Tar Print is an iPhone application that simplifies the process of calculating pervious and impervious surface percentages. Developed by Nagesh Vaddi, this educational and reference tool integrates Apple Maps with machine learning and novel computer vision algorithms to analyze surface types without the need for training classifiers.

With Tar Print, users can easily quantify impervious surface percentages by simply specifying a location and settings, and clicking the camera button. This streamlined approach allows students, researchers, and environmental enthusiasts to access a surface type analyzer effortlessly.

The availability of Tar Print promotes citizen science and environmental stewardship efforts by increasing the accessibility of surface type analysis. This, in turn, helps mitigate the harmful impacts of urban development on local water quality and stream ecology.

It is important to note that Tar Print does not collect or store any location data, ensuring user privacy. The application is designed for in-the-field research, environmental stewardship projects, urban development, stormwater management, and any other projects that benefit from surface percentage analysis. Additionally, the accuracy of Tar Print is currently being assessed against well-known remote sensing tools such as ArcGIS, with the intention of making the results public.