The size of the Italy Geospatial Analytics market was valued at USD XXX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 8.17% during the forecast period. Recent developments include: March 2023: The Italian space agency and NASA have collaborated to build and launch the Multi-Angle Imager for Aerosols mission, an effort to investigate the health impacts of tiny airborne particles polluting the cities through analyzing data by collecting data from the satellite-based observatories, which would fuel the demand for geospatial analytics market in the country., January 2023: EDB, an open-source database service provider in Italy, announced its partnership with Esri to certify EDB Postgres Advanced Server with Esri ArcGIS Pro and Esri ArcGIS Enterprise, which work together to form Esri's Geospatial analytic solutions, operating in many countries, including Italy. After this partnership, users can connect their EDB Postgres Advanced Server to explore, visualize and analyze their geospatial data and share their work with an Esri ArcGIS Enterprise portal. In addition, EDB customers, especially those in the public sector, can use their database with Esri ArcGIS software to transform their data into something that improves workflows and processes and shapes policies and engagement within their communities.. Key drivers for this market are: Increase in the number of Smart Cities in The Country, The Implementation of analytics Software in the Country's Public Transportation. Potential restraints include: High Costs and Operational Concerns, Lack of Standardization for Data Integration. Notable trends are: The Increase in the Number of Smart Cities in The Country Fuels the Market Growth.

This resource was created by Esri Canada Education and Research. To browse our full collection of higher-education learning resources, please visit https://hed.esri.ca/resourcefinder/.This tutorial introduces you to using Python code in a Jupyter Notebook, an open source web application that enables you to create and share documents that contain rich text, equations and multimedia, alongside executable code and visualization of analysis outputs. The tutorial begins by stepping through the basics of setting up and being productive with Python notebooks. You will be introduced to ArcGIS Notebooks, which are Python Notebooks that are well-integrated within the ArcGIS platform. Finally, you will be guided through a series of ArcGIS Notebooks that illustrate how to create compelling notebooks for data science that integrate your own Python scripts using the ArcGIS API for Python and ArcPy in combination with thousands of open source Python libraries to enhance your analysis and visualization.To download the dataset Labs, click the Open button to the top right. This will automatically download a ZIP file containing all files and data required.You can also clone the tutorial documents and datasets for this GitHub repo: https://github.com/highered-esricanada/arcgis-notebooks-tutorial.git.Software & Solutions Used: Required: This tutorial was last tested on August 27th, 2024, using ArcGIS Pro 3.3. If you're using a different version of ArcGIS Pro, you may encounter different functionality and results.Recommended: ArcGIS Online subscription account with permissions to use advanced Notebooks and GeoEnrichmentOptional: Notebook Server for ArcGIS Enterprise 11.3+Time to Complete: 2 h (excludes processing time)File Size: 196 MBDate Created: January 2022Last Updated: August 27, 2024

This deep learning model is used to detect trees in low-resolution drone or aerial imagery. Tree detection can be used for applications such as vegetation management, forestry, urban planning, etc. High resolution aerial and drone imagery can be used for tree detection due to its high spatio-temporal coverage.

This deep learning model is based on MaskRCNN and has been trained on data from the DM Dataset preprocessed and collected by the IST Team.

There is no need of high-resolution imagery you can perform all your analysis on low resolution imagery by detecting the trees with the accuracy of 75% and finetune the model to increase your performance and train on your own data.

Licensing requirements ArcGIS Desktop – ArcGIS Image Analyst and ArcGIS 3D Analyst extensions for ArcGIS Pro ArcGIS Enterprise – ArcGIS Image Server with raster analytics configured ArcGIS Online – ArcGIS Image for ArcGIS Online

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.

Note: Deep learning is computationally intensive, and a powerful GPU is recommended to process large datasets.

Input 3-band low-resolution (70 cm) satellite imagery.

Output Feature class containing detected trees

Applicable geographies The model is expected to work well in the U.A.E.

Model architecture This model is based upon the MaskRCNN python package and uses the Resnet-152 model architecture implemented in pytorch.

Training data This model has been trained on the Satellite Imagery created and Labelled by the team and validated on the different locations with more diverse locations.

Accuracy metrics This model has an average precision score of 0.45.

Sample results Here are a few results from the model.

The way to access Layers Quickly.

Quick Layers is an Add-In for ArcGIS Pro 3 that allows rapid access to the DNR's Geospatial Data Resource Site (GDRS). The GDRS is a data structure that serves core geospatial dataset and applications for not only DNR, but many state agencies, and supports the Minnesota Geospatial Commons. Data added from Quick Layers is pre-symbolized, helping to standardize visualization and map production. Current version: 3.11

To use Quick Layers with the GDRS, there's no need to download QuickLayers from this location. Instead, download a full copy or a custom subset of the public GDRS (including Quick Layers for ArcGIS Pro 3) using GDRS Manager.

Quick Layers also allows users to save and share their own pre-symbolized layers, thus increasing efficiency and consistency across the enterprise.

Installation:

After using GDRS Manager to create a GDRS, including Quick Layers, add the path to the Quick Layers addin to the list of shared folders:
1. Open ArcGIS Pro
2. Project -> Add-In Manager -> Options
3. Click add folder, and enter the location of the Quick Layers Pro app. For example, if your GDRS is mapped to the V drive, the path would be V:\gdrs\apps\pub\us_mn_state_dnr\quick_layers_pro3
4. After you do this, the Quick Layers ribbon will be available. To also add Quick Layers to the Quick Access Toolbar at the top, right click Quick Layers, and select Add to Quick Access Toolbar

The link below is only for those who are using Quick Layers without a GDRS. To get the most functionality out of Quick Layers, don't install it separately, but instead download it as part of a GDRS build using GDRS Manager.

This template is used to compute urban growth between two land cover datasets, that are classified into 20 classes based on the Anderson Level II classification system. This raster function template is used to generate a visual representation indicating urbanization across two different time periods. Typical datasets used for this template is the National Land Cover Database. A more detailed blog on the datasets can be found on ArcGIS Blogs. This template works in ArcGIS Pro Version 2.6 and higher. It's designed to work on Enterprise 10.8.1 and higher.References:Raster functionsWhen to use this raster function templateThe template is useful to generate an intuitive visualization of urbanization across two images.Sample Images to test this againstNLCD2006 and NLCD2011How to use this raster function templateIn ArcGIS Pro, search ArcGIS Living Atlas for raster function templates to apply them to your imagery layer. You can also download the raster function template, attach it to a mosaic dataset, and publish it as an image service. The output is a visual representation of urban sprawl across two images. Applicable geographiesThe template is designed to work globally.

ArcGIS Pro ist eine professionelle Desktop-GIS-Anwendung von Esri mit vollem Funktionsumfang. Mit ArcGIS Pro können Sie Daten erkunden, visualisieren und analysieren, 2D-Karten und 3D-Szenen erstellen sowie Ihre Arbeit im ArcGIS Online- oder ArcGIS Enterprise-Portal freigeben. In den folgenden Abschnitten werden der Anmeldevorgang, die Startseite, ArcGIS Pro-Projekte und die Bedienoberfläche vorgestellt. https://pro.arcgis.com/de/pro-app/latest/get-started/get-started.htm

The National Forest Climate Change Maps project was developed to meet the need of National Forest managers for information on projected climate changes at a scale relevant to decision making processes, including Forest Plans. The maps use state-of-the-art science and are available for every National Forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation and air temperature, including both Alaskan and lower 48 datasets. Data from the lower 48 were downloaded from here: https://www.fs.usda.gov/rm/boise/AWAE/projects/national-forest-climate-change-maps.html, and Alaskan data came from here: https://www.snap.uaf.edu/tools/data-downloads. Historical data are compared with RCP 8.5 projections from the 2080s.A Raster Function Template is available in this service that will classify the data as originally intended by OSC. The RFT currently works in AGOL but not in ArcGIS Pro.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

The National Forest Climate Change Maps project was developed to meet the need of National Forest managers for information on projected climate changes at a scale relevant to decision making processes, including Forest Plans. The maps use state-of-the-art science and are available for every National Forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation and air temperature, including both Alaskan and lower 48 datasets. Data from the lower 48 were downloaded from here: https://www.fs.usda.gov/rm/boise/AWAE/projects/national-forest-climate-change-maps.html, and Alaskan data came from here: https://www.snap.uaf.edu/tools/data-downloads. Historical data are compared with RCP 8.5 projections from the 2080s.A Raster Function Template is available in this service that will classify the data as originally intended by OSC. The RFT currently works in AGOL but not in ArcGIS Pro.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

The National Forest Climate Change Maps project was developed to meet the need of National Forest managers for information on projected climate changes at a scale relevant to decision making processes, including Forest Plans. The maps use state-of-the-art science and are available for every National Forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation and air temperature, including both Alaskan and lower 48 datasets. Data from the lower 48 were downloaded from here: https://www.fs.usda.gov/rm/boise/AWAE/projects/national-forest-climate-change-maps.html, and Alaskan data came from here: https://www.snap.uaf.edu/tools/data-downloads. Historical data are compared with RCP 8.5 projections from the 2080s.A Raster Function Template is available in this service that will classify the data as originally intended by OSC. The RFT currently works in AGOL but not in ArcGIS Pro.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

Intended for searching and web map display in Portal web maps and web applications or in ArcGIS Pro. Source of feature class that published this web service is from enterprise geodatabase. Key words are standardized for ArcGIS Pro users to be able to search through the County's Geo Portal web services without being logged in.

The National Forest Climate Change Maps project was developed to meet the need of National Forest managers for information on projected climate changes at a scale relevant to decision making processes, including Forest Plans. The maps use state-of-the-art science and are available for every National Forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation and air temperature, including both Alaskan and lower 48 datasets. Data from the lower 48 were downloaded from here: https://www.fs.usda.gov/rm/boise/AWAE/projects/national-forest-climate-change-maps.html, and Alaskan data came from here: https://www.snap.uaf.edu/tools/data-downloads. Historical data are compared with RCP 8.5 projections from the 2080s.A Raster Function Template is available in this service that will classify the data as originally intended by OSC. The RFT currently works in AGOL but not in ArcGIS Pro.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

Discover the booming Italian Geospatial Analytics market! Explore its €260 million (2025) valuation, 8.17% CAGR, key drivers, trends, and leading players like ESRI and Hexagon AB. This in-depth analysis projects market growth through 2033 across sectors including agriculture, defense, and utilities. Recent developments include: March 2023: The Italian space agency and NASA have collaborated to build and launch the Multi-Angle Imager for Aerosols mission, an effort to investigate the health impacts of tiny airborne particles polluting the cities through analyzing data by collecting data from the satellite-based observatories, which would fuel the demand for geospatial analytics market in the country., January 2023: EDB, an open-source database service provider in Italy, announced its partnership with Esri to certify EDB Postgres Advanced Server with Esri ArcGIS Pro and Esri ArcGIS Enterprise, which work together to form Esri's Geospatial analytic solutions, operating in many countries, including Italy. After this partnership, users can connect their EDB Postgres Advanced Server to explore, visualize and analyze their geospatial data and share their work with an Esri ArcGIS Enterprise portal. In addition, EDB customers, especially those in the public sector, can use their database with Esri ArcGIS software to transform their data into something that improves workflows and processes and shapes policies and engagement within their communities.. Key drivers for this market are: Increase in the number of Smart Cities in The Country, The Implementation of analytics Software in the Country's Public Transportation. Potential restraints include: Increase in the number of Smart Cities in The Country, The Implementation of analytics Software in the Country's Public Transportation. Notable trends are: The Increase in the Number of Smart Cities in The Country Fuels the Market Growth.

Shapefile of the Salt Lake or Bidhannagar's administrative boundary only for the residential area. The shapefile was created with QGIS and Google Earth. Verified on ArcGIS Pro (Enterprise). Kolkata's (KMDA) administrative boundary does not contain elite Bidhannagar. It is under a different local administration unit. This shapefile is not covering Sector V zonal distribution.

Intended for web map display in Portal web maps, ArcGIS Online, web applications, and use in ArcGIS Pro. Source of feature class is yavgis.MISSDEADM.Tracts from the production enterprise database. Published in Central AZ State Plane Coordinate System. No definition queries. Visibility range is 1:500,000.

The National Forest Climate Change Maps project was developed to meet the need of National Forest managers for information on projected climate changes at a scale relevant to decision making processes, including Forest Plans. The maps use state-of-the-art science and are available for every National Forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation and air temperature, including both Alaskan and lower 48 datasets. Data from the lower 48 were downloaded from here: https://www.fs.usda.gov/rm/boise/AWAE/projects/national-forest-climate-change-maps.html, and Alaskan data came from here: https://www.snap.uaf.edu/tools/data-downloads. Historical data are compared with RCP 8.5 projections from the 2080s.A Raster Function Template is available in this service that will classify the data as originally intended by OSC. The RFT currently works in AGOL but not in ArcGIS Pro.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

Intended for web map display in Portal web maps, web applications, and use in ArcGIS Pro. Source of feature class is yavgis.MISSDEADM.Townships from the production enterprise database. Published in Central AZ State Plane Coordinate System. No definition queries. Visibility range is 1:2,000,000.

This dataset consists of topographic features across the East Antarctic coastal region, extending from 33°E to 168°E and from the coast inland to approximately 84°S in some areas.

The features were digitised using ArcGIS Pro and were created within a topology to ensure the spatial integrity of the data. Line data include coastlines, ice fronts and grounding lines. Polygon data include continent features, islands, ice shelfs, ice tongues, icebergs, rocks and lakes.

The features were digitised at a scale of 1:25,000 using Sentinel2 imagery: earthexplorer.usgs.gov, 'Copernicus Sentinel data [2023]'. Note: Individual Sentinel 2 data source images are referenced in the data attribute tables with the exception of the coastline polygon dataset which was derived from the coastline line dataset.

Grounding lines were derived from ASAID_Grounding_line_continent_Sc_dep : Rignot, E., J. Mouginot, and B. Scheuchl. 2016. MEaSUREs Antarctic Grounding Line from Differential Satellite Radar Interferometry, Version 2. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://nsidc.org/data/nsidc-0498/versions/2

The ASAID data were edited using ICESat2 data: Derived Grounding Zone for Antarctic Ice Shelves, United States Antarctic Program Data Center (USAP-DC) www.usap-dc.org ; http://www.usap-dc.org/view/dataset/609469 as well as Sentinel2 imagery and The Reference Elevation Model of Antarctica version 2 (REMA 2): Howat, I. M., Porter, C., Smith, B. E., Noh, M.-J., and Morin, P., The Reference Elevation Model of Antarctica, The Cryosphere, 13, 665-674, https://doi.org/10.5194/tc-13-665-2019 , 2019 DEM(s) courtesy of the Polar Geospatial Center.

The Antarctic Iceberg Data were sourced from U.S.National Ice Centre (usicecenter.gov/Products/AntarcIcebergs) in CSV format. The CSV data used in this project is dated 3 Feb 2023. The point data were used to locate and digitise icebergs using Sentinel 2 imagery at a scale of 1:25000.

The 25K topographic features are stored in the Australian Antarctic Division Enterprise GIS and are available for download using the provided links.

The National Forest Climate Change Maps project was developed to meet the need of National Forest managers for information on projected climate changes at a scale relevant to decision making processes, including Forest Plans. The maps use state-of-the-art science and are available for every National Forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation and air temperature, including both Alaskan and lower 48 datasets. Data from the lower 48 were downloaded from here: https://www.fs.usda.gov/rm/boise/AWAE/projects/national-forest-climate-change-maps.html, and Alaskan data came from here: https://www.snap.uaf.edu/tools/data-downloads. Historical data are compared with RCP 8.5 projections from the 2080s.A Raster Function Template is available in this service that will classify the data as originally intended by OSC. The RFT currently works in AGOL but not in ArcGIS Pro.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

This dataset consists of 100-metre-interval contour lines across East Antarctica. The contours are derived from the REMA 2 (Reference Elevation Model of Antarctica version 2) 10-metre mosaic digital elevation model. Features were produced using the ArcGIS Pro 'Generate Topographic Contours' tool with a Raster Smooth Tolerance of 0.6, a Contour Minimum Length of 300 metres, and a Contour Smooth Tolerance of 150 metres based on an output map scale of 1:1 million. Contour generation was limited to a source mosaic tile set extending from the from approximately 31°E to 177°E and from the coast inland to approximately 76°S. The contours were edited to remove holes present in the source DEM and some shorter-length contours were manually removed to improve clarity. This data is stored in the AAD's relief ln enterprise dataset.

The National Forest Climate Change Maps project was developed to meet the need of National Forest managers for information on projected climate changes at a scale relevant to decision making processes, including Forest Plans. The maps use state-of-the-art science and are available for every National Forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation and air temperature, including both Alaskan and lower 48 datasets. Data from the lower 48 were downloaded from here: https://www.fs.usda.gov/rm/boise/AWAE/projects/national-forest-climate-change-maps.html, and Alaskan data came from here: https://www.snap.uaf.edu/tools/data-downloads. Historical data are compared with RCP 8.5 projections from the 2080s.A Raster Function Template is available in this service that will classify the data as originally intended by OSC. The RFT currently works in AGOL but not in ArcGIS Pro.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.