In this seminar, the presenters will introduce essential concepts of Collector for ArcGIS and show how this app integrates with other components of the ArcGIS platform to provide a seamless data management workflow. You will also learn how anyone in your organization can easily capture and update data in the field, right from their smartphone or tablet.This seminar was developed to support the following:ArcGIS Desktop 10.2.2 (Basic)ArcGIS OnlineCollector for ArcGIS (Android) 10.4Collector for ArcGIS (iOS) 10.4Collector for ArcGIS (Windows) 10.4

This is a video demonstrating how to connect Collector for ArcGIS to an external GNSS receiver.Steps:Connect your mobile device to the external GNSS receiver using bluetooth.Once the connection is successful, open an ArcGIS mobile app for field data collection (e.g., Collector for ArcGIS).Go to Settings, and look for Location setting.Press "Provider", click the add ("+") button, and choose the appropriate external GNSS receiver.You can specify the antenna height, if applicable, and then press "Done".The Collector for ArcGIS can now be used to collect field data by utilising the connected external GNSS receiver.Credits: Anatum GeoMobile Solutions

This database was designed in response to the Director Memorandum - "Effective January 1, 2019 all structure greater than 120 square feet in the State Responsibility Area (SRA) damaged by wildfire will be inspected and documented in the DINS Collector App."To document and structure damaged or destroyed by the McKinney wildland fire open the associated Field Map app.NOTE - this feature service is configured to not allow record deletion. If a record needs to be deleted contact the program manager below.This is the schema developed and used by the CAL FIRE Office of State Fire Marshal to assess and record structure damage on wildland fire incidents. The schema is designed to be configured in the Esri Collector/Field Maps app for data collection during or after an incident.

This database was designed in response to the Director Memorandum - "Effective January 1, 2019 all structure greater than 120 square feet in the State Responsibility Area (SRA) damaged by wildfire will be inspected and documented in the DINS Collector App."To document and structure damaged or destroyed by the Oak wildland fire open the associated Field Map app.NOTE - this feature service is configured to not allow record deletion. If a record needs to be deleted contact the program manager below.This is the schema developed and used by the CAL FIRE Office of State Fire Marshal to assess and record structure damage on wildland fire incidents. The schema is designed to be configured in the Esri Collector/Field Maps app for data collection during or after an incident.

This database was designed in response to the Director Memorandum - "Effective January 1, 2019 all structure greater than 120 square feet in the State Responsibility Area (SRA) damaged by wildfire will be inspected and documented in the DINS Collector App."To document structures damaged or destroyed by the 2023 Pineapple Express flooding in Monterey County open the associated Field Map app.NOTE - this feature service is configured to not allow record deletion. If a record needs to be deleted contact the program manager below.This is the schema developed and used by the CAL FIRE Office of State Fire Marshal to assess and record structure damage on flooding incidents. The schema is designed to be configured in the Esri Collector/Field Maps app for data collection during or after an incident.

This database was designed in response to the Director Memorandum - "Effective January 1, 2019 all structure greater than 120 square feet in the State Responsibility Area (SRA) damaged by wildfire will be inspected and documented in the DINS Collector App."To document and structure damaged or destroyed by the Mill wildland fire open the associated Field Map app.NOTE - this feature service is configured to not allow record deletion. If a record needs to be deleted contact the program manager below.This is the schema developed and used by the CAL FIRE Office of State Fire Marshal to assess and record structure damage on wildland fire incidents. The schema is designed to be configured in the Esri Collector/Field Maps app for data collection during or after an incident.

Use the Attachment Viewer template to provide an app for users to explore a layer's features and review attachments with the option to update attribute data. Present your images, videos, and PDF files collected using ArcGIS Field Maps or ArcGIS Survey123 workflows. Choose an attachment-focused layout to display individual images beside your map or a map-focused layout to highlight your map next to a gallery of images. Examples: Review photos collected during emergency response damage inspections. Display the results of field data collection and support downloading images for inclusion in a report. Present a map of land parcel along with associated documents stored as attachments. Data requirements The Attachment Viewer template requires a feature layer with attachments. It includes the capability to view attachments of a hosted feature service or an ArcGIS Server feature service (10.8 or later). Currently, the app can display JPEG, JPG, PNG, GIF, MP4, QuickTime (.mov), and PDF files in the viewer window. All other attachment types are displayed as a link. Key app capabilities App layout - Choose between an attachment-focused layout, which displays one attachment at a time in the main panel of the app with the map on the side, or a map-focused layout, which displays the map in the main panel of the app with a gallery of attachments. Feature selection - Allows users to select features in the map and view associated attachments. Review data - Enable tools to review and update existing records. Zoom, pan, download images - Allow users to interact with and download attachments. Language switcher - Provide translations for custom text and create a multilingual app. Home, Zoom controls, Legend, Layer List, Search Supportability This web app is designed responsively to be used in browsers on desktops, mobile phones, and tablets. We are committed to ongoing efforts towards making our apps as accessible as possible. Please feel free to leave a comment on how we can improve the accessibility of our apps for those who use assistive technologies.

This database was designed in response to the Director Memorandum - "Effective January 1, 2019 all structure greater than 120 square feet in the State Responsibility Area (SRA) damaged by wildfire will be inspected and documented in the DINS Collector App."To document and structure damaged or destroyed by the Mosquito wildland fire open the associated Field Map app.NOTE - this feature service is configured to not allow record deletion. If a record needs to be deleted contact the program manager below.This is the schema developed and used by the CAL FIRE Office of State Fire Marshal to assess and record structure damage on wildland fire incidents. The schema is designed to be configured in the Esri Collector/Field Maps app for data collection during or after an incident.

This database was designed in response to the Director Memorandum - "Effective January 1, 2019 all structure greater than 120 square feet in the State Responsibility Area (SRA) damaged by wildfire will be inspected and documented in the DINS Collector App."To document and structure damaged or destroyed by the 2023 Tulare Flooding Incident open the associated Field Map app.NOTE - this feature service is configured to not allow record deletion. If a record needs to be deleted contact the program manager below.This is the schema developed and used by the CAL FIRE Office of State Fire Marshal to assess and record structure damage on flooding incidents. The schema is designed to be configured in the Esri Collector/Field Maps app for data collection during or after an incident.

The global field data collection software market is experiencing robust growth, driven by the increasing need for efficient data management across diverse sectors. The market's expansion is fueled by several key factors: the rising adoption of mobile technologies and cloud-based solutions for improved data accessibility and real-time analysis; the increasing demand for automation in data collection processes to reduce manual errors and improve productivity; and the growing emphasis on data-driven decision-making across industries such as construction, environmental monitoring, and oil and gas. This shift towards digitalization is transforming traditional fieldwork practices, leading to enhanced accuracy, reduced operational costs, and improved overall efficiency. We estimate the market size in 2025 to be approximately $2.5 billion, with a Compound Annual Growth Rate (CAGR) of 15% projected through 2033. This growth is expected to be further fueled by advancements in AI and machine learning, which enhance data analysis capabilities and provide valuable insights from collected field data. While challenges remain, including concerns regarding data security and integration with existing systems, the overall market outlook remains positive, with significant opportunities for software vendors and service providers. The market segmentation reveals significant opportunities across various applications and deployment types. The cloud-based segment is experiencing the fastest growth, driven by its scalability, accessibility, and cost-effectiveness. The construction, environmental monitoring, and oil and gas sectors are major consumers of field data collection software, demonstrating a strong demand for solutions that streamline workflows, enhance safety protocols, and optimize resource allocation. Geographic analysis suggests North America and Europe are currently the largest markets, although the Asia-Pacific region is expected to witness substantial growth in the coming years due to increasing infrastructure development and industrialization. The competitive landscape is dynamic, with both established players and emerging startups offering specialized solutions. The success of these companies hinges on their ability to provide robust, user-friendly software with strong integration capabilities and advanced analytical features.

The global market for GIS Collectors is experiencing robust growth, driven by increasing adoption of location-based services, the expanding need for precise geospatial data across various sectors, and the continuous advancements in mobile technology and data analytics capabilities. The market is segmented by hardware (handheld devices, tablets, drones) and software (field data collection apps, data management software). Key players like Hexagon, Trimble Geospatial, ESRI, Topcon, Handheld, and Wuhan South are actively innovating and expanding their product portfolios to cater to this growing demand. The market's expansion is further fueled by the rising need for efficient asset management, improved infrastructure planning, and precise mapping for various applications such as environmental monitoring, agriculture, and urban planning. Government initiatives promoting digitalization and smart city development are also contributing significantly to the market's growth trajectory. While high initial investment costs for hardware and software can act as a restraint, the long-term benefits in terms of operational efficiency and data accuracy are overcoming this challenge. We project a steady market growth over the forecast period, with a particular emphasis on the increasing penetration of cloud-based solutions and the integration of AI and machine learning for enhanced data processing and analysis. The period between 2019 and 2024 showed significant market expansion, setting a strong foundation for future growth. We estimate the market size in 2025 at $5 billion, based on observed trends and industry reports. This strong base, coupled with a projected Compound Annual Growth Rate (CAGR) of 12%, will drive considerable market expansion throughout the forecast period (2025-2033). The increasing demand across diverse sectors, from precision agriculture to utility management, will continue to be major drivers. Furthermore, the emergence of new technologies such as 5G and IoT will further enhance data collection and processing capabilities, leading to improved efficiencies and a further expansion of the market. The North American and European markets currently hold a significant share, but emerging economies in Asia-Pacific and Latin America are exhibiting accelerated growth potential, making them crucial regions for future expansion.

The global urban planning app market, valued at $76.9 million in 2025, is projected to experience robust growth, driven by the increasing need for efficient city management and sustainable urban development. A compound annual growth rate (CAGR) of 7.3% is anticipated from 2025 to 2033, indicating a significant expansion of this sector. This growth is fueled by several key factors. The rising adoption of mobile technologies among urban planners and municipalities accelerates the shift towards digital solutions for tasks like zoning, infrastructure planning, and community engagement. Furthermore, the increasing availability of geospatial data and improved mapping technologies empower more sophisticated and data-driven urban planning. Government initiatives promoting smart cities and sustainable urban development further bolster market growth. The market is segmented by application (large enterprises and SMEs) and type (iOS and Android), with large enterprises currently dominating due to their higher investment capacity in sophisticated software solutions. The competitive landscape is dynamic, featuring established players like Autodesk (AutoCAD 360) and Esri (ArcGIS Collector) alongside innovative startups providing specialized solutions. Regional growth is expected to be diverse, with North America and Europe leading initially due to higher technology adoption and existing infrastructure, while Asia-Pacific is poised for significant growth in the coming years, driven by rapid urbanization and infrastructure development in countries like China and India. The market's restraints primarily involve the high initial investment costs associated with implementing and integrating these applications, particularly for smaller municipalities and developing nations. Data security and privacy concerns also represent a significant hurdle, particularly when handling sensitive urban planning data. However, the increasing affordability of cloud-based solutions and advancements in data encryption are mitigating these concerns. The trend toward integrating artificial intelligence (AI) and machine learning (ML) into urban planning apps is likely to transform the sector. AI-powered features will enhance prediction capabilities for urban development challenges like traffic congestion, resource allocation, and environmental impact assessment, further fueling market expansion. The ongoing development of 3D modeling and visualization tools within these apps provides a more realistic and accessible means for urban planners to communicate complex plans to stakeholders and the public, resulting in better community engagement.

This data set contains the trails data that is published for public consumption. It includes hiking, biking, and multi-use trails in Lake County, plus several connecting trails in surrounding counties. Data identifies the location of the trails, the trail name, surface type, trail use, its status within the county's Trails Master Plan, and other details.Local Lake County data is collected in the field using the Collector app. Data from other sources - including FWC, and other counties - was received from those sources with no additional checking. Data is updated as needed and new trails are added as acquired.Contact Lake County Office of Parks and Trails for additional details.

This is a dataset of _location and photo data for the debris flow deposits measured in the Tadpole Wildfire. The data were collected using the ArcGIS Collector application by multiple individuals. The original data are stored in a geodatabase here, and the geodatabase has the following fields: Latitude (decimal degrees), Longitude (decimal degrees), Elevation (meters), GlobalID (a unique ID), CreationDate, Creator, EditDate, Editor, and Notes. Each point in the geodatabase represents an observation (either a debris flow deposit or a wood measurement), and most points also include associated photos of the deposit/wood. An opensource version of the geodatabase is provided as a shapefile, containing the same fields mentioned above. The photos associated with each point are in a separate folder in this data release, and the file called photo_table.csv contains the GlobalIDs and photo names that correspond to each _location in the shapefile.

This is a training dataset for the ArcGIS Collector application. This training will be held August 24, 2017.

Crowdsource Manager is a configurable group app template that can be used for triaging crowd sourced data across multiple layers and maps as it is collected using applications such as Crowdsource Reporter or Collector. Using Crowdsource Manager, these reports can be reviewed and attributes such as assignment and status can be updated. Attachments and comments associated with each report are also accessible.Use CasesCrowdsource Manager can be configured for reviewing any crowd sourced information, including data collected through Crowdsource Reporter configurations such as these:citizen service requestshealth and safety reportscitizen science reportsdrone imagery reviewreviewing real estate property listingsConfigurable OptionsConfigure Crowdsource Manager to present a group of maps with editable layers, and personalize the app by modifying the following options: Display a custom title and logo in the application headerChoose a color schemeUse the map pop-up settings to specify which fields should be visible and which should be editableSupported DevicesThis application is responsively designed to support use in browsers on desktops and tablets..Data RequirementsCrowdsource Manager requires an ArcGIS Online group that contains at least one map with at least one editable feature layer.This web app includes the capability to edit a hosted feature service or an ArcGIS Server feature service. Creating hosted feature services requires an ArcGIS Online organizational subscription or an ArcGIS Developer account. Get Started This application can be created in the following ways:Click the Create a Web App button on this pageShare a group and choose to Create a Web AppOn the Content page, click Create - App - From Template Click the Download button to access the source code. Do this if you want to host the app on your own server and optionally customize it to add features or change styling.Learn MoreFor release notes and more information on configuring this app, see the Crowdsource Manager documentation.

Crowdsource Polling is a configurable app template that can be used for collecting feedback and assessing public sentiment for a series of proposals, plans, or events. Users are presented with a map and list of features containing the details of each proposal, plan, or event including any attached documents. These users can then submit their feedback in the form of votes and comments. Crowdsource Polling can be accessed anonymously and by authenticating via Twitter.Use CasesCrowdsource Polling can be configured to present information such as:proposed land use changesenvironmental impact pollingpublic comment on capital projectspublic comment on proposed rights of way for transmission systemsevents permit reviewConfigurable OptionsConfigure Crowdsource Polling to present content from any web map and personalize the app by modifying the following options: Display a custom title and logo in the application headerUse a custom color schemeChoose which layer contains the features for which feedback is being solicitedProvide custom instruction on the use of the app, contact information, credits, etc. in a highly configurable help windowSupported DevicesThis application is responsively designed to support use in browsers on desktops, mobile phones, and tablets.Data RequirementsThis web app includes the capability to edit a hosted feature service or an ArcGIS Server feature service. Creating hosted feature services requires an ArcGIS Online organizational subscription or an ArcGIS Developer account. Crowdsource Polling requires a web map with at least one feature layer. In addition, the following requirements must be met to expose full app functionality:To enable votes, this layer must have a numeric field for storing the number of votes on each featureTo collect comments, the feature layer must have a related tableTo capture the names of authenticated users, the layer must have a text field for storing this valueGet Started This application can be created in the following ways:Click the Create a Web App button on this pageShare a map and choose to Create a Web AppOn the Content page, click Create - App - From Template Click the Download button to access the source code. Do this if you want to host the app on your own server and optionally customize it to add features or change styling.Learn MoreFor release notes and more information on configuring this app, see the Crowdsource Polling documentation.

The Geospatial Analytics Market size was valued at USD 98.93 billion in 2023 and is projected to reach USD 227.04 billion by 2032, exhibiting a CAGR of 12.6 % during the forecasts period. The Geospatial Analytics Market describes an application of technologies and approaches processing geographic and spatial data for intelligence and decision-making purposes. This market comprises of mapping tools and software, spatial data and geographic information systems (GIS) used in various fields including urban planning, environmental, transport and defence. Use varies from inventory tracking and control to route optimization and assessment of changes in environment. Other trends are the growth of big data and machine learning to improve the predictive methods, the improved real-time data processing the use of geographic data in combination with other technologies, for example, IoT and cloud. Some of the factors that are fuelling the need to find a marketplace for GIS solutions include; Increasing importance of place-specific information Increasing possibilities for data collection The need to properly manage spatial information in a high stand environment. Recent developments include: In May 2023, Google launched Google Geospatial Creator, a powerful tool that allows users to create immersive AR experiences that are both accurate and visually stunning. It is powered by Photorealistic 3D Tiles and ARCore from Google Maps Platform and can be used with Unity or Adobe Aero. Geospatial Creator provides a 3D view of the world, allowing users to place their digital content in the real world, similar to Google Earth and Google Street View. , In April 2023, Hexagon AB launched the HxGN AgrOn Control Room. It is a mobile app that allows managers and directors of agricultural companies to monitor all field operations in real time. It helps managers identify and address problems quickly, saving time and money. Additionally, the app can help to improve safety by providing managers with a way to monitor the location and status of field workers. , In December 2022, ESRI India announced the availability of Indo ArcGIS offerings on Indian public clouds and services to provide better management, collecting, forecasting, and analyzing location-based data. , In May 2022, Trimble announced the launch of the Trimble R12i GNSS receiver, which has a powerful tilt adjustment feature. It enables land surveyors to concentrate on the task and finish it more quickly and precisely. , In May 2021, Foursquare purchased Unfolded, a US-based provider of location-based services. This US-based firm provides location-based services and goods, including data enrichment analytics and geographic data visualization. With this acquisition, Foursquare aims to provide its users access to various first and third-party data sets and integrate them with the geographical characteristics. , In January 2021, ESRI, a U.S.-based geospatial image analytics solutions provider, introduced the ArcGIS platform. ArcGIS Platform by ESRI operates on a cloud consumption paradigm. App developers generally use this technology to figure out how to include location capabilities in their apps, business operations, and goods. It aids in making geospatial technologies accessible. .

This dataset contains 50-ft contours for the Hot Springs shallowest unit of the Ouachita Mountains aquifer system potentiometric-surface map. The potentiometric-surface shows altitude at which the water level would have risen in tightly-cased wells and represents synoptic conditions during the summer of 2017. Contours were constructed from 59 water-level measurements measured in selected wells (locations in the well point dataset). Major streams and creeks were selected in the study area from the USGS National Hydrography Dataset (U.S. Geological Survey, 2017), and the spring point dataset with 18 spring altitudes calculated from 10-meter digital elevation model (DEM) data (U.S. Geological Survey, 2015; U.S. Geological Survey, 2016). After collecting, processing, and plotting the data, a potentiometric surface was generated using the interpolation method Topo to Raster in ArcMap 10.5 (Esri, 2017a). This tool is specifically designed for the creation of digital elevation models and imposes constraints that ensure a connected drainage structure and a correct representation of the surface from the provided contour data (Esri, 2017a). Once the raster surface was created, 50-ft contour interval were generated using Contour (Spatial Analyst), a spatial analyst tool (available through ArcGIS 3D Analyst toolbox) that creates a line-feature class of contours (isolines) from the raster surface (Esri, 2017b). The Topo to Raster and contouring done by ArcMap 10.5 is a rapid way to interpolate data, but computer programs do not account for hydrologic connections between groundwater and surface water. For this reason, some contours were manually adjusted based on topographical influence, a comparison with the potentiometric surface of Kresse and Hays (2009), and data-point water-level altitudes to more accurately represent the potentiometric surface. Select References: Esri, 2017a, How Topo to Raster works—Help | ArcGIS Desktop, accessed December 5, 2017, at ArcGIS Pro at http://pro.arcgis.com/en/pro-app/tool-reference/3d-analyst/how-topo-to-raster-works.htm. Esri, 2017b, Contour—Help | ArcGIS Desktop, accessed December 5, 2017, at ArcGIS Pro Raster Surface toolset at http://pro.arcgis.com/en/pro-app/tool-reference/3d-analyst/contour.htm. Kresse, T.M., and Hays, P.D., 2009, Geochemistry, Comparative Analysis, and Physical and Chemical Characteristics of the Thermal Waters East of Hot Springs National Park, Arkansas, 2006-09: U.S. Geological Survey 2009–5263, 48 p., accessed November 28, 2017, at https://pubs.usgs.gov/sir/2009/5263/. U.S. Geological Survey, 2015, USGS NED 1 arc-second n35w094 1 x 1 degree ArcGrid 2015, accessed December 5, 2017, at The National Map: Elevation at https://nationalmap.gov/elevation.html. U.S. Geological Survey, 2016, USGS NED 1 arc-second n35w093 1 x 1 degree ArcGrid 2016, accessed December 5, 2017, at The National Map: Elevation at https://nationalmap.gov/elevation.html.

This collection grew out of a prototype case tracking and crime mapping application that was developed for the United States Attorney's Office (USAO), Southern District of New York (SDNY). The purpose of creating the application was to move from the traditionally episodic way of handling cases to a comprehensive and strategic method of collecting case information and linking it to specific geographic locations, and collecting information either not handled at all or not handled with sufficient enough detail by SDNY's existing case management system. The result was an end-user application designed to be run largely by SDNY's nontechnical staff. It consisted of two components, a database to capture case tracking information and a mapping component to link case and geographic data. The case tracking data were contained in a Microsoft Access database and the client application contained all of the forms, queries, reports, macros, table links, and code necessary to enter, navigate through, and query the data. The mapping application was developed using Environmental Systems Research Institute's (ESRI) ArcView 3.0a GIS. This collection shows how the user-interface of the database and the mapping component were customized to allow the staff to perform spatial queries without having to be geographic information systems (GIS) experts. Part 1 of this collection contains the Visual Basic script used to customize the user-interface of the Microsoft Access database. Part 2 contains the Avenue script used to customize ArcView to link the data maintained in the server databases, to automate the office's most common queries, and to run simple analyses.