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HomeResearch at CurtinCurtin Institute for Energy TransitionEngagementGlobal trainingEventsMapping heat stress with Google Earth Engine

Mapping heat stress with Google Earth Engine

While climate prediction data is readily available, a significant challenge in the Global South lies in effectively harnessing this data and understanding how it can be applied to context-specific planning.

About the training

The impacts of climate change are becoming increasingly visible and are falling disproportionately upon countries with weaker capacities to adapt. Supporting students and researchers to explore and understand these impacts will contribute to capacity building in contextual adaptation planning.

One of the impacts of climate change is heat stress. The increased frequency of heat stress induced by climate change is more likely to disproportionately affect developing countries, particularly households in poverty and those marginalised in terms of access to energy. Empowering local communities to assess the risks associated with heat stress and utilising this information for improved energy service planning is crucial for adaptation and overall well-being.

Program aims

This program will offer participants:

Insightful discussions on the intersection of heat stress and energy services.
Training for interested students on utilising Google Earth Engine to map the probability of experiencing heat stress and its impact on energy services.
Opportunities for students to work with their chosen datasets and share their findings, enhancing their skills in communicating climate change-related information.
Widespread access to valuable knowledge and learning resources via open-access information

Why participate?

To allow participants to work with climate model data and create their own heat stress maps. The participant will learn how to interpret visualisations of heat stress maps and use them as a tool to communicate the impact of heat stress and its spatial distribution. Participants will also be able to use the maps to inform possible energy demand in response to heat stress and tell their stories to local governments.

Learning outcomes

After completing the program, participants will be able to discuss climate data and describe the use of Google Earth Engine. Participant will be able to download the data and map the heat stress in different scenario and explain it to their friends and community.

Use the tabs below to find the information required to participate in this course.

Schedule
Content
Data/codes
Maps
Technical team

The program will run for three weeks. The first week will be a single two-hour general session with a keynote talk from an expert to provide the context and importance of heat stress mapping to understand future energy service requirements. The following two weeks will have technical sessions aimed at practitioners. There will be two two-hour sessions per week. In the final session, participants will present their map and briefly discuss their interpretations of it.

Dates and times

13-14 February 2024 (Week 1)

20-21 February 2024 (Week 2)

27-28 February 2024 (Week 3)

20:00hrs NZDT (New Zealand), 12:45 NPT (Nepal), 08:00 WAT (Nigeria)

The training program will encompass core concepts related to climate change data and the mapping of temperature data to locate the areas likely to suffer from the heat stress. It is designed to equip participants with fundamental skills for accessing climate data, utilising Google Earth Engine to create maps, and processing this data to analyse the spatial distribution of heat stress and ultimately inform changing energy needs.

To cater to individual interests, the program will feature 3 to 5 modules, allowing participants to select the modules that align with their preferences. Our informal working group will determine the specific set of modules. The learning approach involves a combination of instruction and hands-on practice.

Recognising that everyone progresses at their own pace, we have established separate breakout rooms to provide additional support. This ensures that all participants can successfully complete the course and achieve their personal learning objectives.