Living Earth: Implementing national standardised land cover classification systems for Earth Observation in support of sustainable development

Abstract

Earth Observation (EO) has been recognised as a key data source for supporting the United Nations Sustainable Development Goals (SDGs). Advances in data availability and analytical capabilities have provided a wide range of users access to global coverage analysis-ready data (ARD). However, ARD does not provide the information required by national agencies tasked with coordinating the implementation of SDGs. Reliable, standardised, scalable mapping of land cover and its change over time and space facilitates informed decision making, providing cohesive methods for target setting and reporting of SDGs. The aim of this study was to implement a global framework for classifying land cover. The Food and Agriculture Organisation's Land Cover Classification System (FAO LCCS) provides a global land cover taxonomy suitable to comprehensively support SDG target setting and reporting. We present a fully implemented FAO LCCS optimised for EO data; Living Earth, an open-source software package that can be readily applied using existing national EO infrastructure and satellite data. We resolve several semantic challenges of LCCS for consistent EO implementation, including modifications to environmental descriptors, inter-dependency within the modular-hierarchical framework, and increased flexibility associated with limited data availability. To ensure easy adoption of Living Earth for SDG reporting, we identified key environmental descriptors to provide resource allocation recommendations for generating routinely retrieved input parameters. Living Earth provides an optimal platform for global adoption of EO4SDGs ensuring a transparent methodology that allows monitoring to be standardised for all countries.

A globally relevant change taxonomy and evidence‐based change framework for land monitoring

“…Unlike previous classification approaches, EODESM was uniquely able to access and use the many thousands of categories defined by the FAO LCCS (Owers et al, 2021 ), each of which has a biophysical meaning to generate comprehensive classifications of land cover. This capacity was further demonstrated by Lucas et al ( 2019 ), who initially conveyed the principles behind EODESM and applied the approach to map land covers for selected sites in Australia by integrating EDs retrieved or classified from dense time‐series of Landsat sensor data.…”

“…Conventions for categorical codes are less common, although in many land cover taxonomies, numeric codes for different descriptions of the environment are stated (e.g., those specific to different leaf types, water states or water hydro-periods within the LCCS; Owers et al, 2021). Consistent code sets have also been put in place for other categories such as plant species (e.g., Turland et al, 2018).…”

“…OEDs representing vegetated and aquatic land covers can be interpreted in the field or mapped (e.g., by thresholding summaries of satellite‐derived vegetation cover fraction [%] or water extent, as determined from temporal observations of water occurrence [frequency over time]). Artificial surfaces (ASs) or cultivated land can be classified directly using, for example, machine‐learning algorithms (Owers et al, 2021 ).…”

“…Herein, these are referred to as Essential Environmental Descriptors (EEDs) as they are needed to define and deliver classifications according to the taxonomy used, either partially or in full. Continuing with the LCCS as the example, the modular‐hierarchical phase (Figure 2 ), termed Level 4 by Lucas et al ( 2019 ) and Owers et al ( 2021 ), includes sub‐levels (I–IV) that successively reference relevant sets of EDs and combine these to provide the final land cover class. Once constructed, further detail can again be added by integrating relevant Additional Environmental Descriptors (AEDs).…”

“…To ensure consistency in the construction and description of land cover classes and scalability of observations, measurements and maps across both space and time (and from local to planetary levels), EDs need to be continuous or categorical and assigned, respectively, defined and measurable units or pre‐defined codes. Conventions for categorical codes are less common, although in many land cover taxonomies, numeric codes for different descriptions of the environment are stated (e.g., those specific to different leaf types, water states or water hydro‐periods within the LCCS; Owers et al, 2021 ). Consistent code sets have also been put in place for other categories such as plant species (e.g., Turland et al, 2018 ).…”