Strategic landscape analysis relating multicriteria analysis and socioeconomic and environmental context to define potential areas for active restoration in São Paulo, Brazil

To optimize forest restoration initiatives, landscape planning emerges as a strategy. Thus, this work aims to determine the active restoration potential in Vale do Paraíba, a Brazilian region inserted in the Atlantic Forest biome, using multicriteria analysis and analyzing the result in light of socioeconomic and environmental contexts. Land use and land cover (LULC), hydrography, and slope variables were used in the multicriteria analysis, while average municipal income per capita, availability of restoration areas on rural lands, and water supply basins were used as socioeconomic and environmental variables. Analytic Hierarchy Process (AHP) and Fuzzy Inference by the gamma operator were employed as multicriteria analysis methods. Two comparisons were performed with AHP, resulting in weights of 0.6 (LULC) and 0.2 (slope and hydrography) for AHP 1, and 0.5 (LULC) and 0.25 (slope and hydrography) for AHP 2. Values of 0.4, 0.6, and 0.8 were used in the gamma operator in Fuzzy Inference. Comparing results with restoration sites already implemented, AHP 2 was considered the best method. The restoration potential of each municipality was determined. Then, we grouped those with more areas for restoration, as an opportunity to develop common forest restoration programs. Ten water supply basins were identified with more than 40% of region extension with high restoration potential. Municipalities with a lower average per capita income and higher restoration potential were identified, highlighting a potential to generate income through restoration. The study concluded that Vale do Paraíba has a high potential for active restoration. •A strategic planning by multicriteria analysis was done to delimit restoration potential.•With few physical variables it was possible to approach to the restoration practice.•43% of the Vale do Paraíba presents high active restoration potential.•The results can guide decision makers in the implementation of restoration projects.