Human life is precious and in the event of any unfortunate occurrence, highest efforts are made to safeguard it. To provide timely aid or undertake extraction of humans in distress, it is critical to accurately locate them. There has been an increased usage of drones to detect and track humans in such situations. Drones are used to capture high resolution images after natural and manmade disasters. It is possible to find survivors from drone feed, but that requires manual analysis. This is a time taking process and is prone to human errors. This model is capable of detecting humans by looking at drone imagery and can draw bounding boxes around their exact location. Deep learning models are highly capable of learning complex semantics and can produce superior results. Use this deep learning model to automate the task of detection, reducing time and effort required significantly.Licensing requirementsArcGIS Desktop – ArcGIS Image Analyst extension for ArcGIS ProArcGIS Enterprise – ArcGIS Image Server with raster analytics configuredArcGIS Online – ArcGIS Image for ArcGIS OnlineUsing the modelFollow the guide to use the model. Before using this model, ensure that the supported deep learning libraries are installed. For more details, check Deep Learning Libraries Installer for ArcGIS.Note: Deep learning is computationally intensive, and a powerful GPU is recommended to process large datasets.InputHigh resolution (1-5 cm) individual drone images or an orthomosaic.OutputFeature class containing detected humansApplicable geographiesThe model is expected to work well in coastal areas of Africa but can also be tried in other areas.Model architectureThis model uses the FasterRCNN model architecture implemented in ArcGIS API for Python.Accuracy metricsThis model has an average precision score of 72.8 percent for humans and 67.1 for possibly a human class.Limitations • This model has a tendency to maximize detection of humans and errs towards producing false positives. • It has been noticed that a few features get missed when a cluster of features is reported.Sample results

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.

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

Images were acquired from approximately 80 m above ground surface on the 12th of February 2021, using a Phantom 4 Advanced drone with an FC330 camera. The images are in file input_images.zip.

The mission planning software DJI GS Pro was used to automatically acquire images at suitable locations across the survey area to enable the reconstruction of a three dimensional model.

Images 422 to 531 were imported to the photogrammetry software Pix4D (version 4.6.4). The created Pix4D project is Station12Feb2021_limited.p4d, and the processing report is Station12Feb2021_limited_report.pdf.

Four three-dimensional ground control points were used to improve the positioning of the model. No two dimensional control points or check points were used.

These points were in ITRF 2000@2000 datum (UTM Zone 49S), with co-ordinates as per the table below:

Label, Type, X(m), Y(m), Z(m), Accuracy Horz(m), Accuracy Vert(M) BM05, 3D GCP, 478814.460, 2648561.910, 38.558, 0.050, 0.100 EW-05, 3D GCP, 478635.540, 2648617.260, 27.260, 0.050, 0.100 FuelFlange, 3D GCP, 478970.810, 2648642.250, 21.920, 0.050, 0.100 MeltbellFootingA, 3D GCP, 478680.270, 2648466.547, 35.850, 0.050, 0.100

BM-05 is a survey benchmark near the Casey flagpoles, see https://data.aad.gov.au/aadc/survey/display_station.cfm?station_id=600 EW-05 is a 44 gallon drum used as a groundwater extraction well by the remediation project Fuel Flange is the last fuel flange located on the elevated fuel line prior to the fuel line “dipping” under the wharf road. Meltbell footing A is a concrete footing for the Casey melt bell (surveyed in 2019/20).

No point cloud processing (e.g. removal of errant points) was done prior to orthomosaic and model generation.

The resulting orthomosaic (Station12Feb2021_limited_transparent_mosaic_group1.tif) has an average ground sampling distance of 2.9 cm, and covers an area of approximately 15.8 hectares, encompassing the majority of buildings along “main street” at Casey. The quarry, biopiles, helipad, and upper fuel farm area are all visible.

Contour lines were generated in Pix4D at 0.5 m intervals.

Due to the limited number of ground control points, and their imprecision, the estimated residual mean squared error across three dimensions is 0.17 m (17cm), and will be worse on the periphery of the imaged area.

The orthomosaic was exported from ArcGIS to a Google Earth file (CaseyStation Orthomosaic Feb 12 2021.kmz) using XTools Pro Version 17.2.

A map was created in ArcGIS showing the orthomosaic with a background showing contour lines obtained from the AADC data product windmill_is.mdb.

The map was exported in .jpg and .pdf format at 250 dpi. Casey Station Orthomosaic Feb 12 2021.pdf Casey Station Orthomosaic Feb 12 2021.jpg

The Pix4D folder structure has been copied across (with the exception of the temp folder) and is included in this dataset.

Pix4D Folder Structure:

Station12Feb2021_limited.zip 1_intitial • Contains Pix4D files created during the project • Contains the final processing report (as .pdf) 2_densification • Contains the 3D mesh as an .obj file • Contains the point cloud as a .LAS and .PLY file • Contains the point cloud as a .p4b file 3_dsm_ortho • Contains the digital surface model as a georeferenced .tif file • Contains the orthomosaic as a georeferenced .tif file

A text readable log file from the project processing is in the file Station12Feb2021_limited.log

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.

The Drone GIS Mapping market is experiencing robust growth, driven by increasing demand for high-resolution geospatial data across various sectors. The market's expansion is fueled by advancements in drone technology, offering enhanced capabilities in image capture, processing, and analysis. Applications like precision agriculture, infrastructure monitoring (construction and energy), and mining operations are significantly contributing to market expansion. The thematic mapping segment holds a substantial market share due to its wide applicability in environmental monitoring, urban planning, and disaster management. Topographic mapping is also witnessing strong growth, driven by the need for accurate elevation data in construction and infrastructure projects. While the initial investment in drones and software can be a barrier to entry for some, the overall cost-effectiveness compared to traditional surveying methods, coupled with faster turnaround times, makes drone GIS mapping increasingly attractive. North America and Europe currently dominate the market, due to higher technological adoption and established GIS infrastructure; however, rapidly developing economies in Asia-Pacific are expected to demonstrate significant growth in the coming years, particularly in regions like China and India. The market is segmented by application (energy, construction, agriculture, mining, other) and by type of mapping (thematic, topographic, cadastral, navigation, series). This segmentation highlights the diverse applications of drone GIS mapping and drives further market diversification. Competition is currently strong, with various players offering a range of services and solutions. The forecast period of 2025-2033 presents promising opportunities for market expansion. Continued technological advancements, including improved sensor technology, AI-powered data processing, and cloud-based solutions, will further enhance the efficiency and accuracy of drone GIS mapping. Government initiatives promoting digitalization and infrastructure development will also play a crucial role in driving market growth. However, challenges such as regulatory hurdles regarding drone operations and data privacy, along with the need for skilled professionals to operate and interpret the data, will need to be addressed to ensure sustained market growth. The market is poised for significant expansion, with increasing adoption across diverse sectors and regions propelling its trajectory over the forecast period. We project a strong and sustained CAGR, reflecting the combined effect of technological advancement and growing market demands.

The Drone Data Processing Software market is experiencing robust growth, driven by the increasing adoption of drones across various sectors. The market's expansion is fueled by the need for efficient and accurate analysis of the vast amounts of data generated by drone imagery. Applications range from precision agriculture, optimizing crop yields through detailed analysis of plant health and soil conditions, to infrastructure inspection, enabling quicker and safer assessments of bridges, power lines, and pipelines. The telecommunications industry leverages drone data processing for network planning and optimization, while the utilities sector employs it for efficient asset management and damage assessment. Furthermore, the oil and gas industry utilizes this technology for pipeline monitoring and environmental impact studies. The market is segmented into cloud-based and web-based solutions, catering to diverse user needs and preferences. Leading players such as DroneDeploy, Pix4D, and PrecisionHawk are driving innovation, constantly improving software capabilities and expanding their service offerings to maintain a competitive edge. Growth is also fueled by advancements in artificial intelligence (AI) and machine learning (ML), which enhance the speed and accuracy of data processing and analysis. Government initiatives promoting the use of drones for various applications, coupled with the increasing affordability of drone technology, are further contributing to the market's expansion. The market's considerable growth trajectory is projected to continue in the coming years, with a Compound Annual Growth Rate (CAGR) expected to remain significant through 2033. While the initial investment in software and expertise might pose a barrier for some businesses, the long-term cost savings and operational efficiencies gained through improved decision-making outweigh these initial hurdles. Further driving growth are ongoing improvements in processing speeds, data accuracy, and the development of user-friendly interfaces that make the software accessible to a broader range of users. Despite the rapid expansion, challenges such as data security concerns and the need for robust data management infrastructure remain areas of focus for market players and end-users alike. The geographical distribution reflects global adoption, with North America and Europe currently holding the largest market share, although Asia-Pacific is expected to experience significant growth driven by increasing infrastructure development and technological advancements.

The Geospatial Imagery Analytics System market is experiencing robust growth, driven by increasing adoption of cloud-based solutions, advancements in AI and machine learning for image processing, and rising demand across diverse sectors like agriculture, urban planning, and defense. The market size in 2025 is estimated at $15 billion, exhibiting a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This growth is fueled by the ability of geospatial imagery analytics to provide actionable insights from satellite, aerial, and drone imagery, leading to improved decision-making across various applications. The market is segmented based on various factors, and key players like Google, Trimble, and Maxar Technologies are constantly innovating to enhance their offerings and capture market share. The integration of advanced analytics capabilities is transforming the landscape, enabling more sophisticated applications like precision agriculture, infrastructure monitoring, and disaster response. Factors such as high initial investment costs and the need for skilled professionals to interpret the data can pose challenges. However, the continuous decline in data storage and processing costs, coupled with the rising availability of skilled professionals, is mitigating these restraints. The market's future prospects are promising, with increasing government investments in infrastructure projects and a rising focus on sustainable development initiatives globally further boosting demand for geospatial imagery analytics solutions. Technological advancements, particularly in the field of hyperspectral imagery and 3D modeling, are expected to further fuel market expansion in the coming years. The global reach of cloud-based platforms is also contributing to the market’s growth, making these sophisticated tools accessible to a broader user base.

Aerial Imagery System Market Outlook

The global aerial imagery system market size was valued at approximately USD 3.7 billion in 2023 and is projected to reach USD 10.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 12.3% during the forecast period. The rapid adoption of advanced technologies such as high-resolution cameras, drones, and satellite imaging is significantly contributing to the growth of this market. Increasing demand for sophisticated geospatial data in various sectors such as agriculture, defense, urban planning, and environmental monitoring is also fueling market expansion.

Various growth factors are driving the aerial imagery system market. One of the primary factors is the increasing need for high-precision and real-time data in urban planning and smart city projects. Governments and municipalities are heavily investing in aerial imagery systems to monitor infrastructure development, manage urban sprawl, and improve city planning. The integration of these systems with Geographic Information Systems (GIS) and other data analytics platforms allows for more efficient data processing and decision-making. This integration helps in creating more sustainable and efficient urban environments.

Another significant growth factor is the rising application of aerial imagery in agriculture. Farmers and agribusinesses are increasingly utilizing aerial imagery systems to monitor crop health, assess soil conditions, and optimize irrigation systems. The high-resolution images and data collected through these systems help in making informed decisions that can improve crop yields and reduce costs. Precision agriculture is becoming a critical component in modern farming, and aerial imagery systems are at the forefront of this technological advancement. As the global population continues to rise, the demand for efficient agricultural practices will further drive the market.

Moreover, advancements in drone technology and declining costs of unmanned aerial vehicles (UAVs) are making aerial imagery systems more accessible to a broader range of industries. Drones equipped with high-resolution cameras and sensors can capture detailed images and data over large areas quickly and efficiently. This capability is particularly beneficial for applications such as disaster management, where timely and accurate information is crucial. The use of UAVs in emergency response situations to assess damage, plan rescue operations, and monitor recovery efforts is becoming increasingly common, thereby bolstering the market.

In terms of regional outlook, North America currently holds the largest market share due to the presence of numerous technology companies and high adoption rates of advanced imaging systems. The region is expected to maintain its dominance throughout the forecast period. However, the Asia Pacific region is anticipated to experience the highest growth rate, driven by rapid urbanization, infrastructural development, and increasing investments in smart city projects. Countries like China, India, and Japan are leading the charge in adopting aerial imagery technologies, which will significantly contribute to the market's growth in this region.

Component Analysis

The component segmentation of the aerial imagery system market includes hardware, software, and services. The hardware segment encompasses cameras, sensors, drones, and satellite systems, which are fundamental for capturing high-quality images and data. The growing demand for high-resolution and multispectral cameras is a significant driver in this segment. These advanced cameras offer superior image quality and have become essential tools in sectors such as agriculture, environmental monitoring, and defense. Additionally, continuous innovations in sensor technologies are enabling more precise data collection, further propelling the hardware market.

On the software side, the market is witnessing substantial growth due to the increasing need for data processing, analysis, and visualization tools. Software solutions are critical for converting raw imagery data into actionable insights. Geographic Information Systems (GIS), image processing software, and data analytics platforms are some of the key components in this segment. The integration of artificial intelligence and machine learning algorithms into these software solutions is enhancing their capabilities, allowing for more accurate and efficient data interpretation. This, in turn, is d

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.

Aerial Imaging and Mapping Market Outlook

The aerial imaging and mapping market size stood at approximately USD 2.8 billion in 2023 and is anticipated to grow significantly, reaching a market size of around USD 6.1 billion by 2032, exhibiting a robust CAGR of 9.1% during the forecast period. This promising growth trajectory is primarily driven by the increasing demand for high-resolution aerial imagery and mapping solutions across various applications such as agriculture, urban planning, and infrastructure development. The growth is also supported by advancements in drone technology and the increasing integration of artificial intelligence and machine learning in mapping processes, which enhance the accuracy and utility of aerial maps.

One of the primary growth factors in the aerial imaging and mapping market is the widespread adoption of drones and unmanned aerial vehicles (UAVs) for various commercial applications. With their ability to capture high-resolution images quickly and efficiently, drones have become invaluable tools in sectors like agriculture, where they are used for monitoring crop health and optimizing irrigation. Similarly, in the construction and infrastructure sector, drones provide detailed topographical data, aiding in the planning and design phase of projects. The efficiency and cost-effectiveness of drones compared to traditional manned aircraft have significantly contributed to the expansion of the market.

The increasing importance of geographic information systems (GIS) and spatial analytics in decision-making processes is another crucial driver of market growth. Organizations across different sectors are harnessing the power of GIS to analyze and visualize spatial data, which is immensely useful in environmental monitoring, urban planning, and disaster management. The integration of aerial imagery with GIS platforms allows for more accurate and insightful analyses, driving the demand for aerial imaging services. Moreover, the advent of cloud-based GIS solutions has further facilitated the accessibility and usability of aerial mapping data, making it easier for organizations to leverage this technology for strategic planning and operational efficiency.

Technological advancements in imaging sensors and software are also playing a pivotal role in the growth of the aerial imaging and mapping market. The development of high-resolution cameras and advanced sensors capable of capturing detailed images from varying altitudes has expanded the applicability of aerial mapping. Additionally, sophisticated software solutions that process and analyze aerial data are enabling users to derive actionable insights with greater accuracy and speed. The integration of machine learning algorithms for image recognition and analysis further enhances the value proposition of aerial imaging solutions, making them indispensable tools for a wide range of industries.

The integration of Digital Elevation Model (DEM) technology has significantly enhanced the capabilities of aerial imaging and mapping. DEMs provide a 3D representation of a terrain's surface, offering detailed insights into elevation changes and topographical features. This technology is particularly beneficial in applications such as flood risk assessment, where understanding the terrain's elevation is crucial for predicting water flow and potential flood zones. By incorporating DEMs into aerial mapping processes, organizations can achieve more accurate and comprehensive analyses, supporting better decision-making in urban planning, infrastructure development, and environmental management. The ability to visualize and analyze elevation data in conjunction with high-resolution imagery further strengthens the utility of aerial mapping solutions across various sectors.

Regionally, North America currently dominates the aerial imaging and mapping market, attributed to the presence of major market players and the early adoption of advanced technologies in the region. The market here is supported by a strong regulatory framework and substantial investments in research and development. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, driven by rapid urbanization and infrastructural development in countries like China and India. Government initiatives to promote the use of drones and UAVs for various applications are also contributing to market expansion in this region. Meanwhile, Europe remains a significant market due to its advanced technological infrastructure and the presence of key industries utilizing

The global digital mapping aerial photography market is experiencing robust growth, driven by increasing demand for precise geospatial data across diverse sectors. The market, valued at approximately $5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033. This expansion is fueled by several key factors, including the proliferation of high-resolution sensors and drones, advancements in image processing and analysis techniques, and the rising adoption of cloud-based solutions for data storage and processing. Furthermore, the increasing need for accurate mapping in urban planning, infrastructure development, agriculture, and environmental monitoring contributes significantly to market growth. The integration of artificial intelligence (AI) and machine learning (ML) is further accelerating the automation of data processing and analysis, improving efficiency and reducing costs. Major players like Vexcel Imaging, Leica Geosystems, and Teledyne Optech are driving innovation through the development of advanced sensor technologies and software solutions. However, the market also faces certain challenges. High initial investment costs associated with specialized equipment and software can be a barrier to entry for smaller players. Data security and privacy concerns, along with the need for skilled professionals to operate and analyze data, also pose limitations. Nevertheless, the ongoing technological advancements and the increasing demand for precise geospatial data are expected to outweigh these challenges, ensuring continued market expansion in the coming years. The segmentation of the market by type of sensor (e.g., LiDAR, RGB), application (e.g., agriculture, urban planning), and region will further contribute to defining the market landscape and potential growth opportunities. This detailed understanding of market dynamics empowers stakeholders to make informed business decisions and capitalize on emerging trends.

This collection contains 2 2022 1-centimeter RGB (red, green, blue) orthorectified image of two study site within and near the 2013-Pony Complex wildfire boundary Near Mountain Home, Idaho. These data were acquired on June 15, 2022. These data are sourced from US NSF Idaho EPSCOR.These data are part of a larger collection (README.txt) of UAS imagery data and data products which includes raw RGB (red, green, blue) and multispectral (5-band) digital imagery and processed data products (dense point cloud, orthophoto, DSM) collected 2022-06-15 from two sites within the 2013-PONY COMPLEX wildfire boundary (FireCode: ID4329411554820130809, Welty and Jeffries 2020) near Mountain Home Idaho. We used a DJI Mavic 2 Pro with Hasselblad 20MP sensor (RGB) with Map Pilot Pro software and DJI Phantom 4 Multispectral sensor (5 band) with DJI GS Pro software to capture imagery over the area of interest. The RGB (Red, Green, Blue) imagery was collected in a crossgrid pattern (20 degree offset) at 44m above ground level; the resulting imagery have a ground resolution of 1.0cm/pixel. The multispectral imagery was collected at 38m above ground level (no crossgrid pattern); the resulting imagery have a ground resolution of 2.0cm/pixel. The images were processed and the products were created in OpenDroneMap version 2.8.8. All products are georectified and in WGS84 UTM Zone 11 N.Recommended Citation: Marie, V., Zaiats, A., Roser, A., Olsoy, P., Delparte, D., Wickersham, R., & Caughlin, T. T. (2023). Digital aerial imagery (RGB and multispectral) from the 2013-PONY COMPLEX wildfire boundary near Mountain Home Idaho USA-2022 [Data set]. University of Idaho. https://doi.org/10.7923/AEZG-KD35Ancillary ODM Workflow: Marie, V., Zaiats, A., Wickersham, R., & Caughlin, T. T. (2023). Open Drone Map: Structure-from-Motion Workflow (Version 1.0). University of Idaho. https://doi.org/10.7923/92HF-GP09Ancillary Fire Dataset: Welty, J.L., and Jeffries, M.I., 2020, Combined wildfire datasets for the United States and certain territories, 1878-2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9Z2VVRTFunding:US National Science Foundation Idaho EPSCoR, Award: OIA-1757324US National Science Foundation, Award: BIO-2207158National Aeronautics and Space Administration, Award: 80NSSC21K1638Individual image tiles can be downloaded using the Idaho Imagery Explorer.These data can be bulk downloaded from a web accessible folder.Data are sourced from: https://doi.org/10.7923/AEZG-KD35

This collection contains 2 2022 1-centimeter RGB (red, green, blue) orthorectified image of two study site within the 2015-Soda wildfire boundary along the Oregon/Idaho border. These data were acquired on June 30, 2022. These data are sourced from US NSF Idaho EPSCOR.These data are part of a larger collection (README.txt) of UAS imagery data and data products which includes raw RGB (red, green, blue) and multispectral (5-band) digital imagery and processed data products (dense point cloud, orthophoto, DSM) collected 2022-06-30 from two sites within the 2015-SODA wildfire boundary (FireCode: ID4311811696020150810, Welty and Jeffries 2020) spanning the Oregon/Idaho border adjacent to US Highway-95. We used a DJI Mavic 2 Pro with Hasselblad 20MP sensor (RGB) with Map Pilot Pro software and DJI Phantom 4 Multispectral sensor (5 band) with DJI GS Pro software to capture imagery over the area of interest. The RGB (Red, Green, Blue) imagery was collected in a crossgrid pattern (20 degree offset) at 44m above ground level; the resulting imagery have a ground resolution of 1.0cm/pixel. The multispectral imagery was collected at 38m above ground level (no crossgrid pattern); the resulting imagery have a ground resolution of 2.0cm/pixel. The images were processed and the products were created in OpenDroneMap version 2.8.8. All products are georectified and in WGS84 UTM Zone 11 N. Recommended Citation: Marie, V., Zaiats, A., Roser, A., Olsoy, P., Delparte, D., Wickersham, R., & Caughlin, T. T. (2023). Digital aerial imagery (RGB and multispectral) from the 2015-SODA wildfire boundary near the Oregon/Idaho border USA-2022 [Data set]. University of Idaho. https://doi.org/10.7923/59M8-5S68Ancillary ODM Workflow: Marie, V., Zaiats, A., Wickersham, R., & Caughlin, T. T. (2023). Open Drone Map: Structure-from-Motion Workflow (Version 1.0). University of Idaho. https://doi.org/10.7923/92HF-GP09Ancillary Fire Dataset: Welty, J.L., and Jeffries, M.I., 2020, Combined wildfire datasets for the United States and certain territories, 1878-2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9Z2VVRTAdditional SODA1 Aerial Imagery Data (2019, 2020 & 2021)Roser, A., Marie, V., Olsoy, P., Delparte, D., & Caughlin, T. T. (2022). Unoccupied aerial systems imagery from the Soda Fire Natural Area Idaho (Version 1.0) [Data set]. University of Idaho. https://doi.org/10.7923/VCAP-4128Funding:US National Science Foundation Idaho EPSCoR, Award: OIA-1757324US National Science Foundation, Award: BIO-2207158National Aeronautics and Space Administration, Award: 80NSSC21K1638Individual image tiles can be downloaded using the Idaho Imagery Explorer.These data can be bulk downloaded from a web accessible folder.Data are sourced from: https://doi.org/10.7923/59M8-5S68

The drone surveying software market is experiencing robust growth, driven by increasing adoption across diverse sectors like agriculture, municipal affairs, mining, and construction. The market's expansion is fueled by several key factors: the rising need for efficient and accurate data acquisition, advancements in drone technology offering higher resolution imagery and improved data processing capabilities, and the decreasing cost of drone hardware and software. Furthermore, the integration of AI and machine learning in drone surveying software is enhancing data analysis speed and accuracy, leading to quicker project completion times and cost savings. The cloud-based segment is witnessing significant traction due to its scalability, accessibility, and collaborative features. While the on-premise segment retains a considerable market share, the cloud-based offering is projected to surpass it in the coming years, driven by the increasing preference for remote data access and reduced infrastructure costs. Competition is fierce, with established players like Autodesk and Esri UK alongside specialized drone surveying software companies like DroneDeploy and Pix4D vying for market share. Geographic expansion, particularly in developing economies experiencing rapid infrastructure development, presents significant opportunities for market growth. However, challenges remain, including regulatory hurdles surrounding drone usage, data security concerns, and the need for skilled professionals capable of operating and interpreting drone surveying data. Looking ahead, the market's trajectory suggests sustained growth over the next decade, propelled by technological innovations and widening applications. The continued refinement of AI-powered analytics within drone surveying software will significantly reduce manual processing, allowing for quicker turnaround times and cost efficiency. The integration of 3D modeling capabilities and advanced data visualization tools are key advancements pushing market adoption. Regional variations in growth will depend on the pace of technological adoption and the regulatory environment in each region. North America and Europe are currently leading the market, but the Asia-Pacific region is projected to witness significant growth in the coming years due to the expansion of infrastructure projects and increasing adoption of advanced technologies. The overall market is poised for a period of sustained growth, driven by increasing demand and ongoing technological improvements.

TThis collection contains 1 2022 1-centimeter RGB (red, green, blue) orthorectified image of a study site within the 1988-Stewart and 1996-Eighth Street wildfire boundaries near Boise, Idaho. These data were acquired on June 29, 2022. These data are sourced from US NSF Idaho EPSCOR.These data are part of a larger collection (README.txt) of UAS imagery data and data products which includes raw RGB (red, green, blue) and multispectral (5-band) digital imagery and processed data products collected 2022-06-29 within the lower Dry Creek watershed within the 1988-STEWART and 1996-EIGHTH STREET wildfire boundaries (FireCode: ID4368311615219880802 and ID4366611613519960826, respectively, Welty and Jeffries 2020) near Boise Idaho, approximately 20 minutes from Boise off Bogus Basin Road. We used a DJI Mavic 2 Pro with Hasselblad 20MP sensor (RGB) with Map Pilot Pro software and DJI Phantom 4 Multispectral sensor (5 band) with DJI GS Pro software to capture imagery over the area of interest. The RGB (Red, Green, Blue) imagery was collected in a crossgrid pattern (20 degree offset) at 44m above ground level; the resulting imagery have a ground resolution of 1cm/pixel. The multispectral imagery was collected at 38m above ground level (no crossgrid pattern); the resulting imagery have ground resolution of 2cm/pixel. The images were processed and the products were created in OpenDroneMap version 2.8.8. All products are georectified and in WGS84 UTM Zone 11 N.Recommended Citation: Marie, V., Zaiats, A., Roser, A., Olsoy, P., Delparte, D., Wickersham, R., & Caughlin, T. T. (2023). Digital aerial imagery (RGB and multispectral) from within the lower Dry Creek watershed near Boise Idaho USA-2022 [Data set]. University of Idaho. https://doi.org/10.7923/ZS2V-7B04Ancillary ODM Workflow: Marie, V., Zaiats, A., Wickersham, R., & Caughlin, T. T. (2023). Open Drone Map: Structure-from-Motion Workflow (Version 1.0). University of Idaho. https://doi.org/10.7923/92HF-GP09Ancillary Fire Dataset: Welty, J.L., and Jeffries, M.I., 2020, Combined wildfire datasets for the United States and certain territories, 1878-2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9Z2VVRTFunding:US National Science Foundation Idaho EPSCoR, Award: OIA-1757324US National Science Foundation, Award: BIO-2207158National Aeronautics and Space Administration, Award: 80NSSC21K1638Individual image tiles can be downloaded using the Idaho Imagery Explorer.These data can be bulk downloaded from a web accessible folder.Data are sourced from: https://doi.org/10.7923/ZS2V-7B04

The commercial drone software market is experiencing robust growth, driven by increasing adoption across diverse sectors like agriculture, construction, and infrastructure. The market's expansion is fueled by several key factors: the decreasing cost of drone hardware, advancements in software capabilities (particularly in areas like autonomous flight, data processing, and analytics), and a growing need for efficient and cost-effective data acquisition and analysis. This software is critical for transforming raw drone imagery into actionable insights, enabling better decision-making and operational efficiency. We estimate the 2025 market size to be around $2.5 billion, with a Compound Annual Growth Rate (CAGR) of 15% projecting a market value exceeding $6 billion by 2033. This growth is further bolstered by the increasing availability of user-friendly software, catering to a broader range of users, including those without extensive technical expertise. However, challenges remain, including data security concerns, regulatory hurdles surrounding drone operations, and the need for robust software integration with existing workflows. The competitive landscape is dynamic, featuring both established players and innovative startups. Key players such as Kespry, DroneDeploy, and Pix4D are leading the way with comprehensive software solutions. However, the market is also witnessing the emergence of niche players focusing on specific industry applications, leading to increased competition and innovation. Future growth will depend on continued advancements in artificial intelligence (AI) and machine learning (ML) integration within the software, allowing for automated data analysis and more sophisticated insights. Furthermore, the development of standardized data formats and interoperability between different software platforms will be critical for market expansion and wider adoption. The integration of cloud-based solutions will also play a significant role, facilitating data storage, processing, and collaboration.

The aerial imaging and mapping market is experiencing robust growth, driven by increasing demand across diverse sectors. Government agencies leverage aerial imagery for infrastructure monitoring, urban planning, and disaster response. The military and defense sectors utilize it for surveillance, reconnaissance, and target acquisition. The energy sector employs aerial mapping for pipeline inspection, oil and gas exploration, and renewable energy site assessment. Precision agriculture relies heavily on aerial imagery for crop monitoring, yield prediction, and efficient resource management. Civil engineering projects benefit from detailed topographic surveys and 3D modeling facilitated by aerial mapping, while commercial enterprises use it for real estate assessments, construction progress monitoring, and insurance risk assessment. Technological advancements, such as improved sensor technology (including hyperspectral and LiDAR), enhanced drone capabilities, and sophisticated data processing software, are key drivers of market expansion. The rising adoption of cloud-based solutions for data storage and analysis further contributes to this growth. While data privacy concerns and regulatory hurdles present some restraints, the overall market outlook remains positive, with a projected continued rise in demand across various applications and regions. The market segmentation reveals a dynamic landscape. Unmanned aerial vehicles (UAVs or drones) are gaining significant traction due to their cost-effectiveness and accessibility, while helicopters and fixed-wing aircraft remain crucial for large-scale projects requiring greater payload capacity and range. North America and Europe currently hold substantial market shares, attributed to advanced technological infrastructure and high adoption rates. However, the Asia-Pacific region demonstrates considerable growth potential, fueled by rapid urbanization, infrastructure development, and increasing government investments in mapping and surveying initiatives. Key players in the market are continuously innovating to offer advanced solutions, driving competition and further fueling market growth. The projected CAGR, though not explicitly provided, is likely in the range of 8-12% based on industry trends and the rapid technological advancements in this sector. This signifies a significant opportunity for companies operating in this space.

The drone analytics software market is experiencing robust growth, driven by increasing adoption across diverse sectors. The market, estimated at $2.5 billion in 2025, is projected to expand significantly over the forecast period (2025-2033), fueled by a Compound Annual Growth Rate (CAGR) of approximately 18%. This growth is primarily attributable to several key factors. Firstly, the decreasing cost and improving capabilities of drones themselves make them more accessible to a wider range of users, from large enterprises to small businesses. Secondly, the sophistication of analytics software continues to advance, offering more insightful data processing and visualization tools for applications spanning agriculture, construction, infrastructure inspection, and environmental monitoring. Finally, the increasing demand for efficient data-driven decision-making across industries is driving investment in drone analytics solutions, promoting innovation and further market expansion. The market's growth is not without its challenges. Data security and privacy concerns represent a significant restraint, particularly as drone usage expands in sensitive sectors. Regulatory hurdles and variations in regulations across different geographies also pose obstacles to market penetration. Nevertheless, the ongoing advancements in artificial intelligence (AI) and machine learning (ML) for data analysis are expected to mitigate some of these challenges, enabling more accurate, efficient, and secure data processing. The market is segmented based on software type (cloud-based, on-premise), application (agriculture, construction, etc.), and deployment model. Key players like Scopito, DroneDeploy, Verizon, Esri, Kespry, Scanifly, Skymatics, PrecisionHawk, Propeller Aero, and Delair are actively competing to capture market share through innovation and strategic partnerships, further shaping the market's trajectory.

The drone mapping software market is experiencing robust growth, driven by increasing demand across diverse sectors like agriculture, construction, and infrastructure. The market's expansion is fueled by several key factors: the declining cost of drones, advancements in software capabilities (including AI-powered image processing and 3D modeling), and the rising need for efficient and accurate data acquisition for various applications. The market is segmented by software type (e.g., photogrammetry, LiDAR processing), deployment mode (cloud-based, on-premise), and end-user industry. While the precise market size for 2025 is unavailable, considering a typical CAGR of 15-20% in the technology sector and a base year (2025) we can reasonably estimate the market size to be around $800 million USD. We project this figure to grow significantly over the forecast period (2025-2033), reaching potentially $2.5 Billion to $3 Billion USD by 2033, depending on various macroeconomic factors. Major players like Airware, 3D Robotics, and DroneDeploy are actively shaping the market landscape through continuous innovation and strategic partnerships. However, challenges such as regulatory hurdles, data security concerns, and the need for skilled professionals to operate and interpret the data remain. The market is expected to witness increasing consolidation as larger companies acquire smaller players, leading to a more concentrated competitive environment. Future growth will be significantly impacted by the development and integration of advanced technologies such as AI-based automation and improved integration with other GIS and data management systems. The continued adoption of drone mapping software will be largely determined by its ability to offer cost-effective and time-saving solutions compared to traditional surveying methods, ultimately increasing efficiency and productivity across various industries.