FOSS4G-Asia 2023 Seoul

Local Climate Zone (LCZ) maps represent a valuable informative tool for several applications including outdoor thermal comfort assessment, building energy consumption, and microclimate modelling. Typically, these maps are produced by taking advantage of multispectral satellite imagery and multiple geospatial layers (e.g. topographic databases and land use/land cover maps), according to established workflows. Nonetheless, cutting-edge data and technologies leave large room for improvement. Furthermore, different features in terms of map accessibility, format and resolution may be required for the different applications depending on the end-users' needs. This is why user requirements should be gathered and addressed during the mapping workflow’s design and implementation.
In view of the above considerations, the LCZ-ODC project (agreement n. 2022-30-HH.0), funded by the Italian Space Agency (ASI), aims to produce multi-temporal LCZ maps for the Metropolitan City of Milan, in northern Italy, using innovative open data sources and Free and Open Source Software (FOSS) tools. The project is being carried out from a user-oriented perspective to achieve high levels of usability while fulfilling different end-user informational needs. Stakeholders, including public administration, professional associations, foundations, and researchers, are actively involved in the project development and validation phases through dedicated workshops and educational events aiming to consolidate user needs, guide product implementation, and assess the usability of the project outcomes.
The LCZ-ODC project uses a hybrid remote sensing/Geographic Information System (GIS) based approach for LCZ mapping, utilizing both open geospatial layers and high-resolution satellite imagery. The latter include multispectral Sentinel-2 images distributed by the European Space Agency (ESA) and hyperspectral data acquired by the PRISMA (Hyperspectral Precursor of the Application Mission) satellite, provided by ASI. Additionally, in-situ weather measurements sensed by authoritative monitoring networks are used to assess the statistical correlation between the LCZ classes and air temperature.
The Open Data Cube (ODC) technology serves as the project’s backend system, facilitating multi-source data integration, pre-processing, and the distribution of ready-to-use data. In particular, geospatial layers contained in the ODC include multi-temporal and multi-resolution LCZ maps, preprocessed satellite images, and static layers describing the LCZ morphological properties, like sky-view factor, building height, and impervious surface fraction. A preconfigured ODC instance will be published in a Docker container, equipped with libraries and tools needed for interacting with and downloading the available datasets. Moreover, Jupyter Notebooks will be made available as a project outcome, enabling non-expert users to easily visualize, query, and download the data from the ODC. These Notebooks also offer documentation and ready-to-use code for expert users, streamlining the data analysis and exploration process.
The ongoing work focuses on developing interactive and user-friendly interfaces to allow users with different levels of expertise to directly access and interact with the data contained in the ODC. Additionally, training sessions are planned during the project's validation phase to demonstrate the products' operational use while tailoring outputs to the specific needs of users.