ASEAN Regional Training Course on Geospatial Big Data Applications for Sustainable Development
Background
The volume of data in the world is increasing exponentially. By some estimates, 90% of the data currently existing worldwide has been created in the last two years, and it is projected to increase by 40% annually. The data revolution encompassing the application of earth observation data, the open data movement, the rise of crowdsourcing, new information and communication technologies (ICTs) for data collection, and the explosion in the availability of big data, together with the emergence of artificial intelligence and the Internet of Things -- is already transforming society. Multi-temporal earth observation data and crowdsourced geospatial data can help us identify depleting natural resources, diagnose underlying causes and can help us devise informed planning for sustainable development. According to the UN global pulse to use big data for development we need to turn imperfect, complex, often unstructured data into actionable information. Often the tools and technologies for analyzing massive amounts of data are rapidly evolving and no single standard exists for generating actionable information. This poses a huge challenge to the practitioners and decision maker for effectively utilizing geospatial big-data for decision making.
As expressed in its Vision 2025, ASEAN highlights the need to promote and ensure balanced social and sustainable environment that meets the needs of the peoples at all times and to work towards a resilient community with enhanced capacity and capability to adapt and respond to social and economic vulnerabilities, disasters, climate change as well as emerging threats and challenges. The Asia-Pacific Plan of Action on Space Applications for Sustainable Development (2018–2030), which was adopted by ESCAP in 2018, is a regionally-coordinated, inclusive and country-needs driven blueprint that harnesses space and geospatial applications, as well as digital innovations to support ASEAN members and other countries in the region, particularly those with special needs, to address regional challenges towards achievement of the Sustainable Development Goals.
To meet this challenge, GISTDA, ARTSA, UNOSAT and UNESCAP are offering an introductory course in the use of Geo-Spatial Information Technology applications for big data relevant to different domains such as disaster risk management, environmental monitoring, hazard mapping and disaster risk reduction for achieving Sustainable Development Goals (SDGs).
Learning objectives
At the end of the course, participants should be able to:
- Define and describe basic concepts and terminology related to Geospatial Big Data Analytics
- Explain the advantages and limitations of using Geospatial Big Data Analytics
- Detect flood using RADAR satellite image and damage estimation using Google Earth Engine
- Monitor disaster situation using web scraped geodata
- Utilise big data techniques for monitoring carbon emission, smog and forest fire using Google Earth Engine
- Undertake the process to prepare actionable information through visual communication
Course content
The course will provide participants with a theoretical understanding of geospatial big data and within the context of geospatial data analysis, its application for problem identification, assessment, and decision support. Participants will also be challenged to solve a problem of their choice by developing a simple decision support application.
Duration and instructional methodology
This is a full-time, face-to-face course with lectures and lab exercises using geospatial big datasets and real case scenarios (60% lab exercises, 40% lectures and discussions). This course is divided into 5 modules. Each module is structured into 4 sessions of 1.5 hours each. The average workload per week is likely to be around 25-30 hours.
The course is designed in a way to have a balanced approach between theoretical and practical teaching methods consisting of PowerPoint presentations, live demos, videos, interactive sessions and geospatial big data analytic exercises. GISTDA, ARTSA, UNOSAT and UNESCAP will set up a community of practice platform to maximize the learning experience of participants and to provide all required technical backstopping and assistance to training participants during and after the training.
Expected participants from ASEAN countries
The course is designed to accommodate ASEAN participants, who work in the government sector as a public officer, from geoinformatics backgrounds and professional experiences. Previous experience in basic programming and algorithm development is recommended. Participation is limited to a maximum of 20 participants.
Software
Lab exercises will be based on free to use and opensource tools like QGIS, Orange, R (programing language) and Google Earth Engine.
Class size
The number of participants is limited to 15-20 (max.) to ensure quality support provided by the instructors.
Certificates
Students will be given a certificate issued by GISTDA, UNESCAP and UNITAR upon successful completion of the course.
Financial support
There are two groups of participants, self-support participants and funded participants, available for this course. Both groups are supported with local expenses by a local host (ARTSA and GISTDA, Thailand) excluded life and health insurance.
UNESCAP and UNOSAT-UNITAR also offering the airfare grant for a limited number of funded participants on competitive bases. A panel of judges from the local organiser and co-organiser in its sole discretion will review all application and decide on the fund recipient.
The applicant for funded participant must be a government officer in ASEAN country or official of ASEAN agencies.
Please indicate in the online course registration form if you would like to apply for the airfare grant as a funded participant and self-funded of airfare as self-support participant. (See at How to apply and required document)
Applicants of both groups will go through the selection process by the Committee.
How to apply and required documents
All applicants are requested to submit the application here with required documents as below detail list.
- The online application form can be accessed
- One copy of passport*
- Curriculum vitae (Maximum 2 pages)*
- One letter of recommendation: e.g. from your supervisor, head of the department or head of the organization who knows well your work (the recommendation form is available on the training course website).
*Note: (2) and (3) should be prepared in PDF format and should be attached in the online application form.