Open Nighttime Lights

Welcome

Module 1 Introduction to remote sensing

1. Introduction to remote sensing (20 min)
2. Introduction to nighttime light data (20 min)
3. VIDEO: introduction to remote sensing and nighttime lights

Module 2 Introduction to open data and tools

1. Data overview (10 min)
2. Getting started with Python (10 min)
3. Introduction to Jupyter notebooks (10 min)
4. Introduction to Google Earth Engine (GEE) (5 min)
5. GEE Python API and geemap (5 min)
6. Practical exercise: image visualization (10 min)
7. VIDEO: Introduction to open data and tools

Module 3 Basic operations on raster files

1. DMSP-OLS annual composites in Google Earth Engine (5 min)
2. Image clipping with VIIRS-DNB (5 min)
3. Conditional operations (10 min)
4. Cell statistics and basic band math (10 min)
5. Expressions (10 min)
6. Expressions (continued)
7. Making simple VIIRS-DNB annual composites (5 min)
8. Importing and exporting data (5 min)
9. VIDEO: Basic operations on raster files

Module 4 Charting

1. Time Series Charts
2. Histograms
3. VIDEO: Plots

Module 5 Data analysis and intercalibration

1. DMSP-OLS intercalibration (10 min)
2. Calculate rate of change (5 min)
3. Working with vector and raster data (10 min)
4. Comparing cities (5 min)
5. VIDEO: Statistical analysis

Module 6 Exercise in data fusion for image classification

1. Overview
2. Framing the analysis
3. Supervised learning and image classification
4. Intro to Sentinel-2
5. Intro to Global Human Settlement Layer
6. Data fusion: Sentinel-2, VIIRS-DNB, GHSL
7. Random Forest Classifier
8. Statistical inference

World Bank - Light Every Night AWS data archive

World Bank - Light Every Night

Applications of nighttime lights

High Resolution Electricity Access (HREA) Indicators

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Index

By World Bank
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