Quality assurance and assessment framework for land cover maps validation in the Copernicus Hot Spot Monitoring activity

Abstract

The Copernicus High-Resolution Hot Spot Monitoring activity (C-HSM) delivers a global dataset of Key Landscapes for Conservation (KLC), which are characterized by pronounced anthropogenic pressures that require high mapping accuracy. Detailed land cover and land cover change map products are freely available through the activity and include extensive map production accuracy assessments. Without a complete understanding of the map products’ spatial, temporal and logical consistencies, quality or quantified confidence levels, usability is reduced and can affect stakeholder decision-making and the implementation of sustainable solutions. For the quantitative accuracy assessment, a stratified random sampling approach was implemented where special emphasis was placed on (i) allocation of sampling units for rare land cover change categories; (ii) effective and accurate labelling of large numbers of sampling units; (iii) accuracy and area estimation in one consistent approach; and (iv) derivation of confidence intervals for all accuracy measures and area estimates. To handle correlations, large uncertainties, and complex probability density functions, bootstrapping was applied instead of analytical equations, which are based on normality assumptions. This paper presents the Quality Assurance and Quality Control framework applied to validate all the C-HSM thematic map products. The Kundelungu-Upemba KLC product results are presented as our use case.

Keywords

• validation
• map accuracy
• land cover
• key landscape for conservation
• copernicus