We put great importance to data protection and therefore use the data you provide to us with upmost care.
You can handle the data you provide to us in your personal dashboard.
You will find our complete regulations on data protection and clarification of your rights in our privacy notice. By using the website and its offers and navigating further, you accept the regulations of our privacy notice and terms and conditions.
Accessible Parking: Using Satellite Data to Map Accessible Assets
Dún Laoghaire-Rathdown County Council and ENABLE, through the Smart Sandyford Programme, have partnered with Access Earth to prototype a ground-breaking, satellite classifier tool to map accessible assets within a built environment.
Today in Ireland, 643,131 people, or 13% of the population, live with a disability. People with disabilities have traditionally been an under serviced community by both the public and private sectors. This is a problem from a moral, ethical and inclusivity perspective, however, this also presents a major business opportunity as this demographic has an estimated spending power of €7 trillion globally. 65% of people with disabilities do not spend their money on travel or leisure due to a lack of, or a perceived lack of, accessibility infrastructure to cater to their needs. Accessible parking is a crucial asset that needs to be available in sufficient quantities to not just cater to individuals who already frequent business and services within an area but to also attract this massive untapped market into that area.
Between February and June 2020, the Access Earth team carried out a satellite analysis of accessible parking infrastructure within Sandyford. This new approach to the analysis of accessible parking infrastructure was tested using Sandyford as an exemplar case study, in partnership with the Smart Sandyford research programme. The goal of this report is to provide an informed insight into the accessible parking landscape for Sandyford. This involves analysing the total number of above ground accessible parking locations for the district where a high confidence level is achieved for accuracy of the image classifier.
Want to learn more about the lessons learned, financial details and results?