MAPi is a web platform for online mapping conceived as a public participation tool for schools and organized civil society. Its main functionalities of visualization, analysis, and collection of spatial data were developed to encourage participatory urban planning, especially focusing students and teachers from basic education.
The Center for Metropolitan Studies (CEM), which is the research center that hosts MAPi´s project, has been responsible for producing and openly sharing databases (cartographic and non-cartographic) since its inception 20 years ago. More recently, CEM expanded its activities in this technology transfer area to develop interactive web systems, like ReSolution and Schools portals, built from the interaction with the center's academic research work and agendas. So the idea is to bridge the gap between highly complex research and technology transfer to academic and non-academic society, respecting the principle of open data and software. All data produced and all softwares developed, including its source codes, are available at no cost.
In this context, however, there is a great challenge to make the knowledge produced by the CEM, especially the cartographic databases, continuously accessible to a portion of society that does not master geospatial analysis techniques. Although the ecosystem that provides tools for this type of analysis is increasingly more accessible, including through the web, they are still far from being widely adopted in non-specialized contexts, such as classrooms.
To tackle this challenge, MAPi arises to perform as a tool that can expand the use of spatial data in primary and secondary schools. So it has the twofold challenge of gathering simplicity in its navigation to ensure a friendly experience with complexity of technique specificities of exploring and visualizing spatial data, especially for the non-specialized public.
Thus, MAPi has, since its first version, native integration with CEM's spatial data repository, GeoCEM, which is developed based on the GeoNode software, with its metadata stored on Geoserver..
Through Geonode, MAPi queries the layers that are published on GeoServer using the Web Feature Service (WFS). WFS specifies an interface for accessing and manipulating geographic elements using the HTTP protocol. The advantage and reason for choosing this standard is its ability to extract only the desired data at the element and attribute level. In this way, we can build a dynamic platform that creates thematic maps in real-time from the parameters chosen by the user, characterizing it as an interactive mapping platform.
MAPi presents as its main tool for spatial data analysis the interface for creating choropleth thematic maps. This type of map is used in MAPi to represent data collected from geographic units such as census tracts and districts. For this functionality, the platform allows the choice between some color palettes (sequential, divergent, or qualitative), which are associated with the polygons of the geographic units according to the class division (quantile or natural breaks). The selection of multiple spatial data layers that are added as a Vector Tile layer in OpenLayers, makes it possible for the user to analyze and compare different themes or periods simultaneously. To serve non-specialized audiences, we maintain only the most essential tools of thematic mapping so that users can in a few steps build visualizations capable of extracting analyses, maintaining some level of parameterization to adapt to the type of phenomenon. Thus, through the OpenLayers and WFS resources, we make parameterizable for each layer its visibility, the attribute that will be associated with the fill color, the data classification method, the color palette, and the attributes that will be displayed in the dynamic map legend (based on attribute values).
Finally, the third axis of functionality, collaborative mapping, aims to provide, in a simplified way, tools for the production of spatial data. We understand here that this functionality can be a tool that enables the expansion and updating of data coverage that official agencies are unable to perform. In this way, we intend to create an area within the platform that allows the creation of forms with location fields to create spatial data to be viewed and analyzed together with the other data on the platform. Currently, only the integration with Mapillary partially accomplishes this goal through the consumption of the visualization of the cover layer, and visualization of the photo sequences available in Mapillary by its users.
One potential application in education from collaborative mapping functionalities is the support in the discussion about neighborhood plans, that are instruments foreseen under master plan development, like the example from the megacity of São Paulo. The tool is under test with basic education teachers that want to promote mapping activities with MAPi in urban geography classes, and also within mathematics classes where they can address methodological issues of the results of this mapping to support basic concepts related to statistics in the classroom. Our next challenges are the optimization of performance for large volumes of data and the implementation of more complex collaborative mapping functionalities in a Agile methodology, with constant interaction with teachers that envision MAPi´s potential to foster engagement of students in urban planning.