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Deep learning model to detect palm trees in high resolution imagery. A brief summary of the item is not available. Add a brief summary about the item.

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Item created: Dec 15, 2021 Item updated: Feb 25, 2025 Number of downloads: 13,680

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Description

This deep learning model is used to detect palm trees in high resolution drone or aerial imagery. Palm trees detection can be used for creating an inventory of palm trees, monitoring their health and location, and predicting the yield of palm oil, etc.  High resolution aerial and drone imagery can be used for palm tree detection due to its high spatio-temporal coverage.

Using the model

Follow the guide to use the model. Before using this model, ensure that the supported deep learning libraries are installed. For more details, check Deep Learning Libraries Installer for ArcGIS.

Fine-tuning the model
This model can be fine-tuned using the Train Deep Learning Model tool. Follow the guide to fine-tune this model.

Input
High resolution RGB imagery (5 - 15 centimeter spatial resolution).

Output
Feature class containing detected palm trees.

Applicable geographies
The model is expected to work well globally.

Model architecture
This model uses the FasterRCNN model architecture implemented in ArcGIS API for Python.

Accuracy metrics
This model has an average precision score of 75 percent.

Training data
This model has been trained on an Esri proprietary palm tree detection dataset.

Sample results
Here are a few results from the model. To view more, see this story.





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Terms of Use

 This work is licensed under the Esri Master License Agreement.

No special restrictions or limitations on using the item's content have been provided.

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    Dashboard views: Desktop

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          Applicable: 2d

          Size: 146.085 MB

          Attachments size: 0 KB

          ID: 916e02960d9e495baeb4d1d2ff4055d0

          Image Count: 0

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          palm tree, palm, trees, dlpk, LivingAtlasDLPK

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          Imagery from OpenAerialMap is licensed under CC-BY 4.0

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