Creating land use-land cover baselines for monitoring Land Degradation Neutrality in Switzerland

Akinyemi, Felicia O.; Bär, Valentin; Ifejika Speranza, Chinwe (27 May 2022). Creating land use-land cover baselines for monitoring Land Degradation Neutrality in Switzerland. In: EGU General Assembly 2022. 10.5194/egusphere-egu22-6523

The non-availability of annual land cover maps for Switzerland at the national and local levels hampers setting a Land Degradation Neutrality (LDN) baseline (2000 – 2015) and monitoring until the year 2030. Land cover change is an LDN sub-indicator required to assess the proportion of degraded land to total land area (Sustainable Development Goal 15 indicator — SDG15.3.1). The Swiss version of the European CORINE Land Cover (CLC), which is available for the years 1990, 2000, 2006, 2012 and 2018, is often used to analyse land cover and land cover change. However, the approximately 6-year production cycle of the CLC is only partially in line with the internationally agreed LDN baseline and monitoring periods.

Yet, annual land cover maps are required not only for baseline setting but crucial for monitoring the SDG15.3.1 on an annual basis until 2030. Further, most studies evaluating the effects of land cover and change often do not consider the impact of differing annual land cover configurations and sizes on their analysis results. Doing so is important, especially for the LDN, because of the pervasive influence land cover and its changes have on other sub-indicators such as Land Productivity Dynamics (LPD) and the change in Soil Organic Carbon stock, whose computation is currently based on land cover change.

Aimed at contributing to the scientific basis for operationalizing LDN for Switzerland, this study developed and applied a remote sensing-based method for generating land cover data. It took advantage of the availability of big spatial data (e.g., Sentinel-1 and Sentinel-2 satellite images, digital elevation model — DEM, CLC) to map land cover for the years 2015 and 2020, with reference datasets created with high resolution images. For 2015 and 2020, 100 training and validation points were created for each of the seven land cover classes (Forest, Grassland, Cropland, Wetland, Artificial Surfaces, and Otherland). Land cover change was calculated for the baseline period of 2000 – 2015 and 2016 – 2020 for the monitoring period. DEM was used in land cover classification, as topography was one of the main limiting factors for identifying land use types, particularly the need to reduce misclassifications of shady mountainous areas.

The methodology and results provide a basis for periodic assessments of the land cover dimension of the LDN and for automating the production of annual land cover maps for Switzerland. Evaluating the changes in land cover both for the baseline and monitoring periods also enabled us to separately analyze how changes in land cover differed between both periods. The land cover change for the monitoring period until 2020 was compared to the baseline, based on which we identify and discuss some challenges relating to land degradation in Switzerland.

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