The global UAV Aerial Survey Services market is experiencing robust growth, driven by increasing demand across diverse sectors. Technological advancements in drone technology, offering higher resolution imagery and improved data processing capabilities, are significantly contributing to this expansion. The market's versatility, providing cost-effective and efficient solutions for various applications, further fuels its growth. Specific sectors like construction, agriculture, and energy are key drivers, utilizing UAV surveys for site mapping, precision agriculture, pipeline inspections, and environmental monitoring. While regulatory hurdles and data security concerns present challenges, the market is overcoming these limitations through the development of standardized operating procedures and robust data encryption techniques. Assuming a conservative CAGR of 15% (a reasonable estimate given the rapid technological advancements and increasing adoption rates in this sector), and a 2025 market size of $2 billion, the market is projected to reach approximately $4.2 Billion by 2033. This substantial growth is further fueled by the increasing affordability and accessibility of UAV technology, enabling more businesses to leverage aerial survey services. The segmentation of the UAV Aerial Survey Services market reveals that orthophoto and oblique image services are widely utilized, catering to diverse application needs. Forestry and agriculture are dominant sectors, with construction, power and energy, and oil & gas industries rapidly adopting this technology. Regional analysis highlights strong growth in North America and Asia-Pacific, driven by significant investments in infrastructure development and agricultural modernization. Europe follows closely, spurred by government initiatives promoting sustainable development and environmental monitoring. The competitive landscape includes both established players like Kokusai Kogyo and Zenrin, and emerging specialized companies, indicating a dynamic and competitive market with potential for further consolidation and innovation. The continued development of advanced data analytics capabilities, integrated with UAV imagery, will create new opportunities and drive market expansion.

Fixed-Wing Drones: With superior range capabilities, these drones provide high-resolution imagery, allowing inspectors to capture detailed images of large-scale assets from a distance. Their extended flight time enables efficient coverage of expansive areas, making them ideal for inspecting pipelines, power lines, and vast infrastructure projects. Multirotor Drones: Offering superior maneuverability and precision control, these drones excel in confined spaces and complex environments. Their hovering capabilities enable inspectors to access hard-to-reach areas, such as the undersides of bridges, wind turbine blades, and intricate industrial machinery. Hybrid Drones: Combining the strengths of fixed-wing and multirotor drones, hybrid drones provide a versatile solution for inspection tasks. They offer extended endurance, allowing for thorough coverage of large areas, while their agile maneuvering enables precise inspection of intricate structures and confined spaces. Recent developments include: July 2023: Airbyte, a data integration platform, partnered with FlytBase, a drone autonomy platform. This partnership will facilitate the integration of drone data into various enterprise systems, enabling real-time insights and data-driven decision-making., October 2023: Trimble, a leading provider of positioning and geospatial technology, acquired Geospatial Commissioning Services (GCS), a drone-based surveying and mapping company. This acquisition strengthens Trimble's position in the drone inspection and monitoring market and expands its service offerings.June 2023: Intel acquired Ascending Technologies, a leading provider of autonomous drones and software solutions. This acquisition gives Intel access to advanced drone technology and expertise, accelerating its development of autonomous drone solutions for various applications.. Key drivers for this market are: Enhanced safety and efficiency in asset inspection and monitoring. Growing adoption of drone inspection services in construction, energy, and agriculture.. Potential restraints include: Privacy and security concerns. Regulatory restrictions on drone operations. Skill gap in drone operation and data analysis.. Notable trends are: Integration of 5G and cellular connectivity for real-time data transmission. Development of swarm drones for autonomous inspection and mapping. Rise of edge computing for real-time data processing on drones..

The LiDAR drone market is experiencing robust growth, projected to reach a market size of $29 million in 2025, expanding at a compound annual growth rate (CAGR) of 18.9% from 2025 to 2033. This surge is driven by increasing demand across diverse sectors. The industrial sector leads the way, leveraging LiDAR drones for precise surveying, infrastructure inspection, and construction monitoring. Agricultural applications are also booming, with farmers using LiDAR technology for crop monitoring, precision spraying, and yield optimization. Geological surveys benefit from the high-resolution data provided by LiDAR drones for terrain mapping and resource exploration. Furthermore, advancements in sensor technology, improved data processing capabilities, and the decreasing cost of drone platforms are fueling market expansion. The rise of autonomous flight capabilities and the integration of AI for enhanced data analysis further contribute to market growth. While regulatory hurdles and initial investment costs can pose challenges, the overall market outlook remains highly positive. The diverse applications and technological advancements make LiDAR drones a powerful tool across numerous industries, ensuring continued market expansion in the coming years. The market segmentation reveals strong growth across both application and type categories. Rotary wing drones currently dominate the market due to their maneuverability and suitability for various terrains, but fixed-wing drones are gaining traction for their longer flight times and wider coverage area. Geographically, North America and Europe currently hold significant market share, driven by early adoption and technological advancements. However, rapid development in Asia-Pacific, particularly in China and India, points towards strong future growth potential in these regions. The competitive landscape is dynamic, with key players including 3D Robotics, DJI, and others continuously innovating and expanding their product offerings to cater to evolving market needs. This competitive environment fosters innovation and drives down prices, furthering market accessibility and penetration. This report provides a detailed analysis of the rapidly expanding LiDAR drone market, projected to be worth over $2 billion by 2028. It examines market dynamics, key players, technological advancements, and future growth prospects. The report leverages extensive primary and secondary research to offer invaluable insights for industry stakeholders, investors, and researchers. Keywords: LiDAR Drone Market, Drone Surveying, Aerial LiDAR, 3D Mapping, Point Cloud Data, Remote Sensing, Agricultural Drones, Industrial Drones, Geological Survey.

Market Size and Growth: The global Drone Mapping Services market was valued at USD 3,491 million in 2023 and is projected to grow exponentially at a CAGR of 16.4% over the forecast period from 2023 to 2033. This remarkable growth is primarily driven by factors such as increasing demand for precise geospatial data, technological advancements in drone technology, and the growing adoption of drones in various industries. Key Drivers, Trends, and Restraints: Key drivers of the market include the rising demand for accurate and timely data for decision-making, the increasing use of drones in surveying, mapping, and infrastructure inspection applications, and government regulations mandating the use of drone technology for certain projects. Advanced technology trends, such as the integration of AI and machine learning, enhance drone mapping accuracy and efficiency. However, factors such as privacy concerns, data security issues, and the need for skilled professionals can act as potential restraints on market growth.

The global mapping UAV market is experiencing robust growth, driven by increasing demand for high-resolution geospatial data across diverse sectors. This surge is fueled by advancements in sensor technology, improved drone autonomy, and the decreasing cost of UAV platforms. The market, estimated at $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This significant expansion is attributed to the expanding applications of mapping UAVs in infrastructure monitoring, precision agriculture, urban planning, environmental conservation, and disaster response. The military segment remains a significant contributor, utilizing UAVs for surveillance and reconnaissance. However, the civilian sector is witnessing even faster growth, driven by the increasing adoption of UAVs for efficient and cost-effective mapping solutions. The market segmentation highlights the prominence of rotary airfoil UAVs, favored for their maneuverability and vertical takeoff and landing capabilities, in contrast to fixed-wing UAVs that excel in covering larger areas. Technological advancements focusing on enhanced payload capacity, longer flight times, and improved data processing capabilities are further stimulating market expansion. While regulatory hurdles and concerns regarding data security represent potential restraints, the overall market outlook remains positive. The growth is geographically diverse, with North America and Europe currently leading the market, but the Asia-Pacific region is poised for significant expansion due to rapid infrastructure development and increasing adoption across various applications. Key players in the market are continuously innovating, resulting in the introduction of more advanced, feature-rich, and user-friendly UAV systems, further fueling market growth. This in-depth report provides a comprehensive analysis of the global Mapping UAVs market, projected to reach $2.5 billion by 2028. It delves into market concentration, key trends, dominant regions and segments, product insights, and future growth catalysts, offering invaluable insights for businesses, investors, and researchers involved in this rapidly evolving sector.

Two detailed geomorphological maps (1:2000) depicting landscape changes as a result of a glacial lake outburst flood were produced for the 2.1-km-long section of the Zackenberg river, NE Greenland. The maps document the riverscape before the flood (5 August 2017) and immediately after the flood (8 August 2017), illustrating changes to the riverbanks and morphology of the channel. A series of additional maps (1:800) represent case studies of different types of riverbank responses, emphasising the importance of the lateral thermo-erosion and bank collapsing as significant immediate effects of the flood. The average channel width increased from 40.75 m pre-flood to 44.59 m post-flood, whereas the length of active riverbanks decreased from 1729 to 1657 m. The new deposits related to 2017 flood covered 93,702 m2. The developed maps demonstrated the applicability of small Unmanned Aerial Vehicles (UAVs) for investigating the direct effects of floods, even in the harsh Arctic environment.

Aerial Imaging Market size was valued at USD 2.91 Billion in 2023 and is projected to reach USD 7. 29 Billion by 2031, growing at a CAGR of 13.4% during the forecasted period 2024 to 2031.

Aerial Imaging Market: Definition/ Overview

Aerial imaging is the technique of taking images or movies from an elevated position, usually with drones, aircraft, or satellites. This technology allows for the capture of high-resolution photos and data over huge areas, making it useful for a wide range of applications across sectors. Agriculture, for crop monitoring and health evaluation; building, for site surveying and progress tracking; environmental monitoring, to assess land usage and natural resources; and disaster management, which aids in damage assessment and recovery planning. Furthermore, aerial imaging aids in urban planning, real estate marketing, and infrastructure inspection making it a versatile tool for data-driven decision-making.

Snapshot img

Photogrammetry Software Market Size 2024-2028

The photogrammetry software market size is forecast to increase by USD 1.16 billion at a CAGR of 14.3% between 2023 and 2028.

The market is experiencing significant growth due to the increasing adoption of 3D mapping and modeling in various industries, particularly in building and construction. This technology enables the creation of geo-referenced maps and orthomosaic images from drone images, which are essential for 3D visualizations and 3D reconstruction. Additionally, the use of 3D scanning and computer visualization in applications such as 3D modeling and 3D printing of models for drones and quadcopters is driving market growth. However, challenges persist, including the inadequate infrastructure in developing and underdeveloped countries, which hampers the market's expansion. Key software solutions in this market include VisualSFM and OpenMVG, which offer advanced features for processing Images and Video to generate 3D models.

What will be the Size of the Market During the Forecast Period?

Request Free Sample

Photogrammetry software has emerged as a critical tool in various industries, particularly in defense and security, engineering, architecture, and surveyor sectors. This software utilizes advanced imaging technologies, such as high-resolution cameras, Lidar, and drones, to capture data in the form of a series of photographs. These images are then processed using artificial intelligence (AI) and machine learning algorithms to generate 3D models in real time. Data collection technologies have significantly evolved in recent years, with the integration of AI and machine learning enabling faster and more accurate processing of large datasets.

Moreover, the AI-driven photogrammetry software uses pixels and reference points from the images to create 3D meshes, which are essential for various applications, including emergency management and object recognition in space. The market is segmented into cloud-based Software as a Service (SaaS) and on-premises commercial/proprietary software. The SaaS model offers benefits such as cost savings, flexibility, and scalability, while on-premises software provides greater control and security. The use of AI-driven photogrammetry software is not limited to specific industries. It is widely adopted by surveyors, architects, engineers, and contractors to streamline their workflows and improve accuracy. For instance, Autodesk REMake, an AI-driven photogrammetry software, enables users to create 3D models from images, which can be used for various applications, including architectural design and construction planning.

Similarly, the geospatial technology plays a crucial role in the effective implementation of photogrammetry software. Real-time data processing and analysis are essential for various applications, including emergency management and infrastructure monitoring. The integration of AI and machine learning algorithms in photogrammetry software enables faster and more accurate processing of geospatial data, making it an indispensable tool for various industries. In conclusion, the advancement of imaging technologies, AI, and machine learning algorithms has significantly impacted the market. The software's ability to generate 3D models from a series of photographs in real-time makes it an essential tool for various industries, including defense and security, engineering, architecture, and surveyor sectors. The integration of geospatial technology further enhances the software's capabilities, making it an indispensable tool for data-driven decision-making.

Market Segmentation

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD Billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Application

  3D printing
  Drones and robots
  Films and games
  Others


Deployment

  On-premises
  Cloud


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK


  APAC

    China


  South America



  Middle East and Africa

By Application Insights

The 3D printing segment is estimated to witness significant growth during the forecast period. In the realm of advanced imaging technologies, the market is witnessing significant growth. This expansion is driven by various sectors, including Defense and Security, where high-precision 3D models are essential for mission planning and analysis. Artificial Intelligence (AI) and Machine Learning (ML) are also playing a pivotal role in the market's growth, enabling real-time data processing and analysis. Data collection technologies, such as LiDAR and high-resolution cameras, integrated with drones, are revolutionizing the way data is captured and processed. Geospatial technology, a critical component of photogrammetry, is enabling the creation

Hilltop Arboretum Dataset for GRASS GIS

This geospatial dataset contains raster data for the landform at Hilltop Arboretum, Baton Rouge, Louisiana, USA. This data was collected in an aerial survey with a DJI Phantom 4 Pro drone over Hilltop Arboretum on 12/31/2019 by Brendan Harmon and Josef Horacek. The aerial photographs were processed in Agisoft Metashape using Structure from Motion (SfM) to generate a point cloud, orthophotograph, and digital surface model. The point cloud was processed in CloudCompare to generate a bare earth point cloud. The orthophoto, digital surface model, and bare earth point cloud were imported into GRASS GIS. The bare earth point cloud was interpolated as a digital elevation model using the Regularized Spline with Tension method. The top level directory lousiana_s_spm_hilltop is a GRASS GIS location for the North American Datum of 1983 (NAD 83) / Louisiana South State Plane Meters with EPSG code 26982. Inside the location there are the PERMANENT mapset, a license file, and readme file.

Survey

• Location: LSU Hilltop Arboretum, Baton Rouge, Louisiana, USA.
• Drone: DJI Phantom 4 Pro
• Software: Agisoft Metashape, CloudCompare, GRASS GIS
• Team: Brendan Harmon and Josef Horacek
• Date: 12/31/2019
• GCPs: 10 AeroPoints

Instructions
Install GRASS GIS, unzip this archive, and move the location into your GRASS GIS database directory. If you are new to GRASS GIS read the first time users guide.

License
This dataset is licensed under the ODC Public Domain Dedication and License 1.0 (PDDL) by Brendan Harmon.

This dataset contains data used to test the protocol for high-resolution mapping and monitoring of recreational impacts in protected natural areas (PNAs) using unmanned aerial vehicle (UAV) surveys, Structure-from-Motion (SfM) data processing and geographic information systems (GIS) analysis to derive spatially coherent information about trail conditions (Tomczyk et al., 2023). Dataset includes the following folders:

Cocora_raster_data (~3GB) and Vinicunca_raster_data (~32GB) - a very high-resolution (cm-scale) dataset derived from UAV-generated images. Data covers selected recreational trails in Colombia (Valle de Cocora) and Peru (Vinicunca). UAV-captured images were processed using the structure-from-motion approach in Agisoft Metashape software. Data are available as GeoTIFF files in the UTM projected coordinate system (UTM 18N for Colombia, UTM 19S for Peru). Individual files are named as follows [location]_[year]_[product]_[raster cell size].tif, where:

[location] is the place of data collection (e.g., Cocora, Vinicucna)

[year] is the year of data collection (e.g., 2023)

[product] is the tape of files: DEM = digital elevation model; ortho = orthomosaic; hs = hillshade

[raster cell size] is the dimension of individual raster cell in mm (e.g., 15mm)

Cocora_vector_data. and Vinicunca_vector_data – mapping of trail tread and conditions in GIS environment (ArcPro). Data are available as shp files. Data are in the UTM projected coordinate system (UTM 18N for Colombia, UTM 19S for Peru).

Structure-from-motio n processing was performed in Agisoft Metashape (https://www.agisoft.com/, Agisoft, 2023). Mapping was performed in ArcGIS Pro (https://www.esri.com/en-us/arcgis/about-arcgis/overview, Esri, 2022). Data can be used in any GIS software, including commercial (e.g. ArcGIS) or open source (e.g. QGIS).

Tomczyk, A. M., Ewertowski, M. W., Creany, N., Monz, C. A., & Ancin-Murguzur, F. J. (2023). The application of unmanned aerial vehicle (UAV) surveys and GIS to the analysis and monitoring of recreational trail conditions. International Journal of Applied Earth Observations and Geoinformation, 103474. doi: https://doi.org/10.1016/j.jag.2023.103474

The UAV Surveying Laser LiDAR market is experiencing robust growth, driven by increasing demand for high-precision mapping and surveying solutions across various sectors. The market, currently valued at approximately $1.5 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This significant expansion is fueled by several key factors. The rising adoption of UAVs in infrastructure development, agriculture, mining, and environmental monitoring is a primary driver. These drones offer cost-effective, efficient, and safer alternatives to traditional surveying methods, providing detailed 3D point cloud data for accurate analysis and decision-making. Technological advancements, including the development of more compact, lightweight, and cost-effective LiDAR sensors with improved accuracy and range, are further accelerating market growth. The increasing availability of user-friendly data processing software is also streamlining workflow and widening the accessibility of LiDAR technology across diverse user groups. Furthermore, government initiatives promoting the use of advanced technologies in surveying and mapping are providing a strong impetus for market expansion. Segmentation analysis reveals a strong preference for Near-Infrared Laser Type LiDAR systems due to their cost-effectiveness and suitability for various applications. However, Water Penetrating Green Light Type LiDAR systems are gaining traction, especially in applications requiring data acquisition through water bodies. In terms of application, Fixed-Wing UAVs currently dominate the market due to their larger payload capacity and longer flight endurance. However, Rotary Airfoil UAVs are progressively gaining market share due to their maneuverability and suitability for complex terrain. Geographic distribution indicates a strong concentration of the market in North America and Europe, driven by advanced technological infrastructure and early adoption of LiDAR technology. However, rapid technological advancements and increasing infrastructure investments in the Asia-Pacific region are expected to fuel significant growth in this market segment over the forecast period. Despite these positive trends, challenges remain, including regulatory hurdles regarding UAV operations and the high initial investment costs associated with LiDAR systems.

The drone-mounted 3D scanner market is experiencing robust growth, projected at a 19% CAGR from 2025 to 2033, driven by increasing demand across diverse sectors. The market's current size of $844 million in 2025 signifies its significant presence and potential for future expansion. Key drivers include the rising need for efficient and cost-effective data acquisition in surveying, mapping, and inspection applications. The construction and municipal administration sectors are significant contributors, leveraging the technology for infrastructure monitoring, site modeling, and asset management. Agriculture and forestry benefit from precise land surveying and crop monitoring capabilities offered by these scanners. Similarly, the energy sector utilizes drone-mounted 3D scanners for pipeline inspection and renewable energy project development. Technological advancements, such as improved sensor accuracy, longer flight times, and enhanced data processing capabilities, are further fueling market expansion. However, regulatory hurdles related to drone operations and the high initial investment cost of the technology represent significant restraints to broader adoption. The market is segmented by application (Agriculture and Forestry, Air Transportation, Energy, Construction and Municipal Administration, Other) and scanner type (Light, Medium, Heavy), indicating diverse market needs and potential for specialized solutions. Competition is relatively high with key players such as Teledyne Geospatial, RIEGL, and others actively competing based on technology innovation and market reach. Geographic expansion is anticipated across North America, Europe, and Asia Pacific, reflecting increasing awareness and adoption across these regions. The market's trajectory suggests sustained growth, particularly in developing economies with substantial infrastructure development projects. Future growth will likely be influenced by technological innovations such as the integration of AI for automated data processing and analysis, and the development of more compact and affordable drone-mounted 3D scanners. Increased regulatory clarity and standardization of drone operations will also unlock wider market adoption. The heavy segment is anticipated to grow significantly due to the need for high-accuracy data in demanding applications. The continuous improvement in sensor technology, leading to better resolution and range, is driving the adoption of these systems across multiple sectors. Continued investment in research and development by key market players will further propel innovation and market expansion.

This Web Map is included in the Mitigating Marshes Against Sea Level Rise: Thin Layer Placement Experiment application.The National Estuarine Research Reserve (NERR) System Science Collaborative funded a two-year experiment at 8 different NERR sites to provide broad geographic scale, including Chesapeake Bay NERR in Virginia. The three core research questions they aim to answer include: “Is sediment addition an effective adaptation strategy for marshes in the face of sea level rise? How does marsh resilience respond to different levels of sediment addition? How do low versus high marsh habitats differ in their response to this restoration strategy?”.This Story Map is a tool for 6th-12th grade teachers to help teach students about marshes and thin layer placement restoration techniques by exploring maps, videos, and images. Students will analyze how vegetation has changed in the Chesapeake Bay National Estuarine Research Reserve in Virginia (CBNERR-VA) marsh experiment plots in the first year of monitoring. They will evaluate images and graphs different treatments and determine which could be used as a possible restoration technique to combat sea level rise in marshes.Data: https://www.vims.edu/cbnerr/resources/gis-data-layers/index.php

The Southeast Texas Urban Integrated field lab’s Co-design team captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024. Aerial photos taken were through autonomous flight, and models were processed through the DroneDeploy engine. All aerial photos are in .JPG format and contained in zipped files for each area. The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point Cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857. For using these data: - The Adobe Suite gives you great software to open .Tif files. - You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains. - Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk. - You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files. - The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file. This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset will support researchers' decision-making processes under uncertainties.

Geospatial data used in article "Estimation of river water surface elevation using UAV photogrammetry and machine learning" by Radosław Szostak, Marcin Pietroń, Przemysław Wachniew, Mirosław Zimnoch and Paweł Ćwiąkała (AGH UST).

Each zip archive contains the following files:

dsm.tif - raster of digital surface model,

ortho.tif - raster of orthophoto,

gnss_wse.json - geojson multipoint shape containing RTN GNSS measurements of water surface elevation,

grid.json - geojson multipolygon shape containing square areas of samples used in deep learning solution.

centerline.json - geojson multipoint shape containing values sampled from DSM along centerline,

wateredge.json - geojson multipoint shape containing values sampled from DSM along "water-edge".

Data in AMO18.zip archive was collected by Bandini et. al (https://doi.org/10.5281/zenodo.3519888).

Preprocessed machine learning dataset and source codes are available in github repository at: https://github.com/radekszostak/river-wse-uav-ml

General Description

A manually annotated dataset, consisting of the video frames and segmentation masks, for segmentation of forest fire burned area based on a video captured by a UAV. A detailed explanation of the dataset generation is available in the open-access article "Burned area semantic segmentation: A novel dataset and evaluation using convolutional networks".

Data Collection

The BurnedAreaUAV dataset derives from a video captured at the coordinates' latitude 41° 23' 37.56" and longitude -7° 37' 0.32", at Torre do Pinhão, in northern Portugal in an area characterized by shrubby to herbaceous vegetation. The video was captured during the evolution of a prescribed fire using a DJI Phantom 4 PRO UAV equipped with an FC6310S RGB camera.

Video Overview

The video captures a prescribed fire where the burned area increases progressively. At the beginning of the sequence, a significant portion of the UAV's sensor field of view is already burned, and the burned area expands as time goes by. The video was collected by an RGB sensor installed on a drone while keeping the drone in a nearly static stationary stance during the data collection duration.

The video has about 15 minutes and a frame rate of 25 frames per second, amounting to 22500 images. It was collected by an RGB sensor installed on a drone while keeping the drone in a nearly static stationary stance during the data collection duration. Throughout this period, the progression of the burned area is observed. The original video has a resolution of 720×1280 and is stored in H.264 (or MPEG-4 Part 10) format. No audio signal was collected.

Manual Annotation

The annotation was done every 100 frames, which corresponds to a sampling period of 4 seconds. Two classes are considered: burned_area and unburned_area. This annotation has been done for the entire length of the video. The training set consists of 226 frame-image pairs and the test set of 23. The training and test annotations are offset by 50 frames.

We plan to expand this dataset in the future.

File Organization (BurnedAreaUAV_v1.rar)

The data is available in PNG, JSON (Labelme format), and WKT (segmentation masks only). The raw video data is also made available.

Concomitantly, photos were taken that allow to obtain metadata about the position of the drone, including height and coordinates, the orientation of the drone and the camera, and others. The geographic data regarding the location of the controlled fire are represented in a KML file that Google Earth and other geospatial software can read. We also provide two high-resolution orthophotos of the area of interest before and after burning.

The data produced by the segmentation models developed in "Burned area semantic segmentation: A novel dataset and evaluation using convolutional networks", comprising outputs in PNG and WKT formats, is also readily available upon request

BurnedAreaUAV_dataset_v1.rar
MP4_video (folder)
-- original_prescribed_burn_video.mp4

PNG (folder)
train (folder)
frames (folder)
-- frame_000000.png (raster image)
-- frame_000100.png
-- frame_000200.png
…
msks (folder)
-- mask_000000.png
-- mask_000100.png
-- mask_000200.png
…

test (folder)
frames (folder)
-- frame_020250.png
-- frame_020350.png
-- frame_020350.png
…
msks (folder)
-- mask_020250.png
-- mask_020350.png
-- mask_020350.png
…
JSON (folder)
-- train_valid_json (folder)
-- frame_000000.json (Labelme format)
-- frame_000100.json
-- frame_000200.json
-- frame_000300.json
…
-- test_json (folder)
-- frame_020250.json
-- frame_020350.json
-- frame_020450.json
…
WKT_files (folder)
-- train_valid.wkt (list of masks polygons)
-- test.wkt

UAV photos (metadata)
-- uav_photo1_metadata.JPG
-- uav_photo2_metadata.JPG

High resolution ortophoto files
-- odm_orthophoto_afterBurning.png
-- odm_orthophoto_beforeBurning.png

Keyhole Markup Language file (area under study polygon)
-- pinhao_cell_precribed_area.kml

Acknowledgements

This dataset results from activities developed in the context of partially projects funded by FCT - Fundação para a Ciência e a Tecnologia, I.P., through projects MIT-EXPL/ACC/0057/2021 and UIDB/04524/2020, and under the Scientific Employment Stimulus - Institutional Call - CEECINST/00051/2018.

The source code is available here.

NPM Bangladesh has produced a number of tools based on its regular data collection activities and drone flights. The package of September - October 2018 is based on NPM Site Assessment 12 (as of 10 October) and NPM most updated drone imagery (as of 26 September).

Here below, the complete package by camp:

• SW Map package
• KMZ file
• Drone image

The full image and shapefiles are available at this link.

The global aerial photogrammetry surveying services market is experiencing robust growth, driven by increasing demand across diverse sectors. While precise market size figures for 2025 aren't provided, a reasonable estimation based on industry reports and the indicated CAGR (let's assume a conservative CAGR of 8% for illustration) suggests a market valuation in the billions of dollars. The market is segmented by both aircraft type (fixed-wing, rotary-wing, UAVs) and application, with significant growth observed in forestry and agriculture, construction, and infrastructure development. The rising adoption of advanced technologies like LiDAR and drone-based photogrammetry is a key trend, offering higher accuracy, efficiency, and cost-effectiveness compared to traditional methods. This technological advancement is also driving the integration of AI and machine learning for automated data processing and analysis, further accelerating market expansion. The increasing need for precise spatial data for urban planning, environmental monitoring, and disaster management contributes significantly to market growth. However, factors like regulatory hurdles, high initial investment costs associated with advanced technologies, and data security concerns may act as restraints to some extent. Growth is expected to be particularly strong in developing economies experiencing rapid urbanization and infrastructure development. North America and Europe currently hold significant market share, but the Asia-Pacific region is projected to exhibit the fastest growth rate due to increasing infrastructure projects and government initiatives promoting technological advancements in surveying. Companies specializing in aerial photogrammetry are strategically investing in research and development to enhance data acquisition and processing capabilities, offering integrated solutions and catering to the specialized needs of various sectors. The future of the aerial photogrammetry surveying services market is bright, with continued innovation and growing demand expected to fuel its expansion throughout the forecast period (2025-2033). Competition is expected to remain dynamic, with established players and new entrants vying for market share through technological innovation, strategic partnerships, and geographic expansion.

Our Co-design team is from the University of Texas, working on a Department of Energy-funded project focused on the Beaumont-Port Arthur area. As part of this project, we will be developing climate-resilient design solutions for areas of the region. More on www.caee.utexas.edu. We captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024. Aerial photos taken were through DroneDeploy autonomous flight, and models were processed through the DroneDeploy engine as well. All aerial photos are in .JPG format and contained in zipped files for each area. The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857. For using these data: - The Adobe Suite gives you great software to open .Tif files. - You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains. - Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk. - You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files. - The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file. This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset could streamline researchers' decision-making processes and enhance the design as well.

Our Co-design team is from the University of Texas, working on a Department of Energy-funded project focused on the Beaumont-Port Arthur area. As part of this project, we will be developing climate-resilient design solutions for areas of the region. More on www.caee.utexas.edu. We used a DJI Mavic 2 Pro to capture aerial photos in Beaumont-Port Arthur, TX, in February 2023, including: I. Beaumont Soccer Club II. Corps’ Port Arthur Resident Office III. Halbouty Pump Station comprises its vicinity IV. Lamar University (Including Exxon Power Plants close to Lamar Univ.) V. MLK Boulevard for aerial images of the industry and the ship channel VI. Salt Water Barrier (include some aerial images about the Big Thicket) Aerial photos taken were through DroneDeploy autonomous flight, and models were processed through the DroneDeploy engine as well. All aerial photos are in .JPG format and contained in zipped files for each location. The processed data package including 3D models, geospatial data, mappings, point clouds, and the animation video of Halbouty Pump Station has various file types: - The Adobe Suite gives you great software to open .Tif files. - You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains. - Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk. - You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files. - The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file. This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset could streamline researchers' decision-making processes and enhance the design as well. In October 2023, we had our follow-up data collection, including: I. Beaumont Soccer Club II. Shipping and Receiving Center at Lamar University After the aerial collection, we obtained aerial photos of those two locations mentioned above, as well as processed data (such as point clouds and models).