Tree crown delineation using detectreeRGB (Jupyter Notebook) published in the Environmental Data Science book - fork
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Input Datasets of detectreeRGB AI4ER MRes Project
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Environmental Data Science Book Community
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detectreeRGB source code
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Jupyter Notebook Forest modelling tree crown detect tree RGB
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Tree crown delineation using detectreeRGB (Jupyter Notebook) published in the Environmental Data Science book - fork
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description: The research object refers to the Tree crown delineation using detectreeRGB notebook published in the Environmental Data Science book. Purpose: Accurately delineating trees using detectron2, a library that provides state-of-the-art deep learning detection and segmentation algorithms. Modelling approach: An established deep learning model, Mask R-CNN was deployed from detectron2 library to delineate tree crowns accurately. A pre-trained model, named detectreeRGB, is provided to predict the location and extent of tree crowns from a top-down RGB image, captured by drone, aircraft or satellite. detectreeRGB was implemented in python 3.8 using pytorch v1.7.1 and detectron2 v0.5. Further details can be found in the repository documentation. Highlights: detectreeRGB advances the state-of-the-art in tree identification from RGB images by delineating exactly the extent of the tree crown. We demonstrate how to apply the pretrained model to a sample image fetched from a Zenodo repository. Our pre-trained model was developed using aircraft images of tropical forests in Malaysia. The model can be further trained using the user’s own images
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cite-as: Sebastian H. M. Hickman, and Alejandro Coca-Castro. "Tree crown delineation using detectreeRGB (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Mar 27 ,2022. https://w3id.org/ro-id/6bc62582-2f11-4983-a51c-0af32459eca6.

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Image showing interactive plot of detectreeRGB model predictions of tree crown over a sample drone image in Sepilok, Sabah, Malaysia
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