Artificial night-time light data extraction
If artificial night-time lights (ANTL) are considered means for safety and security, then what is the optimum level of brightness to ensure safety and security without compromising the environment?
About the training
Artificial Night-time Lights (ANTL) have been widely used in social science research as a robust proxy for economic development, the quantification of disaster impacts, electricity consumption, and various other applications. However, employing ANTL in social science research requires a comprehensive understanding of confounding factors, necessitating their individual consideration based on the specific needs of the application. This training aims to provide hands-on experience in both the theory and application of ANTL.
Program objectives
This program will achieve the following outcomes:
- Raise awareness among emerging global leaders about ANTL.
- Share knowledge on ANTL theory, practice, and measurement techniques.
- Train students from the global south to extract, analyse, and visualise ANTL.
- Understand the limitations of satellite imagery in capturing artificial night-time lights.
Use the tabs below to find the information required to participate in this course.
Detailed information about each session is included below.
Date | Module | Session | Activities | Facilitator | Objective | |
---|---|---|---|---|---|---|
Week 1 | 25 June 2024 | Introduction and keynote | Part 1: Why and how of the training and session | 5 slides about the objective team, process and expectation (10 minutes) | Sobia Rose | Learn course, process and expectation |
Part 2: Keynote and Q & A | Keynote: Using Night Light data for socio-economic research (1.15 hour) | Professor John Gibson Department of Economics University of Waikato | Keynote | |||
Q&A with expert (25 min) | Chizoba Obianuju Oranu, University Of Nigeria Nsukka | Q & A | ||||
Summary and Thank you (10 minute) | Professor Margaret Chitiga-Mabugu University of Pretoria | Thank you note. | ||||
26 June 2024 | Module 1 | Part 1: Understand the ANTL | Presentation on what is ANTL, how it is captured, and why it is useful in social, economic and environmental terms. | Dipendra Bhattarai | Observe the data and guess the possible sources of nighttime lights. | |
Practical: From the reading materials find out and list the possible sources of nighttime lights. | ||||||
Part 2: Data sources | Potential data sources and confounding factors of ANTL. | Know open access data source and find the data that is useful for your study. | ||||
Week 2 | 2 July 2024 | Module 2 | Upload data and understand | Extract data and understand the format. | Dipendra Bhattarai, Darcy, Bishal, and WiZelle | Learn mapping |
Identify key issues and resolve | Identify key problem or issues in uploading data and resolve it. | |||||
Map your chosen data | Use open-source ANTL data and map it. | |||||
Play with the maps | Identify the hotspots and potential sources emitting ANTL. | |||||
Week 3 | 3 July 2024 | Module 3 | Part 1: Extract the annual ANTL data | Calculate the zonal statistics and export the data to tabular format. | Learn about application |
Contact details
If you are registered for this training and need assistance, contact the training or technical coordinators as below. For country-specific questions, reach out to your local coordinator (check the working group for their contact details).