Free and open source software for geospatial applications (FOSS4G) to support Future Earth

The development, integration, and distribution of the information and spatial data infrastructure (i.e. Digital Earth; DE) necessary to support the vision and goals of Future Earth (FE) will occur in a distributed fashion, in very diverse technological, institutional, socio-cultural, and economic contexts around the world. This complex context and ambitious goals require bringing to bear not only the best minds, but also the best science and technologies available. Free and Open Source Software for Geospatial Applications (FOSS4G) offers mature, capable and reliable software to contribute to the creation of this infrastructure. In this paper we point to a selected set of some of the most mature and reliable FOSS4G solutions that can be used to develop the functionality required as part of DE and FE. We provide examples of large-scale, sophisticated, mission-critical applications of each software to illustrate their power and capabilities in systems where they perform roles or functionality similar to the ones they could perform as part of DE and FE. We provide information and resources to assist the readers in carrying out their own assessments to select the best FOSS4G solutions for their particular contexts and system development needs

A SEMI-AUTOMATIC PROCEDURE FOR A DEMOGRAPHIC ANALYSIS OF THE FOSS4G DEVELOPERS' COMMUNITY

Abstract. The open and direct collaboration at the creation, improvement, and documentation of source code and software applications &amp;ndash; enabled by the web &amp;ndash; is recognized as a peculiarity of the Free and Open Source Software for Geospatial (FOSS4G) projects representing, at the same time, one of their main strengths. With this in mind, it turns out to be interesting to perform an extensive monitoring of both the evolution and the geographical arrangement of the developers' communities in order to investigate their actual extension, evolution and degree of activity. In this work, a semi-automatic procedure to perform this particular analysis is described. The procedure is mainly based on the use of the GitHub Search Application Programming Interface by means of JavaScript custom modules to perform a census of the users registered with a collaborator role to the repositories of the most popular FOSS4G projects, hosted on the GitHub platform. The collected data is processed and analysed using Python and QGIS. The results &amp;ndash; presented through tables, charts, and thematic maps &amp;ndash; allow describing both dimensions as well as the geographical heterogeneity of the contributing community of each individual project, while enabling to identify the most active countries &amp;ndash; in terms of the number of contributors &amp;ndash; in the development of the most popular FOSS4G. The limits of the analysis, including technical constraints and considerations on the significance of the developers' census, are finally highlighted and discussed.</p

MOVING TOWARD OPEN GEOSPATIAL SYSTEMS: THE UN OPEN GIS INITIATIVE

Abstract. The UN Open GIS Initiative is an ongoing Partnership Initiative leaded by the United Nations Geospatial Operations. The Initiative, established in March 2016, is supported by several UN Member States, UN Field Missions, UN Agencies and technology contributing partners (international organizations, academia, NGOs, and the private sector) and takes full advantage of their expertise.The target is the creation of an extended spatial data infrastructure that meets the requirements of the UN Secretariat (including UN field missions and regional commissions), and then expands to UN agencies, UN operating partners and developing countries. The paper presents the activities done in the past year and the status of the Initiative

UN open gis capacity building

The UN Open GIS Initiative is to identify and develop, under UN guidance, an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners (partner nations, technology contributing countries, international organizations, academia, NGO's, private sector). The project, started in 2016, is composed by 4 working groups. One of the working group is specifically related to Capacity Building, given its importance for the success of the project. UN Open GIS will be based on some existing open source geospatial software (packages and libraries) with many extensions specifically developed. The users of the platform will be the UN staff supporting with mapping and GIS the peacekeeping missions. Therefore, they are generally expert of this specific domain, even if they are currently using proprietary software. UN Open GIS Capacity Building is specifically thought for covering this gap, providing them the suitable background about open source geospatial software in general and the education tailored to the solution that has been being developed within the project itself

FogLearn: Leveraging Fog-based Machine Learning for Smart System Big Data Analytics

Big data analytics with the cloud computing are one of the emerging area for processing and analytics. Fog computing is the paradigm where fog devices help to reduce latency and increase throughput for assisting at the edge of the client. This paper discussed the emergence of fog computing for mining analytics in big data from geospatial and medical health applications. This paper proposed and developed fog computing based framework i.e. FogLearn for application of K-means clustering in Ganga River Basin Management and realworld feature data for detecting diabetes patients suffering from diabetes mellitus. Proposed architecture employed machine learning on deep learning framework for analysis of pathological feature data that obtained from smart watches worn by the patients with diabetes and geographical parameters of River Ganga basin geospatial database. The results showed that fog computing hold an immense promise for analysis of medical and geospatial big data

Urban geo big data

The paper deals with the general presentation of the Urban GEO BIG DATA, a collaborative acentric and distributed Free and Open Source (FOS) platform consisting of several components: 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.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. Besides the case studies, the architecture of the system and its components will be presented

Optimising urban routes as a factor to favour sustainable school transport

We thank Gema Zarrías Martos, Technical Topography Engineer, for her participation in developing this project. The authors also wish to thank the European Commission for supporting the project MySmart School, with Ref. 2015-1-FR01-KA201-015274 in the KA201 programme of strategic actions in Primary Education through those people who participated in this project: the public Vicente Blasco Ibáñez school, the Alginet Town Council and the Universidad Politécnica de Valencia (UPV). We particularly thank: (i) the management team, the collaborators from the school s Mother and Fathers Association, the tutors and students of grade 5 and 6 students from the public Vicente Blasco Ibáñez School in Alginet, especially for their enthusiasm, direct implication and active participation in this project; (ii) the Alginet Town Council for supporting the project and for implementing the proposed improvements; (iii) the UPV research team for its collaboration, help and for providing ideas.Mora Navarro, JG.; Femenia-Ribera, C.; Martínez Llario, JC.; Antequera Terroso, EB. (2018). Optimising urban routes as a factor to favour sustainable school transport. Journal of Transport Geography. 72:211-217. https://doi.org/10.1016/j.jtrangeo.2018.09.001S2112177

TOWARDS UNDERSTANDING THE IMPACT OF MAPATHONS – REFLECTING ON YOUTHMAPPERS EXPERIENCES

Abstract. YouthMappers is a global network of student chapters actively engaged in collaborative mapping efforts, such as OpenStreetMap mapathons. Many questions have been raised about the impact of mapathons on open map data and on the participating mappers. For example, how can the social gathering and event format encourage productivity and quality, while also contributing to community building? Because YouthMappers chapters regularly host mapathons, there are frequent opportunities to investigate the impact of mapathons. In this paper, three universities involved in the YouthMappers network, located in Europe, North America and Africa, describe how mapathons are conducted at their respective universities. Incorporating mapathons into the curriculum encourages students to contribute much-needed open geospatial data for humanitarian projects. At the same time, students get practical experience in data capturing with open source tools and awareness is raised of humanitarian challenges in other parts of the world, thus nurturing socially engaged citizens for the future. The experiences at the three universities are diverse and richly contextual to the specific character of the campus and its students. These differences underscore the challenge of a common means to formally assess the impact of such events in general. Based on this exploratory research, three themes for assessing the impact of mapathons are proposed: the volume and quality of open geographic data produced during mapathons; the social and personal growth of the students attending the mapathons; and the changes in university programs and curricula introduced as a result of the mapathons.</p

Extending accuracy assessment procedures of global coverage land cover maps through spatial association analysis

High-resolution land cover maps are in high demand for many environmental applications. Yet, the information they provide is uncertain unless the accuracy of these maps is known. Therefore, accuracy assessment should be an integral part of land cover map production as a way of ensuring reliable products. The traditional accuracy metrics like Overall Accuracy and Producer's and User's accuracies – based on the confusion matrix – are useful to understand global accuracy of the map, but they do not provide insight into the possible nature or source of the errors. The idea behind this work is to complement traditional accuracy metrics with the analysis of error spatial patterns. The aim is to discover errors underlying features which can be later employed to improve the traditional accuracy assessment. The designed procedure is applied to the accuracy assessment of the GlobeLand30 global land cover map for the Lombardy Region (Northern Italy) by means of comparison with the DUSAF regional land cover map. Traditional accuracy assessment quantified the classification accuracies of the map. Indeed, critical errors were pointed out and further analyses on their spatial patterns were performed by means of the Moran's I indicator. Additionally, visual exploration of the spatial patterns was performed. This allowed describing possible sources of errors. Both software and analysis strategies were described in detail to facilitate future improvement and replication of the procedure. The results of the exploratory experiments are critically discussed in relation to the benefits that they potentially introduce into the traditional accuracy assessment procedure