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ASEAN Regional Training Course on Geospatial Big Data Applications for Sustainable Development

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ASEAN Regional Training Course on Geospatial Big Data Applications for Sustainable Development

Satellite Analysis and Applied Research
Plazo: Cerrado
La inscripción está cerrada
Sri Racha, Thailand
5 Ago 2019 a 9 Ago 2019
Duración del evento:
5 Días
Área del programa:
Satellite Imagery and Analysis
Público Objetivo Específico:
Sin cargo
Correo Electrónico del Centro de Coordinación del Evento:
Número del Centro de Coordinación del evento:
Otros detalles del evento:

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[1]. 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 geosptial data can help us identify depleting natural resources, diagnose underlying caueses  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 analysing massive amounts of data are rapidly evolving and no single standard exists for generating actionalble information. This poses a huge challenge to the practitioners and decision maker for effectively utilizing geosptial 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.


UNITAR-UNOSAT, GISTDA, ARTSA,  and UNESCAP is 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).

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 webscraped 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

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.

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 hour 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 in Power Point presentations, live demos, videos, interactive sessions and geospatial big data analytic exercises. At the end of the course. 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 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. 

There are two groups of participants, self support participants and funded participants, available for this course. Both groups are supported with local expenses by local host (ARTSA and GISTDA, Thailand) excluded the life and health insurance.

UNESCAP and UNOSAT-UNITAR also offering the airfare grant for 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.


How to Appy

Sending invitation letter and attendance forms to all selected participants (for VISA purpose)

All applicants are requested to submit the application through ONLINE APPLICATION FORM with required documents as below detail list.

(1)  Online Application form can be accessed at

(2)  One Copy of Passport*

(3)  Curriculum vitae (Maximum 2 pages)*

(4)  One letter of recommendation: e.g. from your supervisor, head of the department or head of organization who  knows well your work (the recommendation form is available on training course website).

* Note: (2) and (3) should be prepated in PDF format and should be attached in the online application form

Important Dates

Call for course application

01 June 2019

Course application deadline

30 June 2019

Announcement of selected participants

5 July2019

Sending invitation letter and attendance forms to all selected participants

(for VISA purpose)

5 – 10 July 2019

Deadline for attendance form submission

20 July 2019

Travel to SKP, Thailand

4 Aug 2019

Geospatial Big Data Course

5 – 9 Aug 2019