Nowadays about 54% of world population lives in urban areas and, according to the 2014 UN-ESA report, this percentage is expected to increase up to 66% by 2050. We are clearly facing a rapid and global trend, that will affect daily life in the next few decades. It is, therefore, crucial to managing this social and cultural change in a much more sustainable way, compared to what was done in the past.
Within this framework, the collection, integration, and sharing of reliable and open spatial information is a key factor, benefiting both of different space (Earth Observation (EO) satellites and Global Navigation Satellite Systems (GNSS)) and ground (low-cost devices networked in the Internet of Things (IoT), 50 billion are expected within 2020) technologies.
The contribution deals with the general presentation of the Urban Geo Big Data, a collaborative acentric and distributed free and open source platform consisting of local data nodes for data and related service Web deploy, a visualization node for data fruition, a catalog node for data discovery, a CityGML modeler, data-rich viewers based on virtual globes, an INSPIRE metadata management system enriched with quality indicators for each dataset.For data visualization and analysis, a 3D model of the urban environment was created. CityGML is an open standard that has been thoroughly tested in the past years. One of the activities in this project was to create an Extract, Transform and Load (ETL) procedure for converting information from cartographic sources into CityGML at LOD1 (Level of Detail 1). Data are viewable by means of Cesium or Web World Wind depending on the specific examined case.
Three use cases in five Italian cities (Turin, Milan, Padua, Rome, and Naples) are examined: 1) urban mobility; 2) land cover and soil consumption at different resolutions; 3) displacement time series. Concerning mobility data and analysis, particular attention has been given to data modeling and processing algorithms with the aim to deliver value-added information enabling standard and innovative services (Origin/Destination matrix, flows checking, routing options, etc.) based also on crowdsourced data. Land cover and soil consumption data derive from semi-automatic classification of Sentinel 1 and 2, integrated with Copernicus land monitoring services at different resolutions and enhanced by photo-interpretation. Several environmental and landscape indicators are assessed at municipal level, exploiting spatial datasets.
For displacement, SAR derived time series and the related Web services (WMS, WFS, and WMTS) metadata in RNDT format (the Italian extension of INSPIRE format) are automatically generated thus relieving the data provider from the need to create them manually.
Besides the case studies, the architecture of the system and its components will be presented.

Geomatics is the key resource in analyzing the deployment of publicly accessible Automated External Defibrillators (AED). Since AEDs are only effective if used within 6 minutes from the onset of an Out-of-Hospital Cardiac Arrest (OHCA), they have a limited area of effectiveness (i.e. ‘catchment area’, CA), that is traditionally computed as a circular surface with radius = 100m. The availability of open geospatial data related to roads network and edification on the territory allows to compute realistic catchment areas based on the effective distance along streets, which is a novel approach, never compared with the traditional method.
Aim of this study was to compare the two approaches, and to evaluate if the territory analysis could support decision making about the mapping technique better suiting each device. The study was performed and validated on the territory of Lombardy (Italy, total surface 23’863.65 km2), and CAs were computed for 7458 known AEDs on the territory (at 28/02/2018). The analysis was performed exploiting open source software, specifically QGIS and PostGIS with pgRouting extension.
Setting a limit of 200m for the realistic CAs, their mean surface for the considered dataset resulted close to that of the traditional circular area: 33’665 m2 against 31’416 m2. However, the spatial coverage of OHCAs (events occurring inside a CA, on the base of a georeferenced database of 45039 OHCAs occurred in Lombardy within 1/1/2015 and 31/12/2018) estimated considering circular areas (9.43%) is very different from that obtained considering realistic areas (15.35%).
The distribution of the mapping error (surface of realistic CA – surface of circular CA) was studied, and its correlation with the characteristics of the surrounding territory was inspected. The considered attributes were: I) distance from the device to the nearest road; II) total length of the roads in the surrounding area; III) number of roads network nodes in the surrounding area; IV) percentage of edified surface in the surrounding area; surrounding area for II) to IV) was a circular area of 50, 100, 150, 200 and 250 m radius. The most correlated attributes were: I) R = -0.58 (p<0.05), and II) R = 0.65 (p<0.05) in 50m-radius area.
Results suggest that circular CAs underestimate the spatial coverage of AEDs located nearby streets in a densely networked area, and in these cases realistic CAs, better suiting real-world scenario, are preferable. However, when AEDs are far from the streets, realistic mapping is not reliable, and the use of circular areas is preferable. This second situation is typical of large and isolated facilities (e.g. airports, sport facilities, warehouses), and the circular area better estimates the coverage of the facility itself.
With known AEDs location, open data and open source software are reliable enough to decide which mapping technique will result in a better estimation of the CA.

The OSGeo United Nations (UN) Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between the OSGeo Board of Directors and the UN GIS team at the FOSS4G conference in Seoul, Korea, in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project "... to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector". In 2018, the OSGeo UN Committee called for proposals for developing open geospatial educational materials as a part of its activities. There were three challenges: the first two (one of them sponsored by Boundless) are related to the UN Open GIS Initiative.

The first challenge, related to UN Open GIS - Spiral 1, aims at the development of education material that teaches users how to apply the GeoSHAPE platform. GeoSHAPE is a free and open source geospatial collaborative platform created from various open source projects. The developed material provides a guide on how to create, edit and share critical data on an integrated dynamic map in near real time, view map updates by users from anywhere in the world and use GeoSHAPE exchange in connected and disconnected environments. The course is structured with content to suit novice, intermediate and advanced users.

The second challenge supports UN Open GIS - Spiral 3, which provides geo-analytical solutions for the UN. The feasibility of the analytical functions developed as part of Spiral 3 were tested against an Ebola Epidemic use case. Requirements for developing suitable applications and methodologies based on actual UN operational cases were defined in 2017. Members of the UN Open GIS - Spiral 3 developed a geo-analytical library, called "Processing Toolbox", which is a plug-in for uDig, an open source desktop GIS. The training material developed in the frame of the OSGeo UN Challenge provides an introduction to the use of the algorithms for environmental analysis in the uDig Processing Toolbox, specifically those related to ecology and ecosystems identification. The training material for Spiral 3 is designed as a step-by-step tutorial, using algorithms in the uDig Processing Toolbox. While working through the tutorial, the user is familiarized with the tools covering all the available macro sections. After completing the tutorial, a user will be able to find the needed algorithms to solve a specific use case.

The presentation deals with the description of the UN Open GIS Challenge and the open training materials developed under this initiative. The material is available under an open license and can therefore be reused by anybody.

During the last decades, production of Land Cover maps (LC) at a continental and global scale has increased thanks to the progress in Earth Observation capacities, as well as due to high demand for these maps for many applications (e.g. climate change monitoring). However, the usefulness of these maps strongly depends on their accuracy. Therefore, for a fruitful LC maps exploitation, accuracy assessments (i.e. validation and inter-comparison) must antedate. Spatial analysis of the errors should then complement the accuracy assessment to provide insights into the local errors patterns which may not be outlined by traditional accuracy assessment techniques.
According to this, we propose here a comprehensive analysis to target accuracy of LCs by focusing on the African continent. Two datasets, GlobeLand30 (GLC30) at and CCI Land Cover - S2 Prototype Land Cover 20m Map Of Africa (CCI Prototype Africa), at 30m and 20m resolution respectively, were considered.

Inter-comparison was performed by means of traditional accuracy indexes computed from the error matrix (i.e. Overall Accuracy, Producer’s and User’s accuracy etc). Harmonization of the two maps in terms of resolution and classification nomenclature is prerequisite for inter-comparison. This was achieved by taking advantage of QGIS functionalities (e.g. resampling). Results of the accuracy assessment provide overall quality metrics for the map as well as quality indicators for each LC class.

Additionally, spatial association statistics were adopted to investigate local patterns of the errors. The analysis was performed by means of GRASS and custom developed Python scripts exploiting cutting-edge data analysis libraries such as Pandas, Dask, and PySAL. By “virtual” overlaying CCI with GLC30, we computed which classes of CCI are under each pixel of GLC30, and what is the pixel fraction of a CCI class at each GLC30 pixel. Results of the overlay were stored in a vector point file whose coordinates represent centers of pixels of GLC30. If the classes of GLC30 and CCI for a point are not the same this results in an error with magnitude represented by the pixel fraction itself. Error fractions at each GLC30 pixel were analysed by means of Local Indicators of Spatial Association (LISA) to map non-random pattern in the spatial distribution of the errors as well as to assess their intensity and spatial association typology.

By considering the results of accuracy assessment and LISA outputs, a comprehensive comparison of the GLC30 or CCI Prototype Africa is achieved. The results provide a guideline for detecting source of the error, which is potentially useful for future LC production (i.e. sampling design of training data). Lastly, it has been demonstrated that processing of massive datasets for accuracy assessment can be accomplished with Free and Open Source Software (FOSS).

With an aim of developing and delivering open source geospatial solutions to the UN, the UN Open GIS Initiative was established in March 2016, taking full advantage of mission partner expertise from UN member states, technology contributing countries, international organizations, academia, NGO’s and private sector.

In order to fulfil the diverse requirements of UN field operations, the scope of the UN Open GIS Initiative covers the geospatial software of the UN Spatial Data I nfrastructure. The activities are organized into four working groups, referred to as ‘spirals’; Spiral one for geo-portal and system infrastructure, Spiral two for capacity building, Spiral three for geo-analytic functions, and Spiral four for geospatial data collection.

This talk will cover an overall introduction of the UN Open GIS initiative including the vision, strategies, technical roadmaps, and achievements of each working group. The experiences and lessons learned from the initiative will be shared during the talk, which we hope will be helpful to the UN as well as developing countries. We will also discuss how to leverage the FOSS4G community and the UN Open GIS Initiative.