Deep learning model to perform human settlements classification on Landsat 8 imagery. A brief summary of the item is not available. Add a brief summary about the item.
Deep learning package
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Item created: Feb 17, 2021 Item updated: Dec 30, 2024 Number of downloads: 4,472
Description
Human settlement maps are useful in understanding growth patterns, population distribution, resource management, change detection, and a variety of other applications where information related to earth surface is required. Human settlements classification is a complex exercise and is hard to capture using traditional means. Deep learning models are highly capable of learning these complex semantics and can produce superior results.
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
Raster, mosaic dataset, or image service. (Preferred cell size is 30 meters.)
Output
Applicable geographies
Model architecture
Training data
This model has been trained on an Esri proprietary human settlements classification dataset.
Sample results
Here are a few results from the model.
An in-depth description of the item is not available.
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Dashboard views: Desktop
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Applicable: 2d
Size: 146.907 MB
ID: f7754e9617b84356845e5f877d3c36c6
Image Count: 0
Image Properties
Layer Drawing
Using tiles from a cache
Dynamically from data
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Credits (Attribution)
No acknowledgements.Esri
Comments (5)
Mosaic datasets created with tools through this model will encounter errors when published to Enterprise; mosaic datasets created with native tools in Pro can be reasoned. “Ensure that you create a mosaic dataset using the Manage Landsat 8 imagery tool. Once created, you can use the multispectral mosaic dataset generated by the tool. This mosaic dataset can also be published as an image service and used as an input.”
Using the provided process to execute in Enterprise, the following errors occurred： esriJobMessageTypeInformative: Submitted. esriJobMessageTypeInformative: Executing... esriJobMessageTypeInformative: Start Time: 2024年12月5日 18:13:07 esriJobMessageTypeInformative: Raster Analytics helper service esriJobMessageTypeInformative: Running on ArcGIS Image Server. esriJobMessageTypeInformative: No cloud raster store. esriJobMessageTypeInformative: Classifying... esriJobMessageTypeError: {"messageCode": "RA_120219", "message": "ClassifyPixelsUsingDeepLearning failed."} esriJobMessageTypeError: {"messageCode": "RA_120306", "message": "Cause of failure: A raster error has occurred. The messages that follow will provide more detail.", "params": {"cause": "A raster error has occurred. The messages that follow will provide more detail."}} esriJobMessageTypeError: {"messageCode": "RA_120306", "message": "Cause of failure: Unable to prepare input raster(s) for the python raster function.", "params": {"cause": "Unable to prepare input raster(s) for the python raster function."}} esriJobMessageTypeError: {"messageCode": "RA_120306", "message": "Cause of failure: Failed to execute (ClassifyPixelsUsingDeepLearning).", "params": {"cause": "Failed to execute (ClassifyPixelsUsingDeepLearning)."}} esriJobMessageTypeInformative: Failed script ClassifyPixelsUsingDeepLearning... esriJobMessageTypeError: Failed to execute (ClassifyPixelsUsingDeepLearning). esriJobMessageTypeInformative: Failed at 2024年12月5日 18:14:34 (Elapsed Time: 1 minutes 26 seconds) esriJobMessageTypeError: Failed.
this particular error indicates the analysis job is running on ArcIGS Enterprise and the input image is not accessible. Can more detail be shared to this specific case? If there is a support ticket for this issue, could you share the ticket number?
i have a challenge to acess more ESRI content help me to have an organizationl accunt help me
anyone fro the technical authorities to help me on this one