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University of California, Los Angeles: Department of Geography
GEOG 182A - Winter 2024
Table of Contents
Table of Contents
Introduction (this page)
Nighttime Illumination Analysis - Methods, Results, and Discussion
NDVI Analysis - Methods, Results, and Discussion
Motivation
Motivation
Monitoring the effects of the war in Ukraine is difficult, especially near the front lines. War is volatile, and situations can change quickly.
This can complicate the already severe humanitarian effects that Ukrainian civilians face, and suddenly block aid efforts. Already, there is quantifiable food insecurity due to decreased crop yield (Deininger et al. 2023), and civilians everywhere have been affected by either urban warfare in their cities or significant refugee movement (Huang et al. 2023). On-the-ground data collection is difficult to near-impossible, and even official reports can be unreliable, or not up to date (Li et al. 2022).
In this context, remote sensing plays a vital role in learning about conflict. It can inform outside international observers, help aid organizations and NGOs, and create a lifeline between refugees and the homes they have left.
Study Area
Study Area
Our study area focuses on the frontline of the Russo-Ukrainian War, in the southeast of the country. This area is heavily agricultural, with a few major cities, and has seen significant change due to the conflict.
Ukraine is large
Ukraine is large
Ukraine is the second-largest country in Europe after Russia, at over 600,000 sq km
Ukraine is urban
Ukraine is urban
~70% of Ukrainians live in cities - Bakhmut, Kherson, Robotyne, Mariupol, and Donetsk are major cities near the frontline
Ukraine is agricultural
Ukraine is agricultural
Ukraine has more arable land than France, Germany, and Poland combined, and its crops largely supply developing countries
The war is in the south
The war is in the south
While the initial invasion attacked on four fronts, only the south and the east have had success
Learn about what night lights can tell us about the different sides of the war.
Can change in night illumination be used to identify areas under attack or soon to be?
Can changes in night lights be used to identify tactical differences in how the two sides of the war are choosing to fight?
Learn about how NDVI can illustrate the scale of a conflict and if it can show famine risk.
Can a change in land cover be used to show progression of the Ukrainian counteroffensive, or to predict territorial changes?
Can NDVI be used to predict famine risk by correlating the destruction of agricultural areas caused by warfare?
References
Deininger, K. et al., 2023, Quantifying war-induced crop losses in Ukraine in near real time to strengthen local and global food security. Food Policy, 115.
Huang, C. et al., 2023, Mapping of nighttime light trends and refugee population changes in Ukraine during the Russian–Ukrainian War. Frontiers Environmental Science, 12.
Li, L. et al., 2022, Multi-Scale Dynamic Analysis of the Russian–Ukrainian Conflict from the Perspective of Night-Time Lights. Applied Sciences, 12, no. 24.
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