Land regularization in favelas is a challenging and complex issue in the Brazilian context, involving legal, social, economic and urban aspects. In this scenario, the use of unmanned aerial vehicles (UAVs), popularly known as drones, emerges as a promising tool with the potential to significantly assist in land regularization activities in informal settlements. This article aims to explore and highlight the potential of UAVs in the regularization of informal settlements, evidencing their ability to provide accurate, up-to-date and detailed geospatial information. UAVs can perform aerial photogrammetric surveys, capturing high-resolution images and generating georeferenced orthomosaics and 3d models of the areas of interest. However, the effective implementation of UAVs in land regularization faces several obstacles and challenges. One of the main challenges is the need for adequate standardization for the use of these technologies in slum areas, considering the particularities and specific demands of these settlements. In addition, issues related to privacy, security, access to the data collected and training of the professionals involved also require attention. Another relevant aspect is the gap between the scientific and technological research developed so far and the discussions on the right to housing. The research has been directed, for the most part, to meet the demands of financial capital, with emphasis on the agribusiness sector, leaving aside the needs of communities in situations of housing vulnerability. Therefore, it is essential to promote a closer integration between scientific research, legislation and public policies aimed at land regularization in favelas, in order to ensure that the use of UAVs is guided by ethical, inclusive and socially just principles. Only in this way will it be possible to fully harness the potential of these technologies to promote decent housing and access to fundamental rights in informal urban areas. DOI:https://doi.org/10.56238/Connexpemultidisdevolpfut-028

Cartographic resources play a crucial role in facilitating communication across various sectors, including research projects focused on low-income communities. Despite this, some researchers still adhere to colonialist and exploitative approaches. This study aims to promote equitable university–community interaction though cartographic resources, aid academic and vulnerable community users in choosing a better platform for their work, and provide insights to developers for improving the platforms to better serve the user profiles of community members. To achieve this, we examined the use of cartographic resources in five projects within low-income communities (commonly referred to as favelas or so-called “slums”) in three Brazilian cities, all guided by equitable principles. The study unfolds in four stages: (i) data collection from documents and interviews; (ii) systematization into seven analytical categories—cartographic resources, data, personnel, processes, equipment, general objectives, and specific objectives; (iii) analysis of eight cartographic resources; and (iv) a critical examination of the outcomes. The synthesis of the collected information identified 65 characteristics/demands, with 17 common to all projects, including vector feature creation, thematic map design, printed map usage, and satellite imagery. We also identified 53 geographic information system (GIS) functionalities required for the projects, predominantly related to vector data generation and editing. The outcomes demonstrate the benefits of project methodologies, contributing to a decolonial university–community praxis. Additionally, they underscore the potential of digital cartographic resources, functioning not solely as data collection tools but also as powerful instruments that empower slum residents to advocate for improvements and foster local development.

Addressing the challenge of mapping deprived urban areas (DUAs) globally requires both technical innovation and user engagement. The IDEAtlas project developed a novel approach to monitor DUAs by combining advanced Earth Observation (EO) technologies with a user-centered design. Central to this is our IDEAtlas User Portal, a data platform that provides scalable, accessible, and participatory mapping solutions in support of Sustainable Development Goal (SDG) 11.1.1. The portal provides outputs from a custom Multi-Branch Convolutional Neural Network (MB-CNN) model trained on freely available Sentinel-1 and Sentinel-2 data, enriched with ancillary open datasets such as building footprints. Presently, the portal offers binary settlement maps, with future plans to include deprivation severity indices, and multi-temporal urban growth maps for the period 2019 to 2023. A unique feature of the IDEAtlas platform is its two-tier access model: an open section offering 100 by 100 m gridded outputs for public use, and a protected section for sensitive, city-level data. In the protected section, users can validate outputs. The user validation is an essential element of our Living Labs and is done in the form of continuous stakeholder collaboration. Through Living Labs and iterative user feedback across eight global cities, the portal has demonstrated how involving local governments, NGOs, and community organizations can enhance data quality, relevance, foster ownership, and empower decision-making. Early user engagements, such as the update of Argentina's RENABAP informal settlement registry, highlight the portal's operational value. By coupling technological scalability with participatory validation. Thus, the IDEAtlas User Portal represents a significant step toward inclusive, evidence-based urban planning and policymaking.

The use of Unmanned Aerial Vehicle (UAV) can contribute significantly to land regularization activities of slums. This article seeks to demonstrate the potentia...

Climate change intensifies flooding and urban waterlogging due to increased frequency and intensity of rainfall, affecting urban areas, especially in lowlands. These areas, characterized by low altitude and inadequate infrastructure, suffer material damage and impact on quality of life. Urban planning is crucial, with measures such as drainage systems and green infrastructure to mitigate risks. The research developed a cloud-based application using Google Earth Engine to identify flood-prone areas in Brazilian cities. The model, validated in Sorocaba, São Paulo, achieved 81% global accuracy, aiding decision-making. The tool is freely accessible, supporting city governments in flood risk management.