Citizen sensing is a new sensor-based data collection paradigm and is focused on the extraction of data generated by people. Initiatives based on this concept are becoming crucial for designers of intelligent urban infrastructures, since they enable the collection of several types of relevant data that cannot be properly captured by traditional physical sensors. A large number of articles and projects associated with the topic appeared over the last few years, and with them the need for properly classifying and organizing these works. In this paper, we propose a taxonomy of citizen sensing initiatives and illustrate each of its dimensions through a survey of recent articles in the area. The proposed scheme also supports the identification and stimulates the development of projects addressing data collection methodologies that have not been properly explored so far. In addition, we present a platform capable of aggregating, analyzing, and extracting knowledge from data generated by physical and human sensing techniques. Finally, we report a real-world experiment in which we used our platform to map accessibility conditions of streets and sidewalks located in a four square kilometer area in Saõ Paulo, Brazil. Our results show that a full coverage was obtained with the support of eight volunteers after only three hours, hence illustrating the effectiveness of the technology.