LAND IT

This master’s thesis was the foundation for LAND IT. The main features available in LAND IT were developed during this research, such as scenario analysis and comparison, scenario sharing, and the creation and editing of geometries within scenarios. The case study used for its development was the municipality of Mação and its nine AIGPs.

This thesis focuses on post-territorial reorganisation, aiming to develop economic models to calculate the profits and costs associated with land use in the years following transformation. The study covered the following land uses: maritime pine, eucalyptus, cork oak, and olive groves. Additionally, a feasibility analysis was conducted on the installation of solar panels in the municipality of Mação.

Portugal has faced severe wildfires, leading to the creation of the AIGP programme aimed at making the landscape more resilient. To optimise this process, LAND IT was developed — a decision support system that facilitates the creation and management of territorial design proposals. It enables scenario comparison and helps prevent input errors. The municipality of Mação was used as a case study and showed very positive results.

The objective of this research is to add editing tools to LAND IT, including geometry editing tools, topological verification tools, and intelligent tools to assist users in the creation of AIGP proposals, such as a filtering system.

Currently, LAND IT has very basic collaboration features, such as timers for handling requests. This thesis aims to identify and improve all use cases where real-time updates are essential. Furthermore, it will explore collaborative map editing, enabling multiple users to draw geometries within the same scenario simultaneously.

LAND IT includes some dashboards with statistical data developed in the early stages of the project. Currently, some of these charts are outdated, while others fail to cover relevant topics. Thus, the objective of this thesis is to enhance existing dashboards and propose new ones.

As LAND IT is a growing platform that continuously evolves alongside the development of AIGP, new functionalities are always required. To facilitate this ongoing integration, the objective of this thesis is to develop an extension system that enables the modular addition of new features without modifying the system’s core code.