has shown that compared to fine-resolution maps over Canada, the ESA-CCI product provides an improved land cover distribution compared to that from the GLC2000 dataset currently used in the CLASSIC (Canadian Land Surface Scheme Including Biogeochemical Cycles) model. A tree cover fraction dataset and a fine-resolution land cover map over Canada are used to compute the sub-pixel fractional composition of the land cover classes in ESA-CCI, which is then used to create a cross-walking table for mapping the ESA-CCI land cover categories to nine PFTs represented in the CLASSIC model. There are large differences between the new PFTs and those currently used in the model. Offline simulations performed with the CLASSIC model using the ESA-CCI based PFTs show improved winter albedo compared to that based on the GLC2000 dataset. This emphasizes the importance of accurate representation of vegetation distribution for realistic simulation of surface albedo in LSMs. Results in this study suggest that the sub-pixel fractional composition analyses are an effective way to reduce uncertainties in the PFT mapping process and therefore, to some extent, objectify the otherwise subjective process.

Evaluating the performance of the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) tailored to the pan-Canadian domain

“…It was generated by the (European Space Agency, 2017) by applying a combination of machine learning and unsupervised image classification methods to three products: Environmental Satellite (ENVISAT;2003, SPOT-VEG (1999, and Project for On-Board Autonomy Vegetation (PROBA-V;. Finally, Hybrid is a Canada-specific product generated by Wang et al (2022). It combines NALCMS with a land cover classification generated by Hermisilla et al (2018) using the Virtual Land Cover Engine (VLCE).…”

“…The VLCE product was generated with a random forest-based classification method using Landsat time-series data and informed by forest change and digital elevation information derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). The Hybrid product has 17 classes and blends the detailed land cover classification of NALCMS with a more accurate forest cover mapping by VLCE (Wang et al, 2022). Based on field survey data and expert knowledge of global biomes and class descriptions, we use cross-walking tables to convert each dataset's land cover classes into the nine default PFTs in CLASSIC (Table 1) (Wang et al, 2006(Wang et al, , 2019(Wang et al, , 2022.…”

“…The Hybrid product has 17 classes and blends the detailed land cover classification of NALCMS with a more accurate forest cover mapping by VLCE (Wang et al, 2022). Based on field survey data and expert knowledge of global biomes and class descriptions, we use cross-walking tables to convert each dataset's land cover classes into the nine default PFTs in CLASSIC (Table 1) (Wang et al, 2006(Wang et al, , 2019(Wang et al, , 2022. Information about shrub fractional cover is available in the underlying Hybrid product, however, the default nine PFTs do not include shrubs so we assign a fraction of the shrub cover to the tree PFTs and the remainder to the C3 grass PFT in Hybrid-9PFT.…”

“…We specify the fractional coverage of these three PFTs by creating a cross-walking table for the Hybrid product that includes 12 PFTs (i.e. the default nine plus the three non-tree new PFTs; Table S1) (Wang et al, 2006(Wang et al, , 2019(Wang et al, , 2022.…”

“…Plant functional types (PFTs) are commonly used in land surface models (LSMs) to represent broad groups of vegetation with similar characteristics such as their growth form, phenological patterns, or photosynthetic pathways (Bonan et al, 2002;Box, 1996;Smith et al, 1993;Ustin & Gamon, 2010). There are, however, large differences in the coverage and type of PFTs used in LSMs, which in turn impact the simulated fluxes of matter and energy from the land surface (Fritz et al, 2011;Hartley et al, 2017;Ottlé et al, 2013;Wang et al, 2022). Moreover, the PFTs used in LSMs have historically been developed to represent global patterns of vegetation and their associated traits (Bonan et al, 2002;Box, 1996;Melton et al, 2020;Wullschleger et al, 2014).…”