This internet browser is outdated and does not support all features of this site. Please switch or upgrade to a different browser to display this site properly.

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.

DateModuleSessionActivitiesFacilitatorObjective
Week 125 June 2024Introduction and keynotePart 1: Why and how of the training and session5 slides about the objective team, process and expectation (10 minutes)Sobia RoseLearn course, process and expectation
Part 2: Keynote and Q & AKeynote: Using Night Light data for socio-economic research (1.15 hour)Professor John Gibson Department of Economics University of WaikatoKeynote
Q&A with expert (25 min)Chizoba Obianuju Oranu, University Of Nigeria NsukkaQ & A
Summary and Thank you (10 minute)Professor Margaret Chitiga-Mabugu University of PretoriaThank you note.
26 June 2024Module 1Part 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 sourcesPotential data sources and confounding factors of ANTL.   Know open access data source and find the data that is useful for your study.
Week 22 July 2024Module 2Upload data and understandExtract data and understand the format.Dipendra Bhattarai, Darcy, Bishal, and WiZelleLearn mapping
Identify key issues and resolveIdentify key problem or issues in uploading data and resolve it. 
Map your chosen dataUse open-source ANTL data and map it.
Play with the maps Identify the hotspots and potential sources emitting ANTL.
 Week 33 July 2024Module 3Part 1: Extract the annual ANTL dataCalculate the zonal statistics and export the data to tabular format.Learn about application