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Deep learning model to detect and segment swimming pools in high-resolution aerial or satellite imagery. A brief summary of the item is not available. Add a brief summary about the item.

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Item created: May 18, 2023 Item updated: Feb 3, 2025 Number of downloads: 4,255

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Description

Swimming pools are important for property tax assessment because they impact the value of the property. Tax assessors at local government agencies often rely on expensive and infrequent surveys, leading to assessment inaccuracies. Finding the area of pools that are not on the assessment roll (such as those recently constructed) is valuable to assessors and will ultimately mean additional revenue for the community.

This deep learning model helps automate the task of finding the area of pools from high resolution satellite imagery. This model can also benefit swimming pool maintenance companies and help redirect their marketing efforts. Public health and mosquito control agencies can also use this model to detect pools and drive field activity and mitigation efforts. 

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 cannot be fine-tuned using ArcGIS tools.

Input

8-bit, 3-band high resolution (5-30 centimeters) imagery.

Output

Feature class containing masks depicting pool.

Applicable geographies

The model is expected to work well in the United States.

Model architecture

The model uses the FasterRCNN model architecture implemented using ArcGIS API for Python and open-source Segment Anything Model (SAM) by Meta.

Accuracy metrics

The model has an average precision score of 0.59.

Sample results
Here are a few results from the model.






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Terms of Use

https://downloads.esri.com/blogs/arcgisonline/esrilogo_new.png This work is licensed under the Esri Master License Agreement.

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

Comments (3)

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s1108564_ZGIS Item Owner commented a month ago Delete Reply

super

1542052797 Item Owner commented a year ago Delete Reply

Hello, how does ESRI's object detection model integrate with the SAM model

esri_analytics Item Owner commented a year ago Delete

This model takes the output bounding boxes from Pool Detection - USA model ( https://www.arcgis.com/home/item.html?id=0e7dffe605c24bdfadf3c376bdf2d413 ) and prompts SAM with their center points of the detected pools. SAM then produces segmentation masks for the pools that are converted to polygons and returned. Both models are called sequentially within this deep learning package.

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          ID: 0d4b8ab238b74da8819df21834338c0d

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          dlpk, Deep Learning, swimming pool, mask, object detection, living atlas, sam, segment anything, LivingAtlasDLPK

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          Esri, Meta

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