The global field data collection software market is experiencing robust growth, driven by increasing demand for efficient data management and analysis across various industries. The market's expansion is fueled by several key factors: the rising adoption of mobile technologies and cloud-based solutions, the need for real-time data insights to improve operational efficiency, and the increasing pressure to comply with stringent regulatory standards in sectors like environmental monitoring and construction. The market is segmented by application (environmental, construction, oil and gas, transportation, mining, and others) and deployment type (cloud-based and on-premises). Cloud-based solutions are witnessing higher adoption rates due to their scalability, cost-effectiveness, and accessibility. While North America currently holds a significant market share due to early adoption and technological advancements, regions like Asia-Pacific are projected to experience substantial growth in the coming years, driven by rapid industrialization and infrastructure development. The competitive landscape includes established players like SafetyCulture and ArcGIS alongside emerging innovative companies continuously improving the software functionalities and user experience. Competition is intense, focused on providing superior data visualization, integration capabilities, and user-friendly interfaces. The market is anticipated to continue its upward trajectory, driven by ongoing technological innovation and the increasing reliance on data-driven decision-making across diverse industries. Despite the positive market outlook, certain challenges remain. The high initial investment required for implementing some solutions, particularly in the on-premises segment, and the need for specialized training to effectively utilize the software can act as restraints. Further, data security and privacy concerns remain a priority for organizations, particularly in regulated industries. Overcoming these challenges will require a focus on developing more user-friendly, affordable, and secure solutions with seamless integration capabilities, emphasizing the value proposition through clear ROI demonstrations and providing robust training and support services to users. The long-term forecast suggests continued market expansion, driven by a sustained focus on addressing these constraints and leveraging technological advancements to enhance data collection and management capabilities. The predicted CAGR will likely be influenced by economic conditions, technological innovation, and the evolving regulatory landscape.

Overview: This document is a reference guide for users of the SAR Field Data Collection Form User Guide. The purpose is to provide a better understanding of how to use the form in the field.

The underlying technology used with this form is likely to evolve and change over time, therefore technical user guides will be provided as appendices to this document.

Background: The SAR Field Data Collection Form was created by an interdisciplinary group of first responders, decision-makers and technology specialists from across Federal, State, and Local Urban Search and Rescue Teams – the NAPSG Foundation SAR Working Group. If you have any questions or concerns regarding this document and associated materials, please send a note to comments@publicsafetygis.org.

Purpose: The SAR Field Data Collection Form is intended to provide a standardized approach to the collection of information during disaster response alongside resource management and tracking of assets.The primary goal of this approach is to obtain situational awareness (where, when, what) for SAR Teams in the field across four relevant themes: Victims that may need assistance or have already been helped. Hazards that must be avoided or mitigated. Damage that have been rapidly assessed for damage, when time and the mission permits. Other mission critical intelligence that vary based on mission type. The secondary goal of this approach is to provide essential elements of information to those not currently on-scene of the disaster. Using the themes above, information and maps can be shared based on “need to know”. If you are a technology specialist looking to deploy this application on your own see the Deployment Kit.

GIS Data Collector Market Outlook

The global GIS Data Collector market size is anticipated to grow from USD 4.5 billion in 2023 to approximately USD 12.3 billion by 2032, at a compound annual growth rate (CAGR) of 11.6%. The growth of this market is largely driven by the increasing adoption of GIS technology across various industries, advances in technology, and the need for effective spatial data management.

An important factor contributing to the growth of the GIS Data Collector market is the rising demand for geospatial information across different sectors such as agriculture, construction, and transportation. The integration of advanced technologies like IoT and AI with GIS systems enables the collection and analysis of real-time data, which is crucial for effective decision-making. The increasing awareness about the benefits of GIS technology and the growing need for efficient land management are also fuelling market growth.

The government sector plays a significant role in the expansion of the GIS Data Collector market. Governments worldwide are investing heavily in GIS technology for urban planning, disaster management, and environmental monitoring. These investments are driven by the need for accurate and timely spatial data to address critical issues such as climate change, urbanization, and resource management. Moreover, regulatory policies mandating the use of GIS technology for infrastructure development and environmental conservation are further propelling market growth.

Another major growth factor in the GIS Data Collector market is the continuous technological advancements in GIS software and hardware. The development of user-friendly and cost-effective GIS solutions has made it easier for organizations to adopt and integrate GIS technology into their operations. Additionally, the proliferation of mobile GIS applications has enabled field data collection in remote areas, thus expanding the scope of GIS technology. The advent of cloud computing has further revolutionized the GIS market by offering scalable and flexible solutions for spatial data management.

Regionally, North America holds the largest share of the GIS Data Collector market, driven by the presence of key market players, advanced technological infrastructure, and high adoption rates of GIS technology across various industries. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, primarily due to rapid urbanization, government initiatives promoting GIS adoption, and increasing investments in smart city projects. Other regions such as Europe, Latin America, and the Middle East & Africa are also experiencing significant growth in the GIS Data Collector market, thanks to increasing awareness and adoption of GIS technology.

The role of a GPS Field Controller is becoming increasingly pivotal in the GIS Data Collector market. These devices are essential for ensuring that data collected in the field is accurate and reliable. By providing real-time positioning data, GPS Field Controllers enable precise mapping and spatial analysis, which are critical for applications such as urban planning, agriculture, and transportation. The integration of GPS technology with GIS systems allows for seamless data synchronization and enhances the efficiency of data collection processes. As the demand for real-time spatial data continues to grow, the importance of GPS Field Controllers in the GIS ecosystem is expected to rise, driving further innovations and advancements in this segment.

Component Analysis

The GIS Data Collector market is segmented by component into hardware, software, and services. Each of these components plays a crucial role in the overall functionality and effectiveness of GIS systems. The hardware segment includes devices such as GPS units, laser rangefinders, and mobile GIS devices used for field data collection. The software segment encompasses various GIS applications and platforms used for data analysis, mapping, and visualization. The services segment includes consulting, training, maintenance, and support services provided by GIS vendors and solution providers.

In the hardware segment, the demand for advanced GPS units and mobile GIS devices is increasing, driven by the need for accurate and real-time spatial data collection. These devices are equipped with high-precision sensors and advanced features such as real-time kinematic (RTK) positioning, which enhance

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

Market Overview The global Field Data Collection Software market has witnessed tremendous growth in recent years, driven by the increasing demand for real-time data collection and analysis. The market size was estimated to be XXX million in 2025 and is projected to grow at a CAGR of XX% from 2025 to 2033. Key growth drivers include the rising adoption of mobile devices and cloud-based platforms, the need for improved safety and compliance, and the increasing complexity of field operations. Segmentation and Regional Analysis The market is segmented by deployment type (cloud-based and on-premises) and application (environmental, construction, oil and gas, transportation, mining, and others). The environmental segment held the largest market share in 2025, driven by the growing need for environmental monitoring and compliance. Geographically, North America and Europe are the dominant markets, followed by Asia Pacific and the Middle East & Africa. The market in Asia Pacific is expected to witness significant growth in the coming years due to the rapidly expanding construction and mining industries.

Survey123 for ArcGIS is a simple and intuitive form-centric field data gathering solution. This seminar teaches you about Survey123. The presenters demonstrate how to create both simple and more sophisticated surveys, collect data over the web and in the field, analyze and view the survey results with Survey123's reporting capabilities, and how survey data is integrated with the ArcGIS platform.This seminar was developed to support the following:Survey123 for ArcGIS

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.

Field data collection was conducted for the U.S. Army Engineer District, Pacific Ocean, Honolulu (POH), during 23-29 August 2007, in the vicinity of the Natatorium, a World War I memorial in Kapiolani Park, Honolulu, Oahu, Hawaii. Three bottom mounted instruments were deployed to measure waves and currents. A Nortek AWAC (1 MHz) acoustic current profiler was placed seaward of the reef, centered off the Natatorium, in about 5m depth. An RD Instruments ADCP (1.2 MHz) current profiler was mounted on the channel bottom near the entrance, in about 3m depth. The third unit was a Nortek Aquadopp current profiler (2 MHz) was placed in a small hole in the reef, about 35m seaward of the Natatorium pool outer wall in a nominal depth of 1.5m. The first two gauges recorded directional waves and current profiles, the Aquadopp only recorded current profiles. Four inexpensive current drogues (drifters) were designed and built at the CHL Field Research Facility (FRF) that used GPS tracking and radio telemetry for positioning.

Observer Program web page that lists the observer field manual and all current data collection forms that observers are required to take out to sea.

U.S. Geological Survey (USGS) scientists conducted field data collection efforts during the time periods of April 25 - 26, 2017, October 24 - 28, 2017, and July 25 - 26, 2018, using a combination of surveying technologies to map and validate topography, structures, and other features at five sites in central South Dakota. The five sites included the Chamberlain Explorers Athletic Complex and the Chamberlain High School in Chamberlain, SD, Hanson Lake State Public Shooting Area near Corsica, SD, the State Capital Grounds in Pierre, SD, and Platte Creek State Recreation Area near Platte, SD. The work was initiated as an effort to evaluate airborne Geiger-Mode and Single Photon light detection and ranging (lidar) data that were collected over parts of central South Dakota. Both Single Photon and Geiger-Mode lidar offer the promise of being able to map areas at high altitudes, thus requiring less time than traditional airborne lidar collections, while acquiring higher point densities. Real Time Kinematic Global Navigational Satellite System (RTK-GNSS), total station, and ground-based lidar (GBL) data were collected to evaluate data collected by the Geiger-Mode and Single Photon systems.

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.

This data release contains field sampling data collected on a farm located in Talbot County. Maryland, roadside survey data from the area surrounding the farm, and WorldView-3 satellite data of the study area. Datasets include: 1) CropResidueDataset.csv: Tabular data for 174 photo sampling locations with crop residue cover ranging from 0% to 98%, as well as line-point transect residue cover measurements and lat-long geolocations 2) Roadside_Survey_May14th2015.zip: Zipfile containing roadside survey data for 63 fields documenting percent crop residue cover, including shapefile of field boundaries 3) GroundCoverPhotographs.zip: Zipfile containing 174 nadir photographs that were the basis for ground cover calculations 4) WorldView-3 satellite imagery collected May 14, 2015 and converted to surface reflectance using MODTRAN. The data support a manuscript published in Remote Sensing journal: Hively, W.D; Lamb, B.T. Daughtry, C.S.T. Shermeyer, J. McCarty, G.W., and Quemada, M., 2018, Mapping Crop Residue and Tillage Intensity Using WorldView-3 Satellite Shortwave Infrared Residue Indices: Remote Sensing, vol. 10, p. 1657. https://doi.org/10.3390/rs10101657

This collection consists of ASCII files containing derived magnetic field maps and equivalent source dipole arrays for the crustal magnetic field of Mercury. Zero values (mainly found along the map edges) indicate no useful data.

Discharge measurements from field-based surveys

This collection consists of ASCII files containing derived magnetic field maps and equivalent source dipole arrays for the crustal magnetic field of Mercury. Zero values (mainly found along the map edges) indicate no useful data.

This dataset contains the West Siberian Lowland (WSL) peatland GIS data collection. The collection covers the entire West Siberian lowland and was compiled from a wide array of data under the auspices of the NSF-funded Sensitivity of the West Siberian Lowland to Past and Present Climate project (Smith et al., 2000; Smith et al., 2004). Detailed physical characteristics of 9,691 individual peatlands (patches) were obtained from previously unpublished Russian field and ancillary map data, previously published depth measurements, and field depth and core measurements taken throughout the region during field campaigns in 1999, 2000, and 2001. The data collection features eight layers containing the detailed peatland inventory, political, and hydrographic information. Point data consist of field and laboratory measurements of peat depth, ash content, and bulk density. This research was funded by the National Science Foundation (NSF) Office of Polar Programs (OPP), grant number OPP-9818496.

Portable Data Collector Market Outlook

The global portable data collector market size was valued at approximately USD 2.5 billion in 2023 and is projected to reach USD 4.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.1% over the forecast period. The growth of this market is primarily driven by the increasing demand for real-time data capture and analysis across various industries. Advancements in technology, such as the integration of IoT and AI, are further propelling the market by enhancing the functionality and efficiency of portable data collectors.

One of the key growth factors for the portable data collector market is the rising need for automation in data collection and processing tasks. Industries such as retail, healthcare, and logistics are increasingly adopting portable data collectors to streamline operations, reduce human errors, and improve overall productivity. These devices enable quick and accurate data capture, which is crucial for inventory management, patient tracking, and supply chain optimization. Additionally, the growing trend of digital transformation across enterprises is encouraging the adoption of advanced data collection solutions.

Another significant factor contributing to the market's growth is the increasing penetration of mobile and wearable technology. The proliferation of smartphones and wearable devices equipped with advanced sensors and connectivity options has made it easier for businesses to deploy portable data collection solutions. These devices offer the flexibility to collect data from remote locations and in real-time, enhancing decision-making processes. Moreover, the integration of cloud computing with portable data collectors allows for seamless data storage and access, further boosting their adoption.

Furthermore, regulatory requirements and standards for data accuracy and security are driving the demand for portable data collectors. Industries such as healthcare and BFSI (Banking, Financial Services, and Insurance) are subject to stringent regulations that mandate precise data capture and secure handling of sensitive information. Portable data collectors equipped with advanced encryption and authentication features are becoming essential tools to comply with such regulations. This trend is expected to continue, further fueling market growth.

From a regional perspective, North America is anticipated to dominate the portable data collector market owing to its advanced technological infrastructure and high adoption rate of innovative solutions. The presence of major market players and the growing emphasis on automation and digitalization in sectors like retail and healthcare are key factors driving the market in this region. Meanwhile, the Asia Pacific region is expected to witness significant growth, attributed to the rapid industrialization and increasing investments in technology by emerging economies like China and India.

Product Type Analysis

The portable data collector market can be segmented by product type into handheld data collectors, wearable data collectors, and mobile data collectors. Handheld data collectors are expected to hold a significant market share, driven by their versatility and ease of use. These devices are widely used in retail, logistics, and healthcare for various applications such as inventory management, asset tracking, and patient care. The robust design and advanced features like barcode scanning and RFID capabilities make handheld data collectors a preferred choice for many industries.

Wearable data collectors are gaining traction due to the increasing adoption of wearable technology in sectors like healthcare and manufacturing. These devices offer hands-free operation, which is particularly beneficial in environments where manual data entry is impractical or hazardous. Wearable data collectors equipped with advanced sensors can monitor and collect data on various parameters such as heart rate, temperature, and movement, making them invaluable in medical and industrial applications. The integration of IoT in wearable data collectors is expected to further enhance their functionality and adoption.

Mobile data collectors, which include smartphones and tablets equipped with data collection apps, are also witnessing substantial growth. The widespread availability of mobile devices and the development of specialized data collection software have made mobile data collectors a cost-effective and flexible solution for businesses. These devices are particularly popular in field data collection activities, where portability a

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

Ontario Geological Survey Summary of Field Work 2018. Summary of Field Work and Other Activities presenting highlights of, and key new information from mapping and geoscientific research conducted during the year.Maleki, A., McNeice, W.J., Justina, F., Eshaghi, E., and Smith, R.S. 2018. Potential field data aquisition and compilation across Metal Earth's areas of interest; in Summary of Field Work and Other Activities, 2018, Ontario Geological Survey, Open File Report 6350, p.46-1 to 46-5.

Tags

   survey, environmental behaviors, lifestyle, status, PRIZM, Baltimore Ecosystem Study, LTER, BES




   Summary


   BES Research, Applications, and Education


   Description


   Geocoded for Baltimore County. The BES Household Survey 2003 is a telephone survey of metropolitan Baltimore residents consisting of 29 questions. The survey research firm, Hollander, Cohen, and McBride conducted the survey, asking respondents questions about their outdoor recreation activities, watershed knowledge, environmental behavior, neighborhood characteristics and quality of life, lawn maintenance, satisfaction with life, neighborhood, and the environment, and demographic information. The data from each respondent is also associated with a PRIZM� classification, census block group, and latitude-longitude. PRIZM� classifications categorize the American population using Census data, market research surveys, public opinion polls, and point-of-purchase receipts. The PRIZM� classification is spatially explicit allowing the survey data to be viewed and analyzed spatially and allowing specific neighborhood types to be identified and compared based on the survey data. The census block group and latitude-longitude data also allow us additional methods of presenting and analyzing the data spatially. 


   The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. 



   The BES 2003 telephone survey was conducted by Hollander, Cohen, and McBride from September 1-30, 2003. The sample was obtained from the professional sampling firm Claritas, in order that their "PRIZM" encoding would be appended to each piece of sample (telephone number) supplied. Mailing addresses were also obtained so that a postcard could be sent in advance of interviewers calling. The postcard briefly informed potential respondents about the survey, who was conducting it, and that they might receive a phone call in the next few weeks. A stratified sampling method was used to obtain between 50 - 150 respondents in each of the 15 main PRIZM classifications. This allows direct comparison of PRIZM classifications. Analysis of the data for the general metropolitan Baltimore area must be weighted to match the population proportions normally found in the region. They obtained a total of 9000 telephone numbers in the sample. All 9,000 numbers were dialed but contact was only made on 4,880. 1508 completed an interview, 2524 refused immediately, 147 broke off/incomplete, 84 respondents had moved and were no longer in the correct location, and a qualified respondent was not available on 617 calls. This resulted in a response rate of 36.1% compared with a response rate of 28.2% in 2000. The CATI software (Computer Assisted Terminal Interviewing) randomized the random sample supplied, and was programmed for at least 3 attempted callbacks per number, with emphasis on pulling available callback sample prior to accessing uncalled numbers. Calling was conducted only during evening and weekend hours, when most head of households are home. The use of CATI facilitated stratified sampling on PRIZM classifications, centralized data collection, standardized interviewer training, and reduced the overall cost of primary data collection. Additionally, to reduce respondent burden, the questionnaire was revised to be concise, easy to understand, minimize the use of open-ended responses, and require an average of 15 minutes to complete. 


   The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data, including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. 


   Additional documentation of this database is attached to this metadata and includes 4 documents, 1) the telephone survey, 2) documentation of the telephone survey, 3) metadata for the telephone survey, and 4) a description of the attribute data in the BES survey 2003 survey.


   This database was created by joining the GDT geographic database of US Census Block Group geographies for the Baltimore Metropolitan Statisticsal Area (MSA), with the Claritas PRIZM database, 2003, of unique classifications of each Census Block Group, and the unique PRIZM code for each respondent from the BES Household Telephone Survey, 2003. The GDT database is preferred and used because