CRIB supports geospatial big data-related tasks and activities of various research projects at ITC and partner organisations by providing consultancy and expert advice, helping in system and analysis workflow design, performing geospatial analyses, and developing software.
- ESA EO Africa Research and Development Facility
A consortium led by ITC is designing and developing ESA's EO AFRICA Research and Development Facility, which aims to develop a cloud-based Innovation Lab to support 30 joint African-European research projects in food security and water scarcity, as well as to set up EO Africa Space Academy and Digital Space Campus for knowledge development activities. CRIB is supporting the setup and operation of the EO Africa Innovation Lab.
- Open Source Scientific Computing for AgroGeospatial Big Data Analysis
ITC has a Nuffic (The Dutch Organisation for Internationalisation in Education) Tailor-Made Training Plus (TMT+) project proposal with the Bangladesh Agricultural Research Institute (BARI) to further develop BARI's capacity in big geospatial data analytics, machine and deep learning, analysis-ready data, and open-source programming and modelling software. CRIB will support hands-on training on big geospatial data technology.
- Remote Sensing Deployable Analysis environmenT (RS-DAT)
eScience Center - SURF Alliance project aims to develop an environment that will provide scientists with tools to access RS data and analyze it, enabling them to use the massive storage and infrastructure offered by SURF. Selected research projects will serve as use cases that will provide insight into the common needs of the EO community and will act as drivers enabling development of generic tools to address these needs. Each generic tool will be delivered with a dedicated tutorial, a demo, and with a deployment recipe on SURF facilities, to promote and ease the environment's adaptation by the scientific community. CRIB is supporting the tool on phenology.
- Mapping phenoregions over Europe and the contiguous United States using AWS
This project aims to develop a proof of concept of the Clustering Geo-data Cubes (CDC) package in AWS to apply advanced clustering workflow to large collection of high spatial and temporal resolution geospatial data. In particular, the use of AWS technologies (e.g., EMR, Kubernetes, ParallelCluster, etc.) to efficiently scale up the computing will be investigated. CRIB supports workflow development and testing.
- Accelerating Process Understanding for Ecosystem Functioning under Extreme Climates with Physics-Aware Machine Learning (EcoExtreML)
This project will couple the vegetation photosynthesis model (SCOPE) with the soil moisture model (STEMMUS, considering dynamic root growth), synergized with Earth-Observation data, to understand how the water-carbon dynamics of an ecosystem vary with environmental and climate stress. CRIB will support development of containerized workflows that will enable distributed data analysis and modeling at global scale.
- Development of a Prototype Computing Platform for UT
Based on the design of ITC Geospatial Computing Platform (GCP), the Library, ICT Services & Archive (LISA) department of the University of Twente decided to develop a similar computing platform for the use of all UT faculties and institutes. CRIB is supporting the initiative by actively contribution to the co-development of the platform.
- Geospatial Computing Platform - VRE Integration
- Multi-threaded Minimum Travel Cost Computation at Global Scale: Globetrotter
Travel time and accessibility analysis plays an important role in many geospatial problems. Global-scale accessibility computations at medium-resolution currently require significant processing time. ITC researchers are working on optimized methods to reduce this time. CRIB takes part in the study by developing parallel algorithms optimized for regular grids and implementing them in various languages, e.g. Go and C++.
- FAO State of Food and Agriculture (SOFA) Phase II (2021)
ITC developed national level indicators for FAO's State of Food and Agriculture report, which captured structural vulnerability of the domestic food system to disruptions in transportation or agricultural area. Second phase aimed to further develop the methodology formed in phase one to include import/export and run it for more than 90 counties. CRIB supported development of the import/export distribution model and international trade stations.
- IDEAMAPS: Modelling Platform (2020-2021)
IDEAMAPS is a network of field-based community mappers, local governments, academics, and data scientists to to develop and maintain an Integrated DEprived Area MAPping System (IDEAMAPS) that leverages the strengths of our current silo-ed approaches to "slum" area mapping. CRIB provided support for the design of the data sharing and mapping framework. ITC's Geospatial Computing Platform also utilized as the modelling platform of the project.
- Digital Earth Africa: Capacity Development Strategy (2020-2021)
ITC is a partner of the Digital Earth Africa, which is a community activity under GEO aiming to provide an operational big earth observation data service to address challenges of Africa. CRIB supported activities related to the development of the capacity development strategy and implementation plan.
- eScience Center Phenology Alliance (2020)
The Netherlands eScience Center set an alliance with ITC for high spatial resolution phenological modelling at continental scales. eScience Engineers and ITC researchers collaborated closely in the development of a distributed computing software package to perform clustering analysis for multidimensional geospatial data (Clustering Geo-data Cubes). CRIB contributed to the development of the package.
- FAO State of Food and Agriculture (SOFA) Phase I (2020)
ITC developed national level indicators for FAO's State of Food and Agriculture report, which captured structural vulnerability of the domestic food system to disruptions in transportation or agricultural area. First phase aimed to develop the basic methodology and tested it for a country (Nigeria). CRIB supported development of the analysis methods.
- Integration of interactive research environments to data repositories to facilitate FAIR data management practices: JupyterFAIR
This project proposal submitted to NWO Open Science Fund 2020/2021 aims to develop and operationalize a tool (JupyterFAIR) for 'one-click' and seamless integration of research environments and data repositories, including metadata transfer and data quality checks. The tool will significantly decrease manual intervention needed to archive research data and promote more frequent data sharing in line with FAIR principles. Project team lead by CRIB includes researchers from ITC, TU Delft DCC, and 4TUResearch.Data.
- Secure and Responsible Data Exchange and Processing for Enhanced Public Services
This NWO Data and Intelligence (KIC) project proposal led by TU Delft aims to develop a framework for fast information sharing and processing of data between a control room and the professionals in the field for govenmental organisations in the safety/security domain. Among the different fields of application, the project will develop a proof-of-concept focusing on developing solutions exploiting remotely sensed data collected by satellites and drones and specifically devoted to fighting criminal activities and synthetic drug productions. CRIB will support the design of the big data computing infrastructure.