Working Groups of ISPRS Commission IV

WG IV/1 - Spatial Data Representation and Interoperability

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Filip Biljecki

College of Design and Engineering
National University of Singapore

Francesca Noardo

Open Geospatial Consortium

Pawel Boguslawski

Wroclaw University of Environmental and Life Sciences
Institute of Geodesy and Geoinformatics
Grunwaldzka 53
50-357 Wroclaw

Elisabetta Colucci

Department of Environment, Land and Infrastructure Engineering
Politecnico di Torino

WG IV/1  Terms of Reference

  • Foster the development and sharing of solutions supporting data interoperability (data models, formats, metadata, etc.).
  • Reviewing conceptual models for spatial data representation and associated data such as time series.
  • Promoting the use of international standards to foster scalability and reusability of solutions.
  • Make sense of disconnected developments and aim for their interoperability.
  • Promote good practices aimed at the use of standards for data management, storage, processing and exchange.
  • Advance knowledge in semantic technologies, ontologies and linked data to solve interoperability problems and make spatial data discoverable.
  • Investigate methodologies for big data spatial representation, mapping, connection and federation of disconnected data models to support multidisciplinary use and data integration. 
  • Disseminate solutions for effective and meaningful spatial data integration.
  • Promote collaboration with international and regional standardisation organisations (OGC, buildingSMART, W3C…).
  • Disseminate practices and research related to the development of use of spatial data spaces.



WG IV/2 - Artificial Intelligence and Uncertainty Modeling in Spatial Analysis

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Mahmoud R. Delavar

Centre of Excellence in Geomatic Eng. in Disaster Management, and Land Administration in Smart City Lab., School of Surveying and Geospatial Eng., College of Engineering
University of Tehran
P.O. Box: 11155-4563, Tehran

Gerhard Navratil

Dept. of Geodesy and Geoinformation,
TU Wien
Gußhausstr. 27-29 / E120 (CD0342)
Wien, 1040
+43(1)58801 12712

Umit Işıkdag

Department of Informatics,
Mimar Sinan Fine Arts University,
Bomonti Kampüsü Cumhuriyet Mah. Silahşör Cad.
No:89 Bomonti Şişli,
+90 212 246 00 11

Inger Fabris-Rotelli

Department of Statistics
University of Pretoria
Lynnwood Road
South Africa
+27 (012) 420-5420/ 082 470 8480

WG IV/2  Terms of Reference

  • Data mining, machine learning and artificial intelligence methods applicable to spatial and spatiotemporal data, spatial analysis and spatial statistics and their assessment
  • Spatial statistics for uncertainty assessment
  • Methods to intelligently assess quality of spatial decision-making processes
  • Challenges in smart big spatial data collection, fusion, mining, and assessment in GIScience
  • Advance knowledge in implementing, customizing and optimizing the artificial intelligence algorithms for spatial analysis, spatial statistics and uncertainty modeling
  • Intelligent assessment of the reliability, quality, and liability of spatial data and spatial analyses
  • Leveraging artificial intelligence in spatial analysis and spatial statistics operations and their uncertainty modeling
  • Development of robust software tools for uncertainty modelling and visualization such as Data Uncertainty Engine (DUE)
  • Uncertainty modelling in indoor, outdoor and seamless environment, real-time processing; control and obstacle avoidance and dynamic scene understanding
  • Validation of new sensors and their calibration, fusion as well as information extraction and their combinations
  • Data quality and uncertainty assessment in multi-dimensional GIS and multi-concept remote sensing of big datasets related to natural and/or built environment
  • Developing and implementing appropriate, comprehensive, intelligent and generally accepted quality control techniques and data quality standards
  • Uncertainty assessment in dynamic geospatial services, deep web, linked data, online multidimensional visualization considering usability, designs for mobile web, seamless indoor/outdoor location-based services, community-driven and participatory applications, and global information services



WG IV/3 - Geo-computation and Geo-simulation

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Bi Yu Chen

Geocompuation Center for Social Science
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing
Wuhan University

René Westerholt

Spatial Modelling Lab
Department of Spatial Planning
TU Dortmund

Azarakhsh Rafiee

GIS Technology team
Department of Architectural Engineering Technology
Delft University of Technology
The Netherlands

Tao Jia

School of Remote Sensing and Information Engineering
Wuhan University

WG IV/3  Terms of Reference

The following terms of reference describe the scope of the activities of the WG:

  • Promote high-performance Geocompuation/Geosimulation techniques for large-scale network optimizations, such as facility location-allocation and transport infrastructure planning;
  • Explore reliable Geocompuation/Geosimulation techniques to produce robust and consensus solutions to complicated geographic problems with various sources of uncertainties;
  • Explore knowledge-based Geocompuation/Geosimulation techniques by integrating data-driven knowledge towards smart geographic problem solving;
  • Develop new complex network analysis methods to detect the evolving patterns of geographical networks, to analyze its vulnerability, reliability and resilience, and to understand scaling laws of urban man-made or natural phenomenon;
  • Explore and promote the use of agent-based simulation and cellular automata in modelling geospatial processes and study their validations;
  • Work towards an effective integration of Geocomputation/Geosimulation techniques in spatial decision support systems;
  • Work on OGC standards for Geocomputation/Geosimulation (e.g. Web Processing Service).



WG IV/4 - Data Management for Spatial Scenarios

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Emmanuel Stefanakis

Department of Geomatics Engineering
University of Calgary
2500 University Drive NW
Calgary, Alberta, T2N 1N4
+1 403 220 4113

Martin Breunig

Geodetic Institute
Chair of Geoinformatics
Karlsruhe Institute of Technology
Englerstr. 7
76131 Karlsruhe
+49 721 608 Ext. 42302

Mulhim Al Doori

Roads and Transport Authority
118899, Dubai
+97 1507549151

Paul Vincent Kuper

Geodetic Institute
Chair of Geoinformatics
Karlsruhe Institute of Technology
Englerstr. 7
76131 Karlsruhe
+49 721 608 Ext. 46787

WG IV/4  Terms of Reference

The working group investigates new ways and best practices to manage multi-dimensional geometric, topological, and semantic dynamic data from a broad range of sources such as sensors, digital twins, BIM, GIS, mobile devices, and others. By doing so it advances the enhancement of standards for data, metadata, and services as well as data integration from different geospatial scenarios.

The WG plan includes the following:

  • Advance interfaces to other commissions and working groups such as the WG IV/1 on spatial data interoperability; WG IV/2 on spatial analysis and artificial intelligence; WG IV/3 on geosimulation; WG IV/9 on spatially enabled digital twins; WG II/3 on Point Cloud Processing; and ICWG II/Ib, and ICWG IV/II on BIM.
  • Review technical progress and OGC/ISO standards for Geospatial Data Management.
  • Explore and develop new ways to model, store, integrate, and manage voluminous and heterogeneous geospatial data for knowledge discovery. This includes the development of semantically rich spatial data structures, spatial indexing schemes and generic analytical tools for model validation.
  • Advance knowledge in intelligent data preparation and analysis, geospatial data access methods, geometric and topological relations, data aggregation, integration, and scalability. This includes the investigation of federated spatial data models and linked data considering different representations, data uncertainty, and data quality.
  • Explore and develop strategies for fusion of multi-dimensional spatial models, Volunteered Geographic Information (VGI), socio-economic models, and IoT data.



WG IV/5 - Extended Reality and Visual Analytics

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Arzu Çöltekin

FHNW University of Applied Sciences and Arts Northwestern Switzerland
School of Engineering
Bahnhofstrasse 6
CH-5210 Windisch

Victoria Rautenbach

Department of Geography, Geoinformatics and Meteorology
University of Pretoria
Geography 1-3.7
University of Pretoria
Private bag X20
Hatfield 0028
South Africa

Azile Mdleleni

Department of Geography, Geoinformatics and Meteorology
University of Pretoria
Geography 1-3.7
University of Pretoria
Private bag X20
Hatfield 0028
South Africa

Hongping Zhang

National Geomatics Center of China
No.28 Lianhuachi West Road
Haidian District
Beijing 100830

WG IV/5  Terms of Reference

  • Engaging in science, research, education and training, and capacity building, in line with the overall strategy of the ISPRS
  • Transferring knowledge and expertise through conferences, workshops, publications and other appropriate online and offline channels
  • Collaborating with other ISPRS commissions and working groups, and sister societies (e.g., the ICA, GeoforAll, IEEE’s Vis, ISMAR and VR, etc.)
  • Enhanced communication of geographic information and knowledge focused on visual analytics for (small and) big data exploration, and visualization of multi-dimensional data.
  • Investigating the effectiveness and usefulness of various geovisualizations, visual analytics software environments and extended reality applications, e.g., regarding visual complexity and decision-making processes
  • Development and evaluation of new extended reality tools for exploring phenomena considering dimensions of space, place and time, and promoting their use
  • Exploring new and novel visualization techniques and tools for visualizing:
    • Heterogeneous geographical data coming from high-resolution sensors (e.g. images, 3D models, LiDAR, raw data, etc.)
    • Building information modelling (BIM) within a traditional geographic information system (GIS)
    • Big data sets produced through crowd-sourcing and social media and the further opening of government data repositories
    • Supporting geographical visualisation including the web and mobile devices



WG IV/6 - Human Behaviour and Spatial Interactions

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Wei Huang

Tongji University

Yingwei Yan

National University of Singapore

Yair Grinberger

Hebrew University of Jerusalem

Hao Li

Technical University of Munich

WG IV/6  Terms of Reference

  • Develop novel models for understanding how human behaviour results in various human activity patterns
  • Address challenges and issues regarding human behaviour uncertainties
  • Uncover underlying mechanisms of the interactions between human behaviour and living environments
  • Develop new spatial analysis technologies for understanding individual and collective behaviour uncertainties within complex systems
  • Advance the understanding and assurance of spatial data quality of human-generated spatial content in relation to individual and collective human behaviour
  • Review geo-visualization methods of spatio-temporal big data on human behaviour
  • Encourage the development of strategies for handling geo-privacy and ethical issues involved in the analysis of and use of individuals’ spatial data (e.g., geotagged social media data)
  • Integrate theoretical thinking related to spatial behaviour (spatial thinking, critical thinking, and ethical thinking) for human activity modeling
  • Advance the research in understanding and modelling human behaviours towards sustainable decision making and planning
  • Promote collaborations with other WGs



WG IV/7 - Intelligent Systems in Sensor Web and IoT

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Songnian Li

Department of Civil Engineering
Toronto Metropolitan University (formerly Ryerson University)
350 Victoria St.
Toronto, ON
M5B 2K3

Monica Wachowicz

Geospatial Science
RMIT University
124 La Trobe Street
Melbourne VIC 3000

Shishuo Xu

Beijing University of Civil Engineering and Architecture
15 Yongyuan Rd
Daxing district
China 102616

Daniele Oxoli

Civil and Environmental Engineering
Politecnico di Milano
P.zza Leonardo da Vinci 32
20133, Milano

WG IV/7  Terms of Reference

  • WG IV/7 aims at advancing and/or promoting the development and international collaboration in the following areas:
    • Fusion and integration of data from sensors, IoT devices, and crowd sources for supporting digital twins and smart cities.
    • New methods and techniques (e.g., machine learning and deep learning based, decentralized processing, and edge computing) for analyzing, predicting, and simulating data from sensors, IoT devices, and crowd sources.
    • Research on ethical use of and trust in data from ubiquitous sensors, IoT devices, crowdsourcing, and intelligent systems.
    • Potential of sensor web, Internet of Things, crowdsourcing, participatory and intelligent systems for user-centered planning and decision support.
    • Efficient use of the data from sensors, IoT devices, crowdsourcing, and intelligent/participatory systems for supporting the implementation of UNs’ SDGs.
  • Promote career development of youth and next-generation scientists and researchers.



WG IV/8 - Digital Twins for Mobility and Navigation

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Zhizhong Kang

Department of Remote Sensing and Geo-Information Engineering
School of Land Science and Technology
China University of Geosciences
Xueyuan Road 29, Haidian District
100083 Beijing
+86 10 8232 2291
+86 10 8232 1807

Mir Abolfazl Mostafavi

Département des sciences géomatiques
Pavillon Louis-Jacques-Casault
1055, avenue du Séminaire, local 1342
Université Laval
Québec (Québec) G1V 0A6
+1 418-656-7411

Ana-Maria Olteanu-Raimond

the LASTIG laboratory
University Gustave Eiffel
73 avenue de Paris
94165 Saint-Mandé CEDEX
+33 1 43 98 62 37

Zhiyong Wang

Department of Transportation
School of Civil Engineering and Transportation
South China University of Technology
Jiaotong Building, Wushan RD NO. 381
510641 Guangzhou
+86 13503083186

WG IV/8  Terms of Reference

The terms of reference describe the scope and limitations of the activities of the working group.

  • Propose conceptual framework for a digital twin in support of efficient mobility and navigation in the context of smart cities
  • Advance in the development of algorithms and standards for semantic and topological modelling of indoor/outdoor realistic environments (addressing Resolution IV.1)
  • Advance knowledge in tracking and data mining for way-finding, traffic monitoring, behavioural control, multi-modal mobility in indoor/outdoor environments, using Artificial Intelligence and machine learning (addressing Resolution IV.2).
  • Promote the application of digital twins for navigation, location based services and mobility in indoor/outdoor (including underground) environments (addressing Resolution IV.3)
  • Benchmark the quality and practicality of semantic and topological modelling methods, standards and mobility analysis algorithms.
  • Review and benchmark the quality and practicality of semantic and topological modelling methods, standards and mobility analysis algorithms.
  • Seek co-operation and involvement in the BIM and GML domains (in collaboration with OGC)
  • Propose and develop adapted mobility and navigation solutions for the people with disabilities and aging people in the context of smart and inclusive cities
  • Propose and develop green and resilient mobility and navigation solutions for sustainable cities



WG IV/9 - Spatially Enabled Urban and Regional Digital Twins

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Mila N. Koeva

University of Twente
Faculty Geo-Information Science and Earth Observation (ITC)
The Netherlands

Giorgio Agugiaro

Delft University of Technology
Julianalaan 134
Delft 2628BL
The Netherlands

Lucía Díaz Vilariño

University of Vigo
Department of Design in Engineering
School of Industrial Engineering

Mojgan Jadidi

Geomatics Engineering
Lassonde School of Engineering
York University

Youness Dehbi

Computational Methods Lab
HafenCity University
Henning-Voscherau-Platz 1
20457 Hamburg

Liu Liu

Tongji University
College of Architecture and Urban Planning

WG IV/9  Terms of Reference

  • Develop innovative geospatial or artificial intelligence based methods for real-time data analysis and data fusion and dynamic representation towards building, urban and regional digital twins
  • Review and combine methodologies for BIM, GIS, sensors, and IoT data integration and multi-dimensional web-based and VR/AR visualization
  • Promote testing, adaptation, and development of semantically rich and standardized 3D city models by incorporating multidisciplinary approaches for multi-dimensional dynamic representation of buildings, cities, and regions
  • Foster communication among scientists and practitioners from heterogeneous applications domains in order to facilitate understanding of common problems and develop implementable solutions
  • Foster discussion among different stakeholders about the implications associated with the adoption of digital twins in the real-world (e.g. challenges, opportunities, ethics, security, privacy)
  • Disseminate new technical and methodological advances, innovations, and research outcomes in the field of both academic audiences (e.g., publications, seminars, workshops) and public (e.g., blog posts, exhibitions, public talks).
  • Establish strong links between relevant international and regional organizations in order to achieve fruitful collaboration



WG IV/10 - Applied Spatial Science for Public Health

Home Page:

Sameer Saran

Geoinformatics Department
Remote Sensing and Geoinformatics Group
Indian Institute of Remote Sensing ( IIRS )
Indian Space Research Organisation (ISRO)
+91 9412917908

Frank B Osei

University of Twente
Faculty of Geo-Information Science and Earth Observation
ITC 2-031
P.O. Box 217
7500 AE Enschede
The Netherlands

Dilek Koç San

Akdeniz University
Faculty of Architecture,
Department of Urban and Regional Planning,
07058, Konyaalti/Antalya

Priyanka Singh

School of Computer Sciences,
University of Petroleum & Energy Studies,
Eergy Acres, Uttarakhand 248007
+91 7011828901

WG IV/10  Terms of Reference

  • Bridge the spatial technologies and public health science communities to explore interdisciplinary collaborations for research, training, and practice to address the growing public health threat
  • Increase awareness and promote the use of the Citizen Science approach among public health professionals for the collection of infectious, chronic, and vector-borne diseases incidence data 
  • Strengthen the spatial statistical robustness of public health research by addressing spatial and spatiotemporal uncertainty to conduct numerous simulations 
  • Advance the knowledge in the field of Multi-Dimensional spatial data handling and management as a selective approach for resource allocation and health policies
  • Evolve mechanism to develop meaningful insights and patterns on multi-dimensional data using Exploratory Spatial Data Analysis (ESDA) techniques to formulate a new hypothesis
  • Study the advances of Artificial Intelligence (AI), Deep Learning (DL), and Machine Learning (ML) with the amalgamation of geospatial technology in newer areas like supply chain management of critical resources, disease predictive modelling, hotspot detection, cluster-based response, and early warning systems
  • Contribute to open access public health data resources by developing a dedicated Health GIS resources repository on an open platform for communities and individuals to contribute to it
  • Build capacity to enhance interdisciplinary research collaborations in the fields of geospatial science and public health



WG IV/11 - Cultural Heritage Visualization and Virtual Restoration

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Grazia Tucci

Department of Civil and Environmental Engineering
University of Florence
Via Micheli 8
50121, Florence

Miaole Hou

School of Surveying and Mapping and Associate Dean, School of Humanities
Beijing University of Civil Engineering and Architecture
1 Exhibition Road
Xicheng District
Beijing, 100044

Mario Santana Quintero

Department of Civil and Environmental Engineering
Carleton University
1125 Colonel By Drive
Ottawa, ON, K1S 5B6
613-520-2600 ext. 3093 or 7468

Lei Luo

Aerospace Information Research Institute
Chinese Academy of Sciences
9 Dengzhuang South Rd.
Beijing, 100094

Stephen Fai

Carleton Immersive Media Studio
Azrieli School of Archietcture and Urbanism
Carleton University
1125 Colonel By Drive
Ottawa, ON, K1S 5B6
613’520.2600 ext. 3423

WG IV/11  Terms of Reference

The work of the WG will concentrate on the following topics:

Topic 1: Cultural heritage cognition and conceptual modelling

  • Cognition and ontology of cultural heritage
  • Data integration and knowledge discovery
  • GIS + HBIM integration of cultural heritage protection methods
  • Visualization of cultural heritage ( Big Data, BIM/CIM, AR/VR/MR, AI)
  • Conceptual modelling
  • Intelligent interaction, visualization, and information update

Topic 2: Deterioration monitoring and assessment of culture heritage

  • Identification, extraction and analysis of heritage deteriorations
  • Deep learning of heritage deteriorations: symptom classification and visualization
  • Dynamic monitoring of  heritage deteriorations based on hyperspectral and X-ray techniques
  • Analysis of the causes of heritage deteriorations
  • Immersive heritage deteriorations diagnosis
  • Evaluation and preventive protection of heritage deteriorations
  • Automated deteriorations mapping

Topic 3: Digital twins and virtual restoration of cultural heritage

  • Digital twins
  • Innovation technology of spatio-temporal information of cultural heritage
  • Virtual restoration, recovery, and reconstruction of cultural heritage
  • Digital storytelling presentation and interpretation of cultural heritage (space, material, value)
  • New Methods of Cultural Heritage Protection in the Post-epidemic Era

Topic 4: Heritage sustainability and other applications

  • Cultural heritage conservation and sustainable development based on multi-source information fusion
  • Sustainable development of cultural heritage based on the expansion of existing UNSDGs indicators
  • Digital cultural heritage applications and services
  • Innovating immersive experience and the industry of culture and tourism
  • Contextual education of cultural heritage
  • Digital cultural heritage interactive conservation with Public Participation
  • Archaeological prospecting using spatial technologies, including remote sensing, GIS, and GNSS.

AI-powered identification of archaeological sites and/or landscapes

Spatial analysis of the past human-enviroment interactions



ICWG IV/III - Global Mapping for SDGs

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Hongchao Fan

Norwegian University of Science and Technology
Department of Civil and Environmental Engineering, Division of Geomatics

Lucy W. Mburu

College of Technology
KCA University

Xiaoguang Zhou

School of Geosciences and Info-Physics Central South University
Changsha, Hunan, 410083

Xuke Hu

German Aerospace Center (DLR)
Institute of Data Science, Data Acquisition and Mobilisation

ICWG IV/III  Terms of Reference

In the next four years, this working group is going to focus on:

  • Identify key scientific and technological challenges of geospatial information and Earth observation in support of SDG monitoring.
  • Showcase the use of geospatial information and Earth observation as well as statistical and other data sources for measuring and monitoring SDGs.
  • Develop novel and innovative methods for deriving essential geospatial variables for SDGs through machine learning, big data analytics, cloud computing, and other related technologies.
  • Establish geospatial knowledge services and collaborative platforms to meet SDGs assessment and monitoring requirements.
  • Increase awareness and understanding of the vital and integrative role of geospatial information and Earth observation in monitoring SDGs.
  • Build capacities in the use of geospatial information and Earth observation in monitoring SDGs in developing countries.

In overall, the WG is aiming at bridging the gap between scientific research and practitioners, showing, on the one hand, real examples of implementation of best practices of global mapping, land cover mapping and big Geospatial Data with the special purpose of monitoring SDGs. On the other hand, acting as a platform to foster ideas for new multi-domains and intelligent approaches and applications.



ICWG IV/III/II - Openness in Geospatial Science and Remote Sensing

Home Page:

Marco Minghini

European Commission - Joint Research Centre (JRC)
Digital Economy Unit
Via Enrico Fermi 2749
21027 Ispra

Anca Anghelea

Department of Science, Applications and Climate
D/EOP, European Space Agency
Largo Galileo Galilei 1
00044 Frascati

Silvana Camboim

Department of Geomatics
Universidade Federal do Paraná
Centro Politécnico CEP 81.531-990 Curitiba, Paraná

Bolelang Sibolla

Council for Scientific and Industrial Research
Meiring Naudé Road, Brummeria
PO Box 395
Pretoria 0001
South Africa

Timur Obukhov

UN Geospatial, Office of Information and Communications Technology
United Nations
1 UN Plaza
New York, NY 10017

ICWG IV/III/II  Terms of Reference

  • Review the scientific and technological state of the art of openness (data, software, infrastructures, standards, policies and initiatives)  in domains relevant to Geospatial and Earth Observation.
  • Advance knowledge in the investigation of technological, social, organisational and legal enablers and barriers for the development of open approaches in the Geospatial and Earth Observation domains, pertaining to open data, open source software, open standards, open education and research, across three dimensions: accessibility, inclusiveness and reproducibility.
  • Promote the notions of open science and reproducibility of research in the domains of geospatial information science and remote sensing through the design, development and test of guidelines and best practices and by showcasing reference approaches. 
  • Design and support the establishment of approaches and good practices to increase awareness, adoption and engagement of the wider community in the fields of Geospatial and Earth Observation through open education and outreach (e.g. capacity building, open competitions, hackathons, etc.).
  • Foster communication and exchange between stakeholders and practitioners belonging to different user groups (academia, public sector organisations, data providers, businesses, standardisation bodies, humanitarian organisations, etc - all involved in the ICWG.) in order to facilitate understanding of common problems, develop and disseminate shared solutions and good practices.
  • Design and support educational and training activities in the domains of geospatial and remote sensing through dedicated events (e.g. webinars and workshops) and by sharing openly accessible educational material.
  • Promote collaboration between all ISPRS Working Groups under Technical Commissions III (Remote Sensing), IV (Spatial Information Science) and V (Education and Outreach).
  • Establish collaboration with relevant external organisations and initiatives in the policy, innovation and research fields relevant to Openness in Geospatial and Remote Sensing, including: the Open Source Geospatial Foundation (OSGeo) and its educational committee (GeoForAll); the Copernicus Programme; national and intergovernmental bodies and space agencies and their relevant programmes and initiatives on Open Science (e.g. ESA, NASA TOPS, United Nations, CEOS, etc.); OpenStreetMap (OSM) communities; the Humanitarian OpenStreetMap Team (HOT); the Open Geospatial Consortium (OGC); the Group on Earth Observation (GEO) and its European counterpart EuroGEO, in particular the GEO Data Working group; the International Cartographic Association (ICA) - Commission on Open Source Geospatial Technologies and Commission on SDIs and Standards; the YouthMappers initiative; the INSPIRE community;  the Pangeo community.
  • Promote special issues within the ISPRS International Journal of Geo-Information and other relevant scientific journals as well as books, reports and conference proceedings of events related to openness in geospatial and remote sensing.




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