This is a yolov8 based object detection model for beaver dams and lodges from aerial imagery
This is a semi-serious side-project to detect beaver dams and lodges from aerial imagery. Beavers are expanding into Arctic regions, which can be even observed indirectly from space. With very-high resolution data from UAV or airborne missions, we can try to map dams and lodges directly.
More cool information on beaver expansion into the Arctic:
- Tape, K. D., Clark, J. A., Jones, B. M., Kantner, S., Gaglioti, B. V., Grosse, G., & Nitze, I. (2022). Expanding beaver pond distribution in Arctic Alaska, 1949 to 2019. Scientific Reports, 12(1), 7123. https://doi.org/10.1038/s41598-022-09330-6
- Jones, B. M., Tape, K. D., Clark, J. A., Nitze, I., Grosse, G., & Disbrow, J. (2020). Increase in beaver dams controls surface water and thermokarst dynamics in an Arctic tundra region, Baldwin Peninsula, northwestern Alaska. Environmental Research Letters, 15(7), 075005. https://doi.org/10.1088/1748-9326/ab80f1
- Tape, K. D., Jones, B. M., Arp, C. D., Nitze, I., & Grosse, G. (2018). Tundra be dammed: Beaver colonization of the Arctic. Global Change Biology, 24(10), 4478–4488. https://doi.org/10.1111/gcb.14332
Info
Model file in pytorch format for ultralytics yolov8
bounding boxes of beaver dams and lodges
trained on aerial imagery from West and Northwest Alaska
This model takes RGB aerial images in high spatial resolution, suhc as UAV or airborne imagery. It was trained on images from tundra regions in NW Alaska.
Target objects were hand labelled with roboflow --> https://app.roboflow.com/awi-response/beaver-finder-vhr-imagery-a9hg9/
Related Code
github
https://github.com/initze/yolov8_object_detection/
Input data
RGB images
Known and potential issues
- false positives for curved shore areas
Classes
1: beaver dam 2: beaver lodge 3: building (not great)
Input data
Examples
The good ones
The bad ones
