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Deep learning model to extract land parcels from high-resolution aerial and 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 27, 2021 Item updated: Dec 30, 2024 Number of downloads: 7,579

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Description

Parcels are units of land that identify property boundaries and are useful for basemap creation and for land management. Traditionally, parcel mapping has been done using highly accurate surveying techniques, but this can be expensive and time consuming. High resolution imagery is increasingly being used for plot delineation, and the use of deep leaning models can automate and speed up the process.

Residential parcels are often associated with visible boundaries, but since legally valid parcels can be defined without a clearly demarcated boundary, this model only deduces their plausible approximations. This model can be used to create basemaps, which can be further refined by manual editing.

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
3-band high-resolution (40–50 cm) imagery.

Output
Feature layer with the number of classes as count of people.

Applicable geographies
The model is expected to work well in the United States. It works well in areas with high urban density and low vegetation.

Model architecture
The model uses the BDCNEdgeDetector model architecture implemented using ArcGIS API for Python.

Accuracy metrics
The model has an accuracy of 73.2 percent when classifying pixels belonging to edges.

Training data
This model has been trained on an Esri proprietary parcel extraction dataset.

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

Land Parcel Model predicted area 1

Land Parcel Model predicted area 2

Land Parcel Model predicted area 3

Land Parcel Model predicted area 4

Land Parcel Model predicted area 5

An in-depth description of the item is not available.

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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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qnadeemrer Item Owner commented a month ago Delete Reply

I am trying to use thi smodel, for that I first want to use the same dataset that has been used in the model, and also to know AOI . is it possible to get this information just make sure the model is working fine

goriliukasbuxton Item Owner commented 3 years ago Delete Reply

the Detect Objects using the DL too fails with this model and the custom Extract Parcels tool also fails

sdas_deldev Item Owner commented 3 years ago Delete

Hi, We don't use the 'Detect Object using DL' tool here. You can use the pre-trained model with the 'Classify Pixels using Deep Learning' tool to get only predicted raster without post-processing or use the tool directly. Please, share the versions of ArcGIS Pro and ArcGIS Python API and also share the error message that you are getting while running the tool. Thanks

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          ID: ee7a5cf6ea4242f7a33014c6d16096ce

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          land parcel, deep learning, pre-trained model, dlpk, living atlas, edge detection, bdcn

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