Abstract

Land cover is one of the key terrestrial variables used for monitoring and as input for modelling in support of achieving the United Nations Strategical Development Goals. Global and Continental Land Cover Products (GCLCs) aim to provide the required harmonized information background across areas; thus, they are not being limited by national or other administrative nomenclature boundaries and their production approaches. Moreover, their increased spatial resolution, and consequently their local relevance, is of high importance for users at a local scale. During the last decade, several GCLCs were developed, including the Global Historical Land-Cover Change Land-Use Conversions (GLC), the Globeland-30 (GLOB), Corine-2012 (CLC) and GMES/ Copernicus Initial Operation High Resolution Layers (GIOS). Accuracy assessment is of high importance for product credibility towards incorporation into decision chains and implementation procedures, especially at local scales. The present study builds on the collaboration of scientists participating in the Global Observations of Forest Cover—Global Observations of Land Cover Dynamics (GOFC-GOLD), South Central and Eastern European Regional Information Network (SCERIN). The main objective is to quantitatively evaluate the accuracy of commonly used GCLCs at selected representative study areas in the SCERIN geographic area, which is characterized by extreme diversity of landscapes and environmental conditions, heavily affected by anthropogenic impacts with similar major socio-economic drivers. The employed validation strategy for evaluating and comparing the different products is detailed, representative results for the selected areas from nine SCERIN countries are presented, the specific regional differences are identified and their underlying causes are discussed. In general, the four GCLCs products achieved relatively high overall accuracy rates: 74–98% for GLC (mean: 93.8%), 79–92% for GLOB (mean: 90.6%), 74–91% for CLC (mean: 89%) and 72–98% for GIOS (mean: 91.6%), for all selected areas. In most cases, the CLC product has the lower scores, while the GLC has the highest, closely followed by GIOS and GLOB. The study revealed overall high credibility and validity of the GCLCs products at local scale, a result, which shows expected benefit even for local/regional applications. Identified class dependent specificities in different landscape types can guide the local users for their reasonable usage in local studies. Valuable information is generated for advancing the goals of the international GOFC-GOLD program and aligns well with the agenda of the NASA Land-Cover/Land-Use Change Program to improve the quality and consistency of space-derived higher-level products.

Highlights

  • Standardized global and continental land cover (GCLC) products provide key terrestrial reference baseline data for numerous global, regional and national scale applications and inputs for large scale economic land use and ecosystem modelling

  • Several global and continental land cover products of varied spatial resolution have been developed for example, Globeland-30, Corine-2012, GlobeCover-2009, Global Historical Land-Cover Change and Land-Use Conversions, UMD land-cover product [1]

  • The validation process indicated that the four GCLCs products show a rather good overall accuracy (OA) at the studied SCERIN areas

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Summary

Introduction

Standardized global and continental land cover (GCLC) products provide key terrestrial reference baseline data for numerous global, regional and national scale applications and inputs for large scale economic land use and ecosystem modelling. Recent studies have shown that when global land cover products are compared, there are significant spatial disagreements across land cover types [2,3]. This is due to the actual thematic class definition, which can be quite different from product to product, the use of different satellite sensors, the classification methodologies and the lack of sufficient in situ data. Different approaches exist for the high resolution GCLC products validation

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