yolov8 remote sensing aerial imagery beaver object detection object-detection license:mit region:us
---
license: mit
pipeline_tag: object-detection
tags:
- yolov8
- remote sensing
- aerial imagery
- beaver
- object detection
---
# 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
  - More info: https://essd.copernicus.org/preprints/essd-2023-193/

- 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 
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/65d21a586a61dce9699400e8/NRsfZ_tJsRU7kWW6X80cb.jpeg)
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/65d21a586a61dce9699400e8/6rimx_aHakwtbkegOvzC4.jpeg)

### The bad ones
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/65d21a586a61dce9699400e8/tU70jjCWeD0fsXw3esu_X.jpeg)
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/65d21a586a61dce9699400e8/UWnXzbUFEGEtLCDEuFTBc.jpeg)
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/65d21a586a61dce9699400e8/iffGBy-If5rbWzfELh5SI.jpeg)