Avoiding, reducing, and reversing land degradation and restoring degraded land is an urgent priority to protect the biodiversity and ecosystem services that are vital to life on Earth. To halt and reverse the current trends in land degradation, there is an immediate need to enhance national capacities to undertake quantitative assessments and mapping of their degraded lands, as required by the Sustainable Development Goals (SDGs), in particular, the SDG indicator 15.3.1 (“proportion of land that is degraded over total land area”). Earth Observations (EO) can play an important role both for generating this indicator as well as complementing or enhancing national official data sources.

Implementations like Trends.Earth to monitor land degradation in accordance with the SDG15.3.1 rely on default datasets of coarse spatial resolution provided by MODIS or AVHRR. Consequently, there is a need to develop methodologies to benefit from medium to high-resolution satellite EO data (e.g. Landsat or Sentinels). In response to this issue, this paper presents an initial overview of an innovative approach to monitor land degradation at the national scale in compliance with the SDG15.3.1 indicator using Landsat observations using a data cube but further work is required to improve the calculation of the three sub-indicators.

At the global scale, the main drivers of land degradation are the high consumption lifestyles of the most developed economies, and the rising consumption in developing and emerging economies. This, combined with population growth, is driving unsustainable levels of agricultural expansion, natural resource and mineral extraction, and urbanization, which typically lead to greater levels of land degradation (Ivits & Cherlet, 2013). Consequently, timely action to avoid, reduce, and reverse land degradation can increase food and water security, can contribute substantially to the adaptation and mitigation of climate change and biodiversity loss, could reduce conflict and migration; and ultimately is essential for meeting many of the Sustainable Development Goals defined in the Agenda 2030 for Sustainable Development (IPBES, 2018; United Nations, 2015)

The indicator is derived from a binary classification of land condition (i.e. degraded or not degraded) of a harmonized set of three measurable sub-indicators:

land cover and land cover changes, to assess the possible loss of ecosystem services that are valuable in a local or national contact (Andrew, Wulder, & Nelson, 2014; Ban, Gong, & Gini, 2015; Burkhard, Kroll, Müller, & Windhorst, 2009).

land productivity trends, to determine changes in health and productive capacity of the land. It usually reflects the net effects of changes in ecosystem functioning (e.g. plant and biomass growth) and declining trends can be a defining characteristic of land degradation (Cowie et al., 2018; Oehri, Schmid, Schaepman-Strub, & Niklaus, 2017).

soil organic carbon trends, to quantify overall soil quality associated with nutrient cycling and its aggregate stability and structure with direct implications for water infiltration, soil biodiversity, vulnerability to erosion, and ultimately the productivity of vegetation, and in agricultural contexts, yields (Hengl et al., 2014; Stumpf et al., 2018).

For each of the sub-indicators, countries can access a wide range of data source (e.g. EO and geospatial data), while at the same time ensuring national ownership (United Nations, 2015).