An economic analysis algorithm for urban forestry projects

The second half of the 20th century was characterized by rapid growth of the urban population and lack of attention to environmental quality in the urbanizes territories. Thus, the development of many cities during that period took place through policies which, over time, resulted in a disaggregated landscape, both in morphological and functional terms. In some cases, these policies have caused the creation of land portions without a specific characterization, and the generation of urban voids that negatively affect the city's development. To solve this problem, the public administration sectors of many countries are looking for new intervention strategies that are feasible from a social and economic point of view which are able to guarantee sustainable development. From this perspective, the execution of urban regeneration initiatives, including forestation, allows for the improvement of both environmental quality and citizens' well-being, and promotes economic development. Considering the multiple effects that these initiatives can generate and the limited availability of public and private resources, it is appropriate to use multicriteria decision support tools through which it is possible to evaluate the interventions' complexity and best identify the city areas that lend themselves to be recovered and improved through the forestation. The aim of this work is to develop a support tool for public administrations aimed at identifying the optimal forestry projects' location according to criteria that not only refer to financial type, but also their social, cultural, and environmental nature. Using Discrete Linear Programming algorithms, the model has been tested through a theoretical case study and reveals the advantages and limitations of the model, as well as future research prospects