Geospatial data for sustainable development goals monitoring: A case study of forest cover dynamics in Romania

Abstract

Monitoring, evaluating, and implementing the Sustainable Development Goals (SDGs), as defined by the United Nations’ 2030 Agenda - require the integration of high-quality, up-to-date datasets with a spatial component. Among the indicators in this group is SDG 15.1.1, which measures “Forest area as a proportion of total land area”. In this study, we demonstrate how open-source geospatial datasets (such as those provided by the Copernicus Land Monitoring Services) can be combined with long-term national statistical data from the National Institute of Statistics (INS) to gain insights into forest cover dynamics between 1990 and 2023. Statistical and spatial analyses were conducted on time-series data to map the evolution of forest cover across all Romanian counties (NUTS 3), as well on the national level and by local administrative unit (LAU). The dataset comprises 34 annual records, enabling both the analysis of macro-level trends and the identification of annual anomalies. Our analysis reveals a stable national average forest cover, but with pronounced heterogeneity at the county level. Certain counties recorded notable increases or losses in forest area, some exhibiting abrupt year-to-year reversals or near-static forest levels over decades. Our analysis also highlights inconsistencies in national forest cover reporting across different sources. Comparing information from different sources – INS, Food and Agriculture Organization (FAO) and Copernicus Land High Resolution Layer (HRL) – shows that varying reporting methods and dataset structures lead to different results, depending on the data used. These findings highlight the necessity of integrating diverse data sources and geospatial approaches to ensure accurate and scalable assessments of forest dynamics in support of sustainable development objectives.