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

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Organization: UN Institute for Training and Research, UN Economic and Social Commission for Asia and the Pacific
Country: Thailand
Registration deadline: 30 Jun 2019
Starting date: 05 Aug 2019
Ending date: 09 Aug 2019

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

5th – 9th August 2019At ASEAN Research and Training Center for Space Technology and Applications (ARTSA) Sirindhorn Center for Geo-Informatics (SCGI), Space Krenovation Park, Chonburi Province, Thailand

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% annually1. 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 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).

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. 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.

Description of the modules

Module A1: Introduction to geospatial big data analytics for sustainable development

  • Asia-Pacific Plan of Action on Space Applications for Sustainable Development (2018 – 2030) - UNESCAP

The Plan of Action is a regionally coordinated, inclusive and country-needs driven blueprint that harnesses space and geospatial applications, to achieve the 2030 Agenda for Sustainable Development. The Plan of Action is fully aligned with ESCAP’s Regional Roadmap for Implementing the 2030 Agenda for Sustainable Development in Asia and the Pacific. It maps the sectoral needs and resources at national and regional levels.

This topic will increase understanding of the regional action plan on using space and geospatial applications in ASEAN member counties and able to apply to the project and work in the participant’s agency.

  • Roles of geospatial big data in geoinformatics application for sustainable development – KING MONGKUT’S INSTITUTE OF TECHNOLOGY LADKRABANG, THAILAND

Achieving sustainable development presents all countries and the global policy community with a set of significant development challenges that are almost entirely geographic in nature. Many of the issues impacting sustainable development can be analyzed, modelled, and mapped within a geographic context, which in turn can provide the integrative framework necessary for global collaboration, consensus and evidence-based decision-making.

This topic aims to explore a new trend technology of geospatial big data, which can be used to address scientific and societal issues and to develop a potential methodology on how to improve more precise and timely results through big data analytic approaches.

Module A2: Geospatial big data application for disaster risk management

  • Flood monitoring and damage assessment from time-series satellite image using Google Earth Engine -UNOSAT

Between July and September 2018 much of Lao PDR was under water. To understand the flood dynamics for the whole country for a duration of two months requires a staggering amount of 237 RADAR satellite images to be analyzed. Using a traditional technique of image by imager flood extraction would require at least several months to come up with the statistics.

In this scenario, the Google Earth Engine platform will be used to extract flooding duration and extent and a massive scale.

  • Disaster monitoring using web-scrapped big data – CHULALONGKORN UNIVERSITY, THAILAND

The combined application of location identification in mobile phones, social network and computers with cloud computing can help faster detection of natural disaster location. By combining information related to disaster situation from Twitter and satellite observations, a scientist can build a real-time map of the location, timing, and impact of disaster assessment.

This topic aims to train the participant to practise writing programing language to extract disaster information and location from Twitter for assessing and monitoring the situation efficiently and timely.

Module A3: Geospatial big data for environmental management

  • Wildland fires, smoke and haze – HYDRO-INFORMATICS INSTITUTE (HII), THAILAND

Wildland fires, smoke and haze consider as a regional problem. Active fires can be detected and utilized in wildfires control. They emitted carbon, carbon dioxide and other greenhouse gases which will continue to warm the planet well into the future. They damage forests that would otherwise remove CO2 from the air. Moreover, they inject soot and other aerosols into the atmosphere, with complex effects on warming and cooling. To timely cope with this growing problem, a combination of satellite image processing with near real-time data supplied by multi-sensors is needed.

This topic will aim to improve the understanding of big data application for forest fire detection and management where is the source of carbon emissions using Google Earth Engine, Sentinel Hub, NASA FIRMS, NASA WorldView, etc.

  • Big data application for social development – CHINESE UNIVERSITY OF HONG-KONG (CUHK), THAILAND

Big Data refers to data sets of much larger size, higher frequency, and often more personalized information. It ensures will be the next frontier for innovation, competition and productivity. Using machine learning technology, a field of data science known as predictive analytics shows the value in large amounts of data. This advantage can be adapted for social development by understanding society and social interaction in ways we never could before.

With the group project, participants will apply big data analytics for preparing actionable information for social benefits.

Module A4: Group project on big data application

  • Technical visiting at Space Krenovation Park - GISTDA, THAILAND

Space Krenovation Park (SKP) was established in 2012 by Geo-Informatics and Space Technology Development Agency (GISTDA). SKP offers a new focus for development on the challenges of meeting global demands in geo-informatics and space technology. SKP comprise of GISTDA’s operation centre to control the THAICHOTE satellite and also to receive the images from various other satellites, Space Inspirium - first Thailand’s space museum. It also will serve as an incubator for young entrepreneurs in the country to set up their business.

In this session, all participants will have a chance to visit all facilities in SKP under the guideline of GISTDA’s experts and satellite engineer to understand the role space technology support to country development.

Module A5: Data visualization

  • Prepare actionable information through visualization - UNOSAT

Infographics - a clipped compound of "information" and "graphics" - are graphic visual representations of information, data or knowledge intended to present information quickly and clearly. Infographics have been around for many years and recently the increase of a number of easy-to-use, free tools have made the creation of infographics available to a large segment of the population.

This topic aims to let everyone understand the concept of infographic and demonstrate infographic application for mapping representing the result of geospatial big data analysis.

Organizers

  • ASEAN Research and Training Center for Space Technology and Applications : (ARTSA)
  • Ministry of Higher Education, Science, Research and Innovation
  • Geo-Informatics and Space Technology Development Agency (Public Organization) (GISTDA)
  • United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP)
  • UNITAR’s Operational Satellite Applications : (UNOSAT)

Collaborator

  • Hydro Informatics Institute (HII), Thailand
  • Chulalongkorn University, Thailand
  • King Mongkut’s Institute of Techmology Ladkrabang, Thailand
  • Chinese University of Hong Kong (CUHK), China
  • United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA)
  • The Regional Committee of United Nations Global Geospatial Information Management for Asia and the Pacific (UNGGIM-AP)

Date & Place

Date: Monday 5th – Friday 9th August 2019 (5 days)

Place: ARTSA, Sirindhorn Center for Geo-Informatics Building,

Space Krenovation Park (SKP), SriRacha, Chonburi, Thailand. Location: 13.102001 N,100.928833 E

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.

Language The language of the training course will be conducted in English.

Lecturers
The lecturers will be conducted by experts on geospatial big data from Thailand, UNESCAP, UNOSAT and prominent organizations.

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.


How to register:

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

  1. The online Application form can be accessed at http://artsa.gistda.or.th/geobigdata2019
  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 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


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