Detroit Street View (DSV) is an urban remote sensing program run by the Enterprise Geographic Information Systems (EGIS) Team within the Department of Innovation and Technology at the City of Detroit. The mission of Detroit Street View is ‘To continuously observe and document Detroit’s changing physical environment through remote sensing, resulting in freely available foundational data that empowers effective city operations, informed decision making, awareness, and innovation.’ LiDAR (as well as panoramic imagery) is collected using a vehicle-mounted mobile mapping system.

Due to variations in processing, index lines are not currently available for all existing LiDAR datasets, including all data collected before September 2020. Index lines represent the approximate path of the vehicle within the time extent of the given LiDAR file. The actual geographic extent of the LiDAR point cloud varies dependent on line-of-sight.

Compressed (LAZ format) point cloud files may be requested by emailing gis@detroitmi.gov with a description of the desired geographic area, any specific dates/file names, and an explanation of interest and/or intended use. Requests will be filled at the discretion and availability of the Enterprise GIS Team. Deliverable file size limitations may apply and requestors may be asked to provide their own online location or physical media for transfer.

LiDAR was collected using an uncalibrated Trimble MX2 mobile mapping system. The data is not quality controlled, and no accuracy assessment is provided or implied. Results are known to vary significantly. Users should exercise caution and conduct their own comprehensive suitability assessments before requesting and applying this data.

Sample Dataset: https://detroitmi.maps.arcgis.com/home/item.html?id=69853441d944442f9e79199b57f26fe3

Mobile GIS Data Collection Software Market Outlook

According to our latest research, the global Mobile GIS Data Collection Software market size reached USD 2.14 billion in 2024, and is anticipated to grow at a robust CAGR of 13.7% during the forecast period, reaching approximately USD 6.42 billion by 2033. This strong growth trajectory is primarily driven by the increasing demand for real-time geospatial data across multiple industries, the proliferation of mobile devices, and the integration of advanced technologies such as IoT and AI into GIS solutions. As organizations globally seek to enhance operational efficiency and decision-making capabilities, the adoption of mobile GIS data collection software continues to accelerate, reshaping the landscape of field data management and spatial analytics.

One of the pivotal growth factors for the Mobile GIS Data Collection Software market is the rapid digital transformation across industries such as utilities, transportation, agriculture, and government. Organizations are increasingly leveraging geospatial data to streamline field operations, optimize resource allocation, and improve asset management. The shift towards digitized workflows has created a surge in demand for mobile GIS solutions that enable real-time data capture, analysis, and sharing from remote locations. Furthermore, the growing emphasis on smart infrastructure and sustainable urban planning has amplified the need for accurate, up-to-date geographic information, positioning mobile GIS software as a critical tool in supporting these initiatives. The convergence of cloud computing, 5G connectivity, and mobile technologies is further enhancing the capabilities and accessibility of GIS platforms, making them indispensable for modern enterprises.

Another significant driver is the increasing adoption of IoT and sensor technologies, which are generating vast volumes of spatial data that require efficient collection, processing, and analysis. Mobile GIS data collection software enables seamless integration with IoT devices, allowing for automated data acquisition and real-time monitoring of assets, environmental conditions, and infrastructure. This capability is particularly valuable in sectors like environmental monitoring, utilities management, and agriculture, where timely and accurate geospatial data is essential for informed decision-making. Additionally, advancements in artificial intelligence and machine learning are empowering GIS software to deliver predictive analytics, anomaly detection, and advanced visualization, further expanding the application scope and value proposition of mobile GIS solutions.

The market is also benefiting from the increasing focus on regulatory compliance and safety standards, particularly in industries such as oil and gas, construction, and transportation. Mobile GIS data collection software facilitates compliance by providing accurate and auditable records of field activities, asset inspections, and environmental assessments. Moreover, the growing need for disaster management, emergency response, and public health surveillance is driving government agencies to invest in robust GIS platforms that support rapid data collection and situational awareness. As a result, vendors are continuously innovating to offer user-friendly, scalable, and secure solutions that cater to the evolving needs of diverse end-users, further fueling market expansion.

The integration of Mobile Mapping System technology into mobile GIS solutions is revolutionizing the way geospatial data is collected and analyzed. By utilizing vehicles equipped with advanced sensors and cameras, Mobile Mapping Systems enable the rapid and accurate capture of geospatial data across large areas. This technology is particularly beneficial for urban planning, infrastructure management, and environmental monitoring, where timely and precise data is crucial. As industries strive to enhance their operational capabilities, the adoption of Mobile Mapping Systems is becoming increasingly prevalent, providing a competitive edge through improved data accuracy and efficiency.

Regionally, North America currently dominates the Mobile GIS Data Collection Software market, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific. The presence of leading technology providers, high adoption rates of digital soluti

Lookup county land records information in this interactive application that is geared for mobile devices.

The 3D mobile mapping market is booming, projected to reach $8 billion by 2033 with a 15% CAGR. Discover key drivers, trends, and challenges shaping this rapidly evolving sector, including the role of AI, autonomous vehicles, and infrastructure management. Explore leading companies and regional market share analysis.

See the KDOT Mobile LiDAR Project Data Portal Home Page or the 2023 Approaches Home Page for more details about the project and the delivered data.

Cleaned dataset for the Pharos application 2023-2024 data collection period (May 2023-March 2024). This dataset includes the full recurring network measurement (RNM), landmark (LM) datasets, as well as the county geographies used for the study catchment area. Also included in this dataset are a text document containing the necessary requirements, as well as python script to clean and visualize the collected data replicating the methods used in our published analysis.

Mobile ready land records, maps and data integrated with tax, CAMA and permitting information.

Discover the booming GIS Data Collector market! This comprehensive analysis reveals a $2.5B market in 2025, projected to reach $4.2B by 2033, fueled by precision agriculture, infrastructure development, and technological advancements. Explore key trends, drivers, restraints, and leading companies shaping this dynamic sector.

These data provide an accurate high-resolution shoreline compiled from imagery of PORT OF MOBILE, AL . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://www.fisheries.noaa.gov/inport/item/39808

GapMaps uses known population data combined with billions of mobile device location points to provide highly accurate and globally consistent GIS data at 150m grid levels across Asia and MENA. Understand who lives in a catchment, where they work and their spending potential.

See the KDOT Mobile LiDAR Project Data Portal Home Page or the 2023 Sidewalks Home Page for more details about the project and the delivered data.

See the KDOT Mobile LiDAR Project Data Portal Home Page or the 2023 Billboard Faces Home Page for more details about the project and the delivered data.

The mobile map market is booming, projected to reach $XX million by 2033 with a CAGR of 18.41%. Explore key drivers, trends, and regional insights in this comprehensive market analysis. Discover leading companies and competitive strategies shaping this dynamic sector. Learn more!

Global Mobile Mapping Market size was valued at USD 24.18 billion in 2022 and is poised to grow from USD 28.1 billion in 2023 to USD 93.39 billion by 2031, growing at a CAGR of 16.2%

The global mapping software market is experiencing robust growth, driven by increasing demand across various sectors. While precise figures for market size and CAGR are absent from the provided data, a reasonable estimation can be made based on industry trends. Considering the presence of major players like Adobe, Autodesk, and Microsoft, and the consistent advancements in GIS technology and location-based services, a conservative estimate places the 2025 market size at approximately $15 billion USD. Assuming a steady growth trajectory influenced by factors like increasing adoption of cloud-based solutions, the integration of AI and machine learning for enhanced mapping capabilities, and the growing need for precise location data in logistics, urban planning, and environmental monitoring, a Compound Annual Growth Rate (CAGR) of 8-10% over the forecast period (2025-2033) seems plausible. This would project market values significantly higher by 2033. This growth is fueled by several key trends. The increasing availability of high-resolution satellite imagery and other geospatial data provides richer inputs for mapping applications. Furthermore, the rising adoption of mobile devices equipped with GPS technology and the proliferation of location-based services (LBS) are expanding the market's addressable user base. However, challenges remain, such as the high cost of advanced mapping software and the complexities associated with data integration and management. Nevertheless, the overall market outlook remains positive, with continued expansion anticipated across various segments and geographic regions. The competitive landscape is marked by a mix of established players and emerging startups, leading to innovation and the continuous improvement of mapping technologies.

This research paper presents the design and development of an indigenous low cost Mobile Mapping System (MMS) for urban surveying applications. The MMS is comprised of economical Hokuyo-30LX 2D laser scanners, vision sensors, Global Positioning System (GPS) and various odometric sensors that can be installed on car like moving platform. The run time sensorial data is interfaced, processed and recorded using Robot Operating System (ROS). The live laser scan is utilized for the pose estimation using Simultaneous Localization and Mapping (SLAM) technique. In absence of valid SLAM estimation and frequent GPS outages, a multimodal sensor fusion framework for the enhanced pose correction has been developed using Kalman Filter (KF) by incorporating the Inertial Measurement Unit (IMU) and wheel odometric data along with SLAM and GPS data. The corrected pose is utilized for the 3D point cloud mapping by incorporating laser scans perceived periodically from various 2D laser scanners mounted on the MMS. The custom-made installation scheme has been followed for mounting three 2D laser scanners at horizontal, vertical and inclined orientations. The efficacy of the developed map has employed for extraction of road edges and associated road assets by establishing the lucrative classification technique of the point cloud using Split and Merge segmentation and Hough transformation. The surveying to map development time has significantly reduced and the mapping results have found quite accurate when matched with the ground truths. Furthermore, the comparison of the developed maps with ground truths and GIS tools reveals the highly acceptable accuracy of the generated results which have found very nearly aligned with the actual urban environment features. In comparison to the existing global MMS variants, the presented MMS is quite affordable solution for limited financial resourced business entities.

This map presents transportation data, including highways, roads, railroads, and airports for the world.

The map was developed by Esri using Esri highway data; Garmin basemap layers; HERE street data for North America, Europe, Australia, New Zealand, South America and Central America, India, most of the Middle East and Asia, and select countries in Africa. Data for Pacific Island nations and the remaining countries of Africa was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.

LiDAR Mobile Mapping for Distribution Market Outlook

According to our latest research, the global LiDAR mobile mapping for distribution market size reached USD 2.14 billion in 2024, with a robust year-on-year growth rate and a compound annual growth rate (CAGR) of 13.6% projected through 2033. The market is anticipated to reach USD 6.52 billion by 2033, driven by the rapid adoption of advanced mapping technologies across diverse distribution networks. This expansion is propelled by the increasing demand for real-time asset management, infrastructure inspection, and route optimization, particularly within utility, transportation, and logistics sectors. As per our latest research, the market's substantial growth is underpinned by technological advancements in LiDAR sensors, improved processing software, and the rising need for high-precision geospatial data in distribution operations.

A primary growth factor for the LiDAR mobile mapping for distribution market is the escalating requirement for accurate and efficient asset management within utility and distribution networks. Utilities and distribution companies increasingly rely on LiDAR mobile mapping systems to capture high-resolution, three-dimensional geospatial data, enabling them to monitor and manage assets such as power lines, pipelines, and telecommunications infrastructure. The ability to rapidly collect and process spatial data reduces operational costs, minimizes downtime, and enhances safety by identifying potential hazards before they escalate. The integration of LiDAR with GIS and cloud-based platforms further augments these capabilities, allowing for real-time data access and collaborative decision-making. As regulatory frameworks tighten around asset integrity and preventive maintenance, the adoption of LiDAR mobile mapping solutions is expected to accelerate, supporting both compliance and operational excellence.

Another significant driver fueling the market's growth is the surge in infrastructure development and modernization projects worldwide. Governments and private enterprises are investing heavily in upgrading aging infrastructure, particularly in the transportation, oil & gas, and telecommunications sectors. LiDAR mobile mapping technologies provide unparalleled precision in surveying and mapping, which is critical for planning, construction, and ongoing maintenance of distribution networks. The technology's ability to deliver rapid, accurate, and cost-effective mapping solutions is especially valuable in large-scale projects where traditional surveying methods are time-consuming and prone to human error. Additionally, the proliferation of smart city initiatives and the growing emphasis on digital twins for infrastructure management are creating new opportunities for LiDAR mobile mapping providers. These trends are expected to sustain high demand for advanced mapping solutions over the next decade.

The market is also being propelled by continuous advancements in LiDAR hardware and software components. Innovations such as multi-sensor integration, enhanced range and accuracy, and miniaturized, lightweight LiDAR units are making mobile mapping systems more versatile and accessible. The emergence of AI-driven analytics and machine learning algorithms for automated feature extraction and classification is further enhancing the value proposition of LiDAR mobile mapping. These technological breakthroughs are reducing the barriers to entry for smaller enterprises and expanding the range of applications across different end-user industries. Moreover, the increasing availability of cloud-based processing services and subscription-based business models are making LiDAR mobile mapping solutions more scalable and cost-effective, thus broadening their adoption in both mature and emerging markets.

From a regional perspective, North America continues to dominate the LiDAR mobile mapping for distribution market, accounting for the largest share in 2024, closely followed by Europe and the Asia Pacific. The strong presence of leading technology providers, early adoption of advanced mapping solutions, and significant investments in infrastructure modernization are key factors supporting market growth in these regions. Meanwhile, the Asia Pacific region is witnessing the fastest growth, driven by rapid urbanization, expanding utility networks, and government initiatives to enhance distribution efficiency and resilience. Latin America and the Middle East & Africa are also emerging as pr

These data provide an accurate high-resolution shoreline compiled from imagery of WESTERN MOBILE BAY, AL . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://www.fisheries.noaa.gov/inport/item/39808