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Processed data are considered as data obtained by processing raw geospatial data for a specific purpose. This article aims to present elements relating to these objects, which are widely used in the fields of urban climatology and territorial analysis. Several concepts related to processed data are first defined, including the notion of reference spatial unit. A non-exhaustive list of processed data is presented, notably morphological and physical indicators. A selection of typologies and classifications for urban fabric at different spatial scales are also introduced. Applications and uses of processed data are detailed, especially concerning the creation of input data for climate simulation models, climate analysis and territorial diagnosis. The article ends by pointing out the limitations of processed data, and their repercussions on the quality of the information produced.
Climate change is shaking up research agendas and urban planning priorities. A number of events, including floods and heatwaves, are disrupting metropolitan areas. Urban redevelopment to meet these challenges is costly and takes time. Numerical simulation is a great tool for studying urban development scenarios and the effectiveness of development solutions. Numerical models of the urban climate exist and are gradually being improved by the scientific community. These models are parameterised, among other things, by geographical data describing mineral surfaces (buildings, asphalt floors), non-mineral surfaces (water surfaces, herbaceous soils, bare permeable soils) and tree canopies. In this article we study the suitability of existing topographic data for parameterising climate models. We begin by recalling the importance of database specifications for understanding the gap between the real world and the content of databases. We then describe strategies for constructing land cover data suitable for studying the urban climate using national reference systems and in the absence of such data. Finally, we consider the potential contribution of very large-scale data, such as BIM, to the study of urban climates. In conclusion, we propose an improvement in the specifications of national geodatabases to better meet the needs of urban planning in the context of climate change.
Today, urban climate diagnostic tools can be useful to local authorities and cities: they provide input for urban planning and development project design at different spatial scales, in a context of mitigating both global climate change and local climate heat peaks. In the following paper, we identify and list diagnostic tools, and mainly focus on geoclimatic ones. The latter have the particularity of requiring geomatics and geographic data to provide useful outputs for diagnosing overheating in cities. A classification of these tools is presented, based on four criteria. The first criteria is based on how the urban fabric is considered by each of the tools: simplified or detailed. The second criteria is the type of output produced by the software: it contains physical quantities or qualitative information (e.g. shadow or sunlit). The third criteria is relative to the choice of the problem-solving approach: physical vs statistical? The last criteria is what type of physics the software tool addresses (air temperature, wind, radiation, etc.). Finally, tools are sorted according to this classification and their relation to geomatics further described. It emerges that each tool has been developed for a particular need and from a specific point of view. This point of view will also help to explain the strengths, weaknesses and simplifications of each tool. Lastly, it highlights areas where software development, or even model development, require the attention of the GIS sci-ences.
The urban heat island and urban air pollution, major health risks in cities, can be measured by networks of fixed stations or mobile measurements in urban environments. Protocols have been set up to ensure that climate and air pollution issues are representative at different spatial and temporal scales. The aim of this article is to present the existing measurement networks, the protocols implemented in French research, and the spatial representations of the data derived from these measurements. This overview provides an insight into the scientific and technical issues involved in setting up climate and air pollution measurements.
