ForestEyes Project: Conception, Enhancements, and Challenges
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Abstract (arXiv)
Rainforests play an important role in the global ecosystem. However, significant regions of them are facing deforestation and degradation due to several reasons. Diverse government and private initiatives were created to monitor and alert for deforestation increases from remote sensing images, using different ways to deal with the notable amount of generated data. Citizen Science projects can also be used to reach the same goal. Citizen Science consists of scientific research involving nonprofessional volunteers for analyzing, collecting data, and using their computational resources to outcome advancements in science and to increase the public's understanding of problems in specific knowledge areas such as astronomy, chemistry, mathematics, and physics. In this sense, this work presents a Citizen Science project called ForestEyes, which uses volunteer's answers through the analysis and classification of remote sensing images to monitor deforestation regions in rainforests. To evaluate the quality of those answers, different campaigns/workflows were launched using remote sensing images from Brazilian Legal Amazon and their results were compared to an official groundtruth from the Amazon Deforestation Monitoring Project PRODES. In this work, the first two workflows that enclose the State of Rondonia in the years 2013 and 2016 received more than 35,000 answers from 383 volunteers in the 2,050 created tasks in only two and a half weeks after their launch. For the other four workflows, even enclosing the same area (Rondonia) and different setups (e.g., image segmentation method, image resolution, and detection target), they received 51,035 volunteers' answers gathered from 281 volunteers in 3,358 tasks. In the performed experiments...
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 2 of its 69 references that are in the map. First posted on arXiv 24 Aug 2022.
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Citing papers per year: 2024: 4.
4 papers.
- 2024How to Identify Good Superpixels for Deforestation Detection on Tropical Rainforestscited by 3
- 2024A Satellite Band Selection Framework for Amazon Forest Deforestation Detection Taskcited by 2
- 2024Sampling Strategies based on Wisdom of Crowds for Amazon Deforestation Detectioncited by 2
- 2024Exploring Superpixel Segmentation Methods in the Context of Citizen Science and Deforestation Detectioncited by 1
- 2024Exploring Superpixel Segmentation Methods in the Context of Citizen Science and Deforestation Detection26 Nov 2024
- 2024How to Identify Good Superpixels for Deforestation Detection on Tropical Rainforests6 Sep 2024
- 2024Sampling Strategies based on Wisdom of Crowds for Amazon Deforestation Detection22 Aug 2024
- 2024A Satellite Band Selection Framework for Amazon Forest Deforestation Detection Task3 Apr 2024