NCN project co-financed by Norwegian funds carried out in a large international consortium. Composition of the consortium listed at https://harsval.eu/

Main objectives of the project

1. Activities aiming at modernisation and standardisation of Svalbard observing system in priority areas for the Polish and Norwegian polar communities.
2. Activities aiming at the development of competencies and skills, internationalisation, and increasing visibility of the Polish polar community, implemented in Polish-Norwegian cooperation.
3. Activities in the area of FAIR data and open science:
4. Activities in the area of dissemination, communication and management:

CENAGIS is involved in the development of the Polar Database. The Polish Polar Consortium has decided to develop the Polish Polar DataBase (PPDB), a nationwide data repository, in a distributed database system. The PPDB has already been part of the SIOS Data Management System (SIOS –  Svalbard Integrated Arctic Earth Observing System). Based on the experience of the SIOS and previous cooperation with Norwegian partners, which are among the leaders in the field of data sharing, it is planned to build a training platform for data stewards and IT specialists to improve broad access to unique research data.

The activity will be performed using the Centre for Scientific Geospatial Analyses and Satellite computations (CENAGIS) cloud-based IT platform.

Planned activities:

1. Design and development of the fundamental components for the Central Geospatial Services Server for the Polish Polar DataBase:

• Development of the tools for integration with other polar research databases (e.g., SIOS Data Access Portal)
• Development of tools for integration with other thematic data services (e.g. international GNSS services, EUREF, EUPOS etc.)
• Configuration of basic tools and applications for data geovisualization
• Configuration of basic tools and applications for data analysis, including the use of big data and artificial intelligence

2. Supporting data sharing by qualified data stewards.

The aim of the project is to develop a service for the inventory and modelling of key technical and transportation infrastructure objects in BIM technology using artificial intelligence tools. The project includes research on implementing deep machine learning solutions based on three-dimensional photogrammetric data acquired by drones equipped with cameras and laser scanners. The project is being carried out in a consortium of the Warsaw University of Technology and SkySnap.

The aim of the project is to study the possibility of using laser scanners and multi- and hyperspectral cameras in the analysis of wooded areas. The project is being carried out in cooperation with Dragonfly Vision. As part of the project, raids are being made with UAV survey platforms over wooded areas in the leafy and leafless seasons. The systematic charges will allow us to test the results reproducibility and carry out a long-term analysis of the state of the forest stand and remote sensing support in its inventory. The project will result in a methodology for acquiring and processing data from UAVs in forested areas. As part of the project, software as a service (SaaS) is being developed to automatically process the data and make the results available to end users in an interactive form.

The aim of the project is to develop a methodology for analyzing the development of the COVID-19 epidemic in time and space, which would enable the construction of a decision support system for social distancing. Implementation of the project requires collecting and processing multi-source epidemiological, geospatial, demographic, economic, climatic and social data. The collected data will enable the preparation of three simulation models using: multi-agent modelling, deep learning, and Monte Carlo simulations.

The aim of the project is to develop a prototype simulation system for planning the terratransformation of Mars. The system created under the project will be used for variant analyses of the terratransformation of the planet. The proposed methods will use multi-scale terrain models of the planet’s terrain fragments to select optimal areas for different development methods, e.g., delineating communication routes and supporting location-navigation systems. The system uses deep learning machine learning methods, multi-source data and relief models, and planetary measurements made by the Opportunity and Curiosity Mars rovers.

The project aims to support the communities and development of rural areas of Mazovia, as well as to strengthen traditional and create new networks of links between stakeholders through modern means of communication, and above all, to raise public awareness of rural development. The basis for achieving the objectives will be to carry out scientific research and analysis involving the identification of elements slowing down agricultural development, assessing farming conditions and identifying factors affecting the slowing down of agricultural

The aim of the project is to reconstruct the building layout of the ancient city of Nea Paphos, located in Cyprus. The result of the integrated research results will be the reconstruction of the cityscape and buildings in the form of 3D models. Among other things, photogrammetric UAV flights are being used for this purpose. The 3D reconstructions obtained will then be subjected to spatial analysis to determine the relationship between the layout of buildings and streets and the functioning of the city in terms of visibility, population flow, potential population, etc.

The international project (OPUS LAP) is carried out in cooperation between the Forest Research Institute, Warsaw University of Technology and the University of Natural Resources and Life Sciences (Vienna).

One of the ways to mitigate the potential negative effects of recreation and tourism is to have information about the public’s preferences, times and places of tourism and its intensity. This information can form the basis for decisions on the placement and adaptation of infrastructure for different user groups, channeling tourist traffic to fit a specific user group.

Taking the above into account, the project focuses on the potential for the provision of cultural ecosystem services (CES) by urban and suburban forest areas in the two metropolitan areas of Warsaw and Vienna. In addition, public demand for such services will be determined, as well as elements related to recreational mobility (hot spots, movement directions) will be studied. The project will use state-of-the-art technology and large data sets (Big Data) from multiple sources to map and valorize the CES. Among the data resources are: social geographic information data (e.g., from Flickr, Twitter); open spatial data from Copernicus, OGD Vienna projects, etc. Therefore, an important goal of the project is also to explore the potential and limitations of Big Data in CES analysis. The project will use the advanced cyberinfrastructure of the “Center for Scientific Geospatial Analysis and Satellite Computing (CENAGIS)” to perform analyses.

Link to the project on FB and Twitter:  
https://www.facebook.com/profile.php?id=100090749589152 
https://twitter.com/ForRest_bigdata