Mapping terrestrial ecosystem health in drylands: comparison of field-based information with remotely sensed data at watershed level

Abstract Context Combining field-based assessments with remote-sensing proxies of landscape patterns provides the opportunity to monitor terrestrial ecosystem health status in support sustainable development goals (SDG). Objectives Linking qualitative field data quantitative imagery map (SDG15.3.1 “land degradation neutrality”). Methods A approach using Interpreting Indicators Rangeland-Health (IIRH) protocol was applied classify at watershed level as “healthy”, “at-risk”, and “unhealthy”. Quantitative complex metrics derived from Landsat spaceborne were used explore whether similar statuses can be retrieved on a broader scale. The assignment classes based remotely sensed tested multivariate cluster analysis methods. Results According IIRH assessments, soil surface loss, plant mortality, invasive species identified important indicators health. metrics, “healthy” sites had lower amounts spectral heterogeneity, edge density, resource leakage. We found high agreement between clusters (NMI = 0.91) when combined DBSCAN k -means clustering together non-metric multi-dimensional scaling (NMDS). Conclusions provide an exemplary workflow how combine assess SDGs related As we standardized method for publicly available satellite data, there is potential test generalizability context-dependency our other arid semi-arid rangelands.