IN-PERSON Lisbon Livable Cities. Section A

Abstract

In partnership with The City of [Redacted], this research uses a custom-designed Python script to deploy an analytic algorithm that can synthesize geospatial data metrics to uncover financial and business case potential across land parcels in the city of [Redacted]. Aiming to give Municipalities and community advocates alike the financial and business language and arguments to defend and catalyze ecological and/or sustainable development solutions to present challenges like climate change, this transdisciplinary project aligns finance innovation methods with critical cartography and public policy. The work first assembled a geolocated inventory of underutilized spatial assets in the city of [Redacted] using the Civic Commons Catalyst (CCC) Initiative framework. Five categories (private vacant lots, public vacant lots, private parking lots, public parking lots, and undeveloped school sites) organized the catalog that involved analyzing satellite imagery, real estate and parking authority listings, and [Redacted]’s MyProperty tool, which provides updated parcel and land-use data. Trends across various zoning types and different regions of the city revealed insights that, when cross-examined with the business and mathematical modeling of urban agriculture (informed by a literature review), further clarified the latent business potential of activating unproductive land with food supply chain localization. Variables examined included Net Present Value (NPV), Return on Investment (ROI), jobs created, wages paid, and total produce servings generated. The algorithmic and computational design methodology applied to this geospatial data question underscores the substantial benefits of urban agriculture in enhancing food security, boosting the local economy, and fostering community well-being.