Drones Flying Free 2017 Recap: Essential Equipment and Software for GIS & Remote Sensing

Drone Hardware: What You Need to Get Started

Unmanned aerial vehicles (UAVs), commonly known as drones, have revolutionized spatial data collection in recent years by offering flexible, low-cost platforms for aerial imagery and remote sensing. For professionals and enthusiasts looking to begin drone-based GIS or mapping work, it’s critical to select the right aircraft. Common choices include multirotor platforms like the DJI Phantom and Mavic series for stable, high-quality imagery, as well as fixed-wing drones for longer flight times and broader coverage. Drones vary in payload capacity, flight duration, and sensor support — all of which influence the quality and type of spatial data you can collect.

Many applications in remote sensing require more than RGB cameras. Drones can be equipped with specialized sensors such as multispectral, hyperspectral, thermal, and LiDAR modules to support vegetation analysis, surface temperature mapping, and three-dimensional terrain modeling. Matching your choice of sensor with your project goals ensures you capture data with the detail and accuracy your analysis demands. Selecting a drone with easy integration and interchangeable payloads will let you adapt as your remote sensing needs evolve.

Software Tools for Processing & Analysis

Once you have captured aerial imagery, processing that data is equally important. Software tools turn raw photos and sensor data into usable products such as orthomosaics, digital elevation models (DEMs), and geographic feature datasets. Popular open-source and commercial options include Pix4D, Agisoft Metashape, DroneDeploy, and QGIS with plugins for photogrammetry and GIS workflows. These platforms support automated structure-from-motion (SfM) processing, orthophoto generation, and 3D reconstruction, which are foundational for most drone GIS projects.

For advanced remote sensing analysis, applications like ENVI or ArcGIS Pro provide powerful capabilities for spectral classification, terrain analysis, and machine learning-based interpretation of multispectral or hyperspectral drone data. Many modern tools also integrate cloud-based processing to handle large datasets efficiently and support collaborative workflows. Choosing software that scales with your project’s complexity helps streamline work from data capture to final deliverables.

Integration into GIS Workflows

One of the most valuable aspects of drone data collection is its ability to integrate seamlessly into existing GIS systems. After processing aerial imagery into georeferenced outputs, these products can be incorporated into mainstream GIS platforms like ArcGIS or QGIS to perform spatial analysis, mapping, and reporting. This interoperability enables practitioners to blend drone-captured datasets with ground control points, cadastral maps, elevation layers, and other geospatial information. Integration also supports decision-making in fields such as urban planning, agriculture, disaster management, and environmental monitoring.

Best Practices and Tips

Operating drones for GIS and remote sensing also requires careful planning and adherence to best practices. Ensuring flight safety, understanding local regulations for UAV operations, and performing regular maintenance on hardware are all essential steps to protect equipment and data quality. Using ground control points (GCPs) and accurate GPS data improves the spatial accuracy of your results. It’s also important to calibrate sensors and validate outputs against reference data to ensure analytical reliability. Following robust workflows will help you produce high-quality, defensible spatial products that support professional geospatial objectives.