{"id":2585592,"date":"2024-11-19T00:01:50","date_gmt":"2024-11-19T08:01:50","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=2585592"},"modified":"2024-11-19T01:38:39","modified_gmt":"2024-11-19T09:38:39","slug":"whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4","title":{"rendered":"What&#8217;s new for GeoAI in the Image Analyst extension of ArcGIS Pro 3.4"},"author":254042,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[770712,22931],"tags":[758311,777362,665211,115262,515302],"industry":[],"product":[36561],"class_list":["post-2585592","blog","type-blog","status-publish","format-standard","hentry","category-geoai","category-imagery","tag-ai","tag-feature-extraction","tag-geoai","tag-imagery","tag-object-detection","product-arcgis-pro"],"acf":{"short_description":"ArcGIS Pro version 3.4 enhances GeoAI for imagery with expanded training data support, new foundation models, improved object detection and more","flexible_content":[{"acf_fc_layout":"content","content":"<p>The <span data-teams=\"true\">latest <\/span>ArcGIS Pro version brings exciting advancements in GeoAI for imagery. Discover the top features we&#8217;ve added to enhance your workflow.<\/p>\n<h2>Expanded support for external training data<\/h2>\n<p>The <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/tool-reference\/image-analyst\/train-deep-learning-model.htm\">Train Deep Learning Model<\/a> tool now offers flexibility in training data sources for object detection. Besides the data from the <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/tool-reference\/image-analyst\/export-training-data-for-deep-learning.htm\">Export Training Data For Deep Learning<\/a> tool, it can now use external data in Pascal Visual Object Classes or KITTI rectangles formats. Just organize the data into images and labels folders. This update makes the tool compatible with numerous open-source and commercial software tools that generate training data differently, thus enhancing its versatility and efficiency.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2585602,"id":2585602,"title":"A Pascal VOC format training data example with training data organized in images and labels folders. The xml on the right shows an example label file.","filename":"A-Pascal-VOC-format-training-data-example.png","filesize":242641,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/A-Pascal-VOC-format-training-data-example.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4\/a-pascal-voc-format-training-data-example","alt":"A Pascal VOC format training data example with training data organized in images and labels folders. The xml on the right shows an example label file.","author":"254042","description":"A Pascal VOC format training data example with training data organized in images and labels folders. The xml on the right shows an example label file.","caption":"A Pascal VOC format training data example with training data organized in images and labels folders. The xml on the right shows an example label file.","name":"a-pascal-voc-format-training-data-example","status":"inherit","uploaded_to":2585592,"date":"2024-11-14 18:47:29","modified":"2024-11-14 18:55:22","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1259,"height":515,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/A-Pascal-VOC-format-training-data-example-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/A-Pascal-VOC-format-training-data-example.png","medium-width":464,"medium-height":190,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/A-Pascal-VOC-format-training-data-example.png","medium_large-width":768,"medium_large-height":314,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/A-Pascal-VOC-format-training-data-example.png","large-width":1259,"large-height":515,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/A-Pascal-VOC-format-training-data-example.png","1536x1536-width":1259,"1536x1536-height":515,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/A-Pascal-VOC-format-training-data-example.png","2048x2048-width":1259,"2048x2048-height":515,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/A-Pascal-VOC-format-training-data-example-826x338.png","card_image-width":826,"card_image-height":338,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/A-Pascal-VOC-format-training-data-example.png","wide_image-width":1259,"wide_image-height":515}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<h2>Enhanced AI-assisted labeling<\/h2>\n<p>The <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/help\/analysis\/image-analyst\/label-objects-for-deep-learning.htm\">AI-assisted labeling<\/a> experience has been enhanced by removing anomalies in the detections, as well as being able to automatically label image collections. By turning on the <strong>Remove Anomalies<\/strong> option in the AI- assisted labeling properties, the tool now automates the process of removing most, if not all, of the false positive detections.<\/p>\n"},{"acf_fc_layout":"content","content":"<h2>Support for new foundation models<\/h2>\n<p><a href=\"https:\/\/github.com\/microsoft\/ClimaX\">ClimaX<\/a> is a <a href=\"https:\/\/huggingface.co\/docs\/transformers\/main\/en\/model_doc\/vit\">Vision Transformer<\/a> (ViT) based deep learning model that uses diverse datasets that cover various weather variables across different spatial and temporal resolutions. This foundational model can be fine-tuned for a broad range of climate and weather applications, including tasks involving atmospheric variables and spatio-temporal details not encountered during the pretraining phase.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2585672,"id":2585672,"title":"An example multidimensional dataset used to predict weather change using ClimaX","filename":"An-example-multidimensional-dataset-used-to-predict-weather-change-using-ClimaX.png","filesize":191550,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-multidimensional-dataset-used-to-predict-weather-change-using-ClimaX.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4\/an-example-multidimensional-dataset-used-to-predict-weather-change-using-climax","alt":"An example multidimensional dataset used to predict weather change using ClimaX","author":"254042","description":"An example multidimensional dataset used to predict weather change using ClimaX","caption":"An example multidimensional dataset used to predict weather change using ClimaX","name":"an-example-multidimensional-dataset-used-to-predict-weather-change-using-climax","status":"inherit","uploaded_to":2585592,"date":"2024-11-14 19:07:30","modified":"2024-11-14 19:07:42","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":422,"height":310,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-multidimensional-dataset-used-to-predict-weather-change-using-ClimaX-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-multidimensional-dataset-used-to-predict-weather-change-using-ClimaX.png","medium-width":355,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-multidimensional-dataset-used-to-predict-weather-change-using-ClimaX.png","medium_large-width":422,"medium_large-height":310,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-multidimensional-dataset-used-to-predict-weather-change-using-ClimaX.png","large-width":422,"large-height":310,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-multidimensional-dataset-used-to-predict-weather-change-using-ClimaX.png","1536x1536-width":422,"1536x1536-height":310,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-multidimensional-dataset-used-to-predict-weather-change-using-ClimaX.png","2048x2048-width":422,"2048x2048-height":310,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-multidimensional-dataset-used-to-predict-weather-change-using-ClimaX.png","card_image-width":422,"card_image-height":310,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-multidimensional-dataset-used-to-predict-weather-change-using-ClimaX.png","wide_image-width":422,"wide_image-height":310}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"image","image":{"ID":2585692,"id":2585692,"title":"ClimaX being used in ArcGIS Pro for sea surface temperature analysis","filename":"ClimaX-being-used-in-ArcGIS-Pro-for-sea-surface-temperature-analysis.gif","filesize":81797,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ClimaX-being-used-in-ArcGIS-Pro-for-sea-surface-temperature-analysis.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4\/climax-being-used-in-arcgis-pro-for-sea-surface-temperature-analysis","alt":"ClimaX being used in ArcGIS Pro for sea surface temperature analysis","author":"254042","description":"ClimaX being used in ArcGIS Pro for sea surface temperature analysis","caption":"ClimaX being used in ArcGIS Pro for sea surface temperature analysis ","name":"climax-being-used-in-arcgis-pro-for-sea-surface-temperature-analysis","status":"inherit","uploaded_to":2585592,"date":"2024-11-14 19:08:51","modified":"2024-11-14 19:09:28","menu_order":0,"mime_type":"image\/gif","type":"image","subtype":"gif","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":624,"height":351,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ClimaX-being-used-in-ArcGIS-Pro-for-sea-surface-temperature-analysis-213x200.gif","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ClimaX-being-used-in-ArcGIS-Pro-for-sea-surface-temperature-analysis.gif","medium-width":464,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ClimaX-being-used-in-ArcGIS-Pro-for-sea-surface-temperature-analysis.gif","medium_large-width":624,"medium_large-height":351,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ClimaX-being-used-in-ArcGIS-Pro-for-sea-surface-temperature-analysis.gif","large-width":624,"large-height":351,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ClimaX-being-used-in-ArcGIS-Pro-for-sea-surface-temperature-analysis.gif","1536x1536-width":624,"1536x1536-height":351,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ClimaX-being-used-in-ArcGIS-Pro-for-sea-surface-temperature-analysis.gif","2048x2048-width":624,"2048x2048-height":351,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ClimaX-being-used-in-ArcGIS-Pro-for-sea-surface-temperature-analysis.gif","card_image-width":624,"card_image-height":351,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ClimaX-being-used-in-ArcGIS-Pro-for-sea-surface-temperature-analysis.gif","wide_image-width":624,"wide_image-height":351}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p><a href=\"https:\/\/huggingface.co\/ibm-nasa-geospatial\/Prithvi-100M\">Prithvi-100m<\/a> is a cutting-edge temporal ViT, now accessible as a foundation model within ArcGIS Pro. It is trained on extensive <a href=\"https:\/\/hls.gsfc.nasa.gov\/\">Harmonized Landsat and Sentinel-2 (HLS)<\/a> data. This model employs a self-supervised encoder built upon a ViT architecture and Masked AutoEncoder (MAE) learning paradigm. The model incorporates both spatial and temporal attention mechanisms to effectively process and analyze image data.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2585702,"id":2585702,"title":"ViT architecture + 3D Patch embedding + 3D positional encoding  source: https:\/\/huggingface.co\/ibm-nasa-geospatial\/Prithvi-100M on 9\/16\/2024","filename":"ViT-architecture-3D-Patch-embedding-3D-positional-encoding.png","filesize":478380,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ViT-architecture-3D-Patch-embedding-3D-positional-encoding.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4\/vit-architecture-3d-patch-embedding-3d-positional-encoding","alt":"ViT architecture + 3D Patch embedding + 3D positional encoding source: https:\/\/huggingface.co\/ibm-nasa-geospatial\/Prithvi-100M on 9\/16\/2024","author":"254042","description":"ViT architecture + 3D Patch embedding + 3D positional encoding \nsource: https:\/\/huggingface.co\/ibm-nasa-geospatial\/Prithvi-100M on 9\/16\/2024","caption":"ViT architecture + 3D Patch embedding + 3D positional encoding \nsource: https:\/\/huggingface.co\/ibm-nasa-geospatial\/Prithvi-100M on 9\/16\/2024","name":"vit-architecture-3d-patch-embedding-3d-positional-encoding","status":"inherit","uploaded_to":2585592,"date":"2024-11-14 19:12:05","modified":"2024-11-14 19:12:32","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1430,"height":555,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ViT-architecture-3D-Patch-embedding-3D-positional-encoding-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ViT-architecture-3D-Patch-embedding-3D-positional-encoding.png","medium-width":464,"medium-height":180,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ViT-architecture-3D-Patch-embedding-3D-positional-encoding.png","medium_large-width":768,"medium_large-height":298,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ViT-architecture-3D-Patch-embedding-3D-positional-encoding.png","large-width":1430,"large-height":555,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ViT-architecture-3D-Patch-embedding-3D-positional-encoding.png","1536x1536-width":1430,"1536x1536-height":555,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ViT-architecture-3D-Patch-embedding-3D-positional-encoding.png","2048x2048-width":1430,"2048x2048-height":555,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ViT-architecture-3D-Patch-embedding-3D-positional-encoding-826x321.png","card_image-width":826,"card_image-height":321,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/ViT-architecture-3D-Patch-embedding-3D-positional-encoding.png","wide_image-width":1430,"wide_image-height":555}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"image","image":{"ID":2585712,"id":2585712,"title":"An example output from the Prithvi-100M-sen1floods11 pretrained model by fine-tuning Prithvi-100m with the Sen1Floods11 dataset, in which the blue color represents floodwater","filename":"An-example-output-from-the-Prithvi-100M-sen1floods11-pretrained-model-by-fine-tuning-Prithvi-100m-with-the-Sen1Floods11-dataset-in-which-the-blue-color-represents-floodwater.png","filesize":406898,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-output-from-the-Prithvi-100M-sen1floods11-pretrained-model-by-fine-tuning-Prithvi-100m-with-the-Sen1Floods11-dataset-in-which-the-blue-color-represents-floodwater.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4\/an-example-output-from-the-prithvi-100m-sen1floods11-pretrained-model-by-fine-tuning-prithvi-100m-with-the-sen1floods11-dataset-in-which-the-blue-color-represents-floodwater","alt":"An example output from the Prithvi-100M-sen1floods11 pretrained model by fine-tuning Prithvi-100m with the Sen1Floods11 dataset, in which the blue color represents floodwater","author":"254042","description":"An example output from the Prithvi-100M-sen1floods11 pretrained model by fine-tuning Prithvi-100m with the Sen1Floods11 dataset, in which the blue color represents floodwater","caption":"An example output from the Prithvi-100M-sen1floods11 pretrained model by fine-tuning Prithvi-100m with the Sen1Floods11 dataset, in which the blue color represents floodwater","name":"an-example-output-from-the-prithvi-100m-sen1floods11-pretrained-model-by-fine-tuning-prithvi-100m-with-the-sen1floods11-dataset-in-which-the-blue-color-represents-floodwater","status":"inherit","uploaded_to":2585592,"date":"2024-11-14 19:13:36","modified":"2024-11-14 19:14:01","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":600,"height":400,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-output-from-the-Prithvi-100M-sen1floods11-pretrained-model-by-fine-tuning-Prithvi-100m-with-the-Sen1Floods11-dataset-in-which-the-blue-color-represents-floodwater-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-output-from-the-Prithvi-100M-sen1floods11-pretrained-model-by-fine-tuning-Prithvi-100m-with-the-Sen1Floods11-dataset-in-which-the-blue-color-represents-floodwater.png","medium-width":392,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-output-from-the-Prithvi-100M-sen1floods11-pretrained-model-by-fine-tuning-Prithvi-100m-with-the-Sen1Floods11-dataset-in-which-the-blue-color-represents-floodwater.png","medium_large-width":600,"medium_large-height":400,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-output-from-the-Prithvi-100M-sen1floods11-pretrained-model-by-fine-tuning-Prithvi-100m-with-the-Sen1Floods11-dataset-in-which-the-blue-color-represents-floodwater.png","large-width":600,"large-height":400,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-output-from-the-Prithvi-100M-sen1floods11-pretrained-model-by-fine-tuning-Prithvi-100m-with-the-Sen1Floods11-dataset-in-which-the-blue-color-represents-floodwater.png","1536x1536-width":600,"1536x1536-height":400,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-output-from-the-Prithvi-100M-sen1floods11-pretrained-model-by-fine-tuning-Prithvi-100m-with-the-Sen1Floods11-dataset-in-which-the-blue-color-represents-floodwater.png","2048x2048-width":600,"2048x2048-height":400,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-output-from-the-Prithvi-100M-sen1floods11-pretrained-model-by-fine-tuning-Prithvi-100m-with-the-Sen1Floods11-dataset-in-which-the-blue-color-represents-floodwater.png","card_image-width":600,"card_image-height":400,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-example-output-from-the-Prithvi-100M-sen1floods11-pretrained-model-by-fine-tuning-Prithvi-100m-with-the-Sen1Floods11-dataset-in-which-the-blue-color-represents-floodwater.png","wide_image-width":600,"wide_image-height":400}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<h2>Object detection on oriented imagery<\/h2>\n<p>Detecting features with <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/help\/data\/imagery\/oriented-imagery-overview.htm\">oriented imagery<\/a> data has been a challenge using deep learning. Now the <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/tool-reference\/image-analyst\/detect-objects-using-deep-learning.htm\">Detect Object Using Deep Learning<\/a> tool has been enhanced to accept oriented imagery datasets as input. The tool detects features within an oriented imagery dataset in pixel space and then projects them to map space.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2585722,"id":2585722,"title":"An oriented imagery dataset viewed in ArcGIS Pro with detected features","filename":"An-oriented-imagery-dataset-viewed-in-ArcGIS-Pro-with-detected-features.png","filesize":1344402,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-oriented-imagery-dataset-viewed-in-ArcGIS-Pro-with-detected-features.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4\/an-oriented-imagery-dataset-viewed-in-arcgis-pro-with-detected-features","alt":"An oriented imagery dataset viewed in ArcGIS Pro with detected features","author":"254042","description":"An oriented imagery dataset viewed in ArcGIS Pro with detected features","caption":"An oriented imagery dataset viewed in ArcGIS Pro with detected features","name":"an-oriented-imagery-dataset-viewed-in-arcgis-pro-with-detected-features","status":"inherit","uploaded_to":2585592,"date":"2024-11-14 19:17:07","modified":"2024-11-14 19:17:21","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1430,"height":848,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-oriented-imagery-dataset-viewed-in-ArcGIS-Pro-with-detected-features-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-oriented-imagery-dataset-viewed-in-ArcGIS-Pro-with-detected-features.png","medium-width":440,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-oriented-imagery-dataset-viewed-in-ArcGIS-Pro-with-detected-features.png","medium_large-width":768,"medium_large-height":455,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-oriented-imagery-dataset-viewed-in-ArcGIS-Pro-with-detected-features.png","large-width":1430,"large-height":848,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-oriented-imagery-dataset-viewed-in-ArcGIS-Pro-with-detected-features.png","1536x1536-width":1430,"1536x1536-height":848,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-oriented-imagery-dataset-viewed-in-ArcGIS-Pro-with-detected-features.png","2048x2048-width":1430,"2048x2048-height":848,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-oriented-imagery-dataset-viewed-in-ArcGIS-Pro-with-detected-features-784x465.png","card_image-width":784,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/An-oriented-imagery-dataset-viewed-in-ArcGIS-Pro-with-detected-features.png","wide_image-width":1430,"wide_image-height":848}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<h2>Feature extraction more accessible<\/h2>\n<p>Easily extract features from imagery with the <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/help\/analysis\/image-analyst\/feature-extraction.htm\">Extract Features<\/a> tool, which is now accessible from the <strong>Imagery<\/strong> tab. This powerful tool offers a variety of ready-to-use models, options to use your own custom models, and a range of inferencing and postprocessing options for enhanced output quality.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2592322,"id":2592322,"title":"The Extract Features tool is now accessible from the Imagery tab","filename":"extract-features.jpg","filesize":494636,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/extract-features.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4\/extract-features","alt":"The Extract Features tool is now accessible from the Imagery tab","author":"254042","description":"The Extract Features tool is now accessible from the Imagery tab","caption":"The Extract Features tool is now accessible from the Imagery tab","name":"extract-features","status":"inherit","uploaded_to":2585592,"date":"2024-11-18 22:34:18","modified":"2024-11-18 22:34:32","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1919,"height":1149,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/extract-features-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/extract-features.jpg","medium-width":436,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/extract-features.jpg","medium_large-width":768,"medium_large-height":460,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/extract-features.jpg","large-width":1804,"large-height":1080,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/extract-features-1536x920.jpg","1536x1536-width":1536,"1536x1536-height":920,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/extract-features.jpg","2048x2048-width":1919,"2048x2048-height":1149,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/extract-features-777x465.jpg","card_image-width":777,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/extract-features-1804x1080.jpg","wide_image-width":1804,"wide_image-height":1080}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<h2>Expand your analysis: append to existing outputs<\/h2>\n<p>The <strong>Detect Objects Using Deep Learning<\/strong> tool and the <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/tool-reference\/image-analyst\/classify-objects-using-deep-learning.htm\">Classify Objects Using Deep Learning<\/a> tool now support appending new results to existing output feature classes. This is useful when you&#8217;ve already processed one area and want to expand your analysis to adjacent regions. Simply run the tool again, and the new results will be added to the existing feature class.<\/p>\n<h2>Customize object detection: focus on what matters<\/h2>\n<p>When using the <strong>Detect Objects Using Deep Learning<\/strong> tool with models capable of identifying multiple object types, you can specify the exact objects of interest. This allows you to tailor the tool&#8217;s output to your needs and improve efficiency.<\/p>\n"}],"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/card.png","wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/banner-1.png","authors":[{"ID":254042,"user_firstname":"Pavan","user_lastname":"Yadav","nickname":"Pavan Yadav","user_nicename":"pyadav","display_name":"Pavan Yadav","user_email":"PYadav@esri.com","user_url":"","user_registered":"2021-07-20 16:55:01","user_description":"Pavan Yadav is a Senior Software Product Engineer at Esri's Imagery team, leveraging AI to extract valuable insights from imagery data and contributing to the development of geospatial AI (GeoAI).","user_avatar":"<img data-del=\"avatar\" src='https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/12\/Pavan-Yadav-213x200.jpg' class='avatar pp-user-avatar avatar-96 photo ' height='96' width='96'\/>"},{"ID":178852,"user_firstname":"Sangeet","user_lastname":"Mathew","nickname":"Sangeet Mathew","user_nicename":"smathew","display_name":"Sangeet Mathew","user_email":"smathew@esri.com","user_url":"","user_registered":"2021-02-11 16:40:56","user_description":"Principal Product Engineer on the Imagery team at Esri, with a focus on AI &amp; Image Analysis.","user_avatar":"<img data-del=\"avatar\" src='https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/12\/SngeetPic-213x200.jpg' class='avatar pp-user-avatar avatar-96 photo ' height='96' width='96'\/>"}],"related_articles":[{"ID":2318532,"post_author":"254042","post_date":"2024-05-09 00:01:49","post_date_gmt":"2024-05-09 07:01:49","post_content":"","post_title":"What's new for GeoAI in the Image Analyst extension of ArcGIS Pro 3.3","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-3","to_ping":"","pinged":"","post_modified":"2024-05-14 11:12:58","post_modified_gmt":"2024-05-14 18:12:58","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=2318532","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":2090062,"post_author":"254042","post_date":"2023-11-14 00:00:09","post_date_gmt":"2023-11-14 08:00:09","post_content":"","post_title":"Deep Learning for Image Analyst \u2013 What\u2019s New in ArcGIS Pro 3.2","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"deep-learning-for-image-analyst-whats-new-in-arcgis-pro-3-2","to_ping":"","pinged":"","post_modified":"2023-12-04 15:24:43","post_modified_gmt":"2023-12-04 23:24:43","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=2090062","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":1835002,"post_author":"254042","post_date":"2023-02-10 11:31:29","post_date_gmt":"2023-02-10 19:31:29","post_content":"","post_title":"What\u2019s new for deep learning in the Image Analyst extension of ArcGIS Pro 3.1","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"whats-new-for-deep-learning-in-the-image-analyst-extension-of-arcgis-pro-3-1","to_ping":"","pinged":"","post_modified":"2023-02-17 08:34:59","post_modified_gmt":"2023-02-17 16:34:59","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=1835002","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"1","filter":"raw"},{"ID":1302112,"post_author":"178852","post_date":"2021-08-02 11:56:22","post_date_gmt":"2021-08-02 18:56:22","post_content":"","post_title":"Performing Feature Extraction &amp; Classification Using Deep Learning with ArcGIS Pro","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"performing-feature-extraction-classification-using-deep-learning-with-arcgis-pro","to_ping":"","pinged":"","post_modified":"2022-08-25 13:59:34","post_modified_gmt":"2022-08-25 20:59:34","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=1302112","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"1","filter":"raw"},{"ID":1319782,"post_author":"254042","post_date":"2021-08-23 17:33:26","post_date_gmt":"2021-08-24 00:33:26","post_content":"","post_title":"Colorizing Historic Black and White Aerial Imagery using Deep Learning","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"colorizing-historic-black-and-white-aerial-imagery-using-deep-learning","to_ping":"","pinged":"","post_modified":"2022-01-13 15:04:59","post_modified_gmt":"2022-01-13 23:04:59","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=1319782","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":1956882,"post_author":"254042","post_date":"2023-06-14 06:00:09","post_date_gmt":"2023-06-14 13:00:09","post_content":"","post_title":"Repurposing Deep Learning Models using Transfer Learning in ArcGIS","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"repurposing-deep-learning-models-using-transfer-learning-in-arcgis","to_ping":"","pinged":"","post_modified":"2023-07-17 10:30:58","post_modified_gmt":"2023-07-17 17:30:58","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=1956882","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"3","filter":"raw"}],"show_article_image":true},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.9 (Yoast SEO v25.9) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Discover the Top Features of GeoAI for Imagery in ArcGIS Pro 3.4<\/title>\n<meta name=\"description\" content=\"Discover GeoAI advancements in ArcGIS Pro 3.4: enhanced training data, smarter labeling, new foundation models, and improved object detection\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What&#039;s new for GeoAI in the Image Analyst extension of ArcGIS Pro 3.4\" \/>\n<meta property=\"og:description\" content=\"Discover GeoAI advancements in ArcGIS Pro 3.4: enhanced training data, smarter labeling, new foundation models, and improved object detection\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4\" \/>\n<meta property=\"og:site_name\" content=\"ArcGIS Blog\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/esrigis\/\" \/>\n<meta property=\"article:modified_time\" content=\"2024-11-19T09:38:39+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@ESRI\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":[\"Article\",\"BlogPosting\"],\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4\"},\"author\":{\"name\":\"Pavan Yadav\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/person\/17827d4b26faea91d7d4c478ab8e5333\"},\"headline\":\"What&#8217;s new for GeoAI in the Image Analyst extension of ArcGIS Pro 3.4\",\"datePublished\":\"2024-11-19T08:01:50+00:00\",\"dateModified\":\"2024-11-19T09:38:39+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4\"},\"wordCount\":13,\"commentCount\":2,\"publisher\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#organization\"},\"keywords\":[\"AI\",\"Feature Extraction\",\"geoAI\",\"Imagery\",\"Object Detection\"],\"articleSection\":[\"AI\",\"Imagery &amp; Remote Sensing\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4\",\"url\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4\",\"name\":\"Discover the Top Features of GeoAI for Imagery in ArcGIS Pro 3.4\",\"isPartOf\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#website\"},\"datePublished\":\"2024-11-19T08:01:50+00:00\",\"dateModified\":\"2024-11-19T09:38:39+00:00\",\"description\":\"Discover GeoAI advancements in ArcGIS Pro 3.4: enhanced training data, smarter labeling, new foundation models, and improved object detection\",\"breadcrumb\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/www.esri.com\/arcgis-blog\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"What&#8217;s new for GeoAI in the Image Analyst extension of ArcGIS Pro 3.4\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#website\",\"url\":\"https:\/\/www.esri.com\/arcgis-blog\/\",\"name\":\"ArcGIS Blog\",\"description\":\"Get insider info from Esri product teams\",\"publisher\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/www.esri.com\/arcgis-blog\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#organization\",\"name\":\"Esri\",\"url\":\"https:\/\/www.esri.com\/arcgis-blog\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/04\/Esri.png\",\"contentUrl\":\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/04\/Esri.png\",\"width\":400,\"height\":400,\"caption\":\"Esri\"},\"image\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/logo\/image\/\"},\"sameAs\":[\"https:\/\/www.facebook.com\/esrigis\/\",\"https:\/\/x.com\/ESRI\",\"https:\/\/www.linkedin.com\/company\/5311\/\"]},{\"@type\":\"Person\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/person\/17827d4b26faea91d7d4c478ab8e5333\",\"name\":\"Pavan Yadav\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/12\/Pavan-Yadav-213x200.jpg\",\"contentUrl\":\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/12\/Pavan-Yadav-213x200.jpg\",\"caption\":\"Pavan Yadav\"},\"description\":\"Pavan Yadav is a Senior Software Product Engineer at Esri's Imagery team, leveraging AI to extract valuable insights from imagery data and contributing to the development of geospatial AI (GeoAI).\",\"sameAs\":[\"https:\/\/www.linkedin.com\/in\/pavan-yadav-1846606\/\"],\"url\":\"https:\/\/www.esri.com\/arcgis-blog\/author\/pyadav\"}]}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"Discover the Top Features of GeoAI for Imagery in ArcGIS Pro 3.4","description":"Discover GeoAI advancements in ArcGIS Pro 3.4: enhanced training data, smarter labeling, new foundation models, and improved object detection","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4","og_locale":"en_US","og_type":"article","og_title":"What's new for GeoAI in the Image Analyst extension of ArcGIS Pro 3.4","og_description":"Discover GeoAI advancements in ArcGIS Pro 3.4: enhanced training data, smarter labeling, new foundation models, and improved object detection","og_url":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4","og_site_name":"ArcGIS Blog","article_publisher":"https:\/\/www.facebook.com\/esrigis\/","article_modified_time":"2024-11-19T09:38:39+00:00","twitter_card":"summary_large_image","twitter_site":"@ESRI","twitter_misc":{"Est. reading time":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":["Article","BlogPosting"],"@id":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4#article","isPartOf":{"@id":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4"},"author":{"name":"Pavan Yadav","@id":"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/person\/17827d4b26faea91d7d4c478ab8e5333"},"headline":"What&#8217;s new for GeoAI in the Image Analyst extension of ArcGIS Pro 3.4","datePublished":"2024-11-19T08:01:50+00:00","dateModified":"2024-11-19T09:38:39+00:00","mainEntityOfPage":{"@id":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4"},"wordCount":13,"commentCount":2,"publisher":{"@id":"https:\/\/www.esri.com\/arcgis-blog\/#organization"},"keywords":["AI","Feature Extraction","geoAI","Imagery","Object Detection"],"articleSection":["AI","Imagery &amp; Remote Sensing"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4#respond"]}]},{"@type":"WebPage","@id":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4","url":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4","name":"Discover the Top Features of GeoAI for Imagery in ArcGIS Pro 3.4","isPartOf":{"@id":"https:\/\/www.esri.com\/arcgis-blog\/#website"},"datePublished":"2024-11-19T08:01:50+00:00","dateModified":"2024-11-19T09:38:39+00:00","description":"Discover GeoAI advancements in ArcGIS Pro 3.4: enhanced training data, smarter labeling, new foundation models, and improved object detection","breadcrumb":{"@id":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.esri.com\/arcgis-blog\/"},{"@type":"ListItem","position":2,"name":"What&#8217;s new for GeoAI in the Image Analyst extension of ArcGIS Pro 3.4"}]},{"@type":"WebSite","@id":"https:\/\/www.esri.com\/arcgis-blog\/#website","url":"https:\/\/www.esri.com\/arcgis-blog\/","name":"ArcGIS Blog","description":"Get insider info from Esri product teams","publisher":{"@id":"https:\/\/www.esri.com\/arcgis-blog\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.esri.com\/arcgis-blog\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/www.esri.com\/arcgis-blog\/#organization","name":"Esri","url":"https:\/\/www.esri.com\/arcgis-blog\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/logo\/image\/","url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/04\/Esri.png","contentUrl":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/04\/Esri.png","width":400,"height":400,"caption":"Esri"},"image":{"@id":"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/esrigis\/","https:\/\/x.com\/ESRI","https:\/\/www.linkedin.com\/company\/5311\/"]},{"@type":"Person","@id":"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/person\/17827d4b26faea91d7d4c478ab8e5333","name":"Pavan Yadav","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/person\/image\/","url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/12\/Pavan-Yadav-213x200.jpg","contentUrl":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/12\/Pavan-Yadav-213x200.jpg","caption":"Pavan Yadav"},"description":"Pavan Yadav is a Senior Software Product Engineer at Esri's Imagery team, leveraging AI to extract valuable insights from imagery data and contributing to the development of geospatial AI (GeoAI).","sameAs":["https:\/\/www.linkedin.com\/in\/pavan-yadav-1846606\/"],"url":"https:\/\/www.esri.com\/arcgis-blog\/author\/pyadav"}]}},"text_date":"November 19, 2024","author_name":"Multiple Authors","author_page":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/whats-new-for-geoai-in-the-image-analyst-extension-of-arcgis-pro-3-4","custom_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/banner-1.png","primary_product":"ArcGIS Pro","tag_data":[{"term_id":758311,"name":"AI","slug":"ai","term_group":0,"term_taxonomy_id":758311,"taxonomy":"post_tag","description":"","parent":0,"count":29,"filter":"raw"},{"term_id":777362,"name":"Feature Extraction","slug":"feature-extraction","term_group":0,"term_taxonomy_id":777362,"taxonomy":"post_tag","description":"","parent":0,"count":3,"filter":"raw"},{"term_id":665211,"name":"geoAI","slug":"geoai","term_group":0,"term_taxonomy_id":665211,"taxonomy":"post_tag","description":"","parent":0,"count":36,"filter":"raw"},{"term_id":115262,"name":"Imagery","slug":"imagery","term_group":0,"term_taxonomy_id":115262,"taxonomy":"post_tag","description":"","parent":0,"count":153,"filter":"raw"},{"term_id":515302,"name":"Object Detection","slug":"object-detection","term_group":0,"term_taxonomy_id":515302,"taxonomy":"post_tag","description":"","parent":0,"count":10,"filter":"raw"}],"category_data":[{"term_id":770712,"name":"AI","slug":"geoai","term_group":0,"term_taxonomy_id":770712,"taxonomy":"category","description":"","parent":0,"count":51,"filter":"raw"},{"term_id":22931,"name":"Imagery &amp; Remote Sensing","slug":"imagery","term_group":0,"term_taxonomy_id":22931,"taxonomy":"category","description":"","parent":0,"count":768,"filter":"raw"}],"product_data":[{"term_id":36561,"name":"ArcGIS Pro","slug":"arcgis-pro","term_group":0,"term_taxonomy_id":36561,"taxonomy":"product","description":"","parent":0,"count":2039,"filter":"raw"}],"primary_product_link":"https:\/\/www.esri.com\/arcgis-blog\/?s=#&products=arcgis-pro","_links":{"self":[{"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/blog\/2585592","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/blog"}],"about":[{"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/types\/blog"}],"author":[{"embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/users\/254042"}],"replies":[{"embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/comments?post=2585592"}],"version-history":[{"count":0,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/blog\/2585592\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/media?parent=2585592"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/categories?post=2585592"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/tags?post=2585592"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/industry?post=2585592"},{"taxonomy":"product","embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/product?post=2585592"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}