Landscape Information Modelling to Improve Feedback in the Geodesign International Collaboration for Carbon Credit Enhancement in Metropolitan Regions – The Case Study of Fortaleza, Brazil

Better landscape designs demand better landscape analysis and vice versa. At regional scale, this feedback demands precision and integration among multiple scales. This work prospects the potential of information modelling to improve Geodesign in decision making and collaborative design through increasing feedback. As a participant of the International Geodesign Collaboration (IGC) workshop “Trees for Metropolitan Regions”, this research has been developed for the Metropolitan Region of Fortaleza (MRF), the 6th largest in Brazil, located on the Northeast coast, and aimed at increasing green areas for Carbon Credit (CC) purposes. This methodological research achieved a script for subsequently information modelling application, which will improve precision in the achievement and evaluation of pre-established goals.

Six methodological steps accomplished a selection of data for latter parametric modelling: 1. Reading enrichment and definition of the planning concept; 2. Division of the metropolitan region into Landscape Units (LU); 3. Selection of squared cut out samples for each LU; 4. Proposition of innovative solutions; 5. Design for CC increment through conservation, expansion, and creation of green areas; 6. Evaluation of CC enhancement and feedback. For the fifth step, three future scenarios have been designed, in 2035 and 2050: the traditional, the late adopter and the early adopter. Replicating designed green areas from samples to their respective LU resulted in a total CC increase of 33.19% for the traditional scenario, 44.29% for the late adopter and 87.71% for the early adopter, all for 2050, which goal has been established by the IGC at 30%. Information modelling, using the identified parameters in this work, may review, accelerate and improve these results. This improvement will be enhanced when precision of sample recognition is increased to define smaller cut out squares. With opportunities of resources for data processing and design, information modelling allows the design of samples on microscale to feedback regional planning, which leads to adaptive goals and to develop a valuable tool for integration among multiple scales through Landscape Information Modeling (LIM).