Land degradation mapping and assessment using object-based image analysis

Abstract

he Intergovernmental Working Group (IWG) of the United Nations Convention to Combat Desertification (UNCCD) defined land degradation neutrality (LDN) as a state whereby the amount and quality of land resources, necessary to support ecosystem functions and services and enhance food security, remains stable or increases within specified temporal and spatial scales and ecosystems. In this context, several initiatives have been involved in mapping land degradation for setting national voluntary LDN targets under UNCCD using the following three indicators: landcover/land-use, land productivity, and soil organic carbon (SOC) stocks. Accordingly, this work aimed at investigating innovative techniques for mapping land degradation within the Qaraoun catchment area in Lebanon. More specifically, the specific objectives were to produce geospatial data for assessing baseline trends in landcover/land-use, land productivity, and soil organic carbon stocks, and consequently, identify areas of intervention for implementing sustainable land management practices. Mapping techniques such as Geographic Object-Based Image Analysis (GEOBIA) is employed in this work. Such techniques provide the possibility of taking multi-resolution and multi-source image processing at a very advanced level. Employed satellite images included: MODIS (MOD17A3H Version 6 product) in addition to multi-temporal satellite Landsat TM and Landsat 8 imagery (30 m) and Sentinel 2A imagery (10 m). Based on the mapping results, degradation was considered as most likely to occur when: negative land cover change occurred; or b) land productivity decreased significantly; or SOC stock decreased significantly. A 2-step process for validation of the assessments included: assessment using Collect Earth (CE) carried out by processing high resolution imagery of specific plots in the study area and, field surveys using pre-designed field forms. Collect Earth communicates with Google Earth Engine to facilitate access to freely available very high satellite images from Earth Engine. Finally, the initial identification of areas of intervention for conducting sustainable land management practices includes a spatial analysis of land degradation. More specifically, land degradation and fragmentation are assessed based on the following factors: number of patches within each administrative unit, mean patch size, largest patch size, edge length, mean nearest neighbor distance, clumpiness index, and aggregation index. Overall, assessment of land degradation trends, coupled with land fragmentation analysis, is an essential step towards understanding current state of land degradation, revealing anomalies and identifying degraded areas. Such an assessment will provide an evidence-based restoration targets, informed decisions-making on potential interventions (e.g., rehabilitation, prevention, mitigation of land degradation) and prioritizing efforts in areas where degradation exists or is taken place.