Our understanding of the relationship between city morphology, materiality, and urban microclimate has been limited due to the lack of availability of urban microclimate data. In order to better understand the influence that building geometries, trees, or topographical variations play in urban microclimates, it is necessary to utilize measuring techniques that gather higher spatial resolution urban environmental data rather than data provided by weather stations or static sensor networks. With this purpose, this research proposes to utilize accessible low-cost technologies for environmental sensing coupled with dynamic devices. A custom sensor kit to record temperature, humidity, and CO2 concentrations, has been mounted to a bike for pedestrian level microclimate sensing. The same sensing kit has been attached to an Unmanned Aerial Vehicle (UAV) for the vertical gradient profile measurements. Image, video processing techniques, and GIS data have been utilized to visualize the recorded measurements and to parameterize the urban properties (green areas, impervious surfaces, and building masses) around the acquisition trajectories. The correlation of the acquired measurements and the urban parameters, show that maximum CO2 concentrations mainly peak in road intersections. Building masses and greenery also appear to affect the distribution of pollutant concentrations both in the pedestrian level and in the vertical profiles. While dynamic sensing attains sufficient spatial resolution, it does not provide high temporal resolution. With the aim to improve data accuracy through data redundancy, the proposed DIY sensing kit utilizes readily available sensors and operates on open-source platforms to encourage the engagement of larger audiences.