Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery
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Abstract (arXiv)
Cattle farming is responsible for 8.8% of greenhouse gas emissions worldwide. In addition to the methane emitted due to their digestive process, the growing need for grazing areas is an important driver of deforestation. While some regulations are in place for preserving the Amazon against deforestation, these are being flouted in various ways, hence the need to scale and automate the monitoring of cattle ranching activities. Through a partnership with textitGlobal Witness, we explore the feasibility of tracking and counting cattle at the continental scale from satellite imagery. With a license from Maxar Technologies, we obtained satellite imagery of the Amazon at 40cm resolution, and compiled a dataset of 903 images containing a total of 28498 cattle. Our experiments show promising results and highlight important directions for the next steps on both counting algorithms and the data collection process for solving such challenges. The code is available at urlhttps://github.com/IssamLaradji/cownterstrike.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Nov 2020.
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Citing papers per year: 2021: 4; 2022: 2; 2023: 2; 2024: 1; 2025: 1.
10 papers.
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- 2021Automated Aerial Animal Detection When Spatial Resolution Conditions Are Variedcited by 5
- 2023Application of deep learning for livestock behaviour recognition: A systematic literature reviewcited by 5
- 2021Enhancing Environmental Enforcement with Near Real-Time Monitoring: Likelihood-Based Detection of Structural Expansion of Intensive Livestock Farmscited by 4
- 2021Detecting Cattle and Elk in the Wild from Spacecited by 0
- 2022Manipulating UAV Imagery for Satellite Model Training, Calibration and Testingcited by 0
- 2022Computer vision system to count crustacean larvaecited by 0
- 2025EarthView: A Large Scale Remote Sensing Dataset for Self-Supervision14 Jan 2025
- 2024Good at captioning, bad at counting: Benchmarking GPT-4V on Earth observation data31 Jan 2024
- 2023Application of deep learning for livestock behaviour recognition: A systematic literature review20 Oct 2023
- 2023GEO-Bench: Toward Foundation Models for Earth Monitoring6 Jun 2023
- 2022Computer vision system to count crustacean larvae13 Sep 2022
- 2022Manipulating UAV Imagery for Satellite Model Training, Calibration and Testing22 Mar 2022
- 2021Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark1 Dec 2021
- 2021Automated Aerial Animal Detection When Spatial Resolution Conditions Are Varied4 Oct 2021
- 2021Detecting Cattle and Elk in the Wild from Space29 Jun 2021
- 2021Enhancing Environmental Enforcement with Near Real-Time Monitoring: Likelihood-Based Detection of Structural Expansion of Intensive Livestock Farms29 May 2021