How to Combine Drone Imagery With Satellite Data for Large-Scale Mapping Projects
- Anvita Shrivastava
- 1 day ago
- 5 min read
Organizations are using drones and satellite imagery together, as geomapping technology continues to grow and evolve. The use of drone and satellite data will enable accurate, scalable, and cost-efficient geomapping. Organizations that use drones and/or satellite imagery can increase detail and coverage, regardless of the type of land or infrastructure they manage (i.e., farm fields, roads, bridges, etc.), or whether they are monitoring/assessing environmental conditions.
Why Combine Drone Imagery and Satellite Data?
Expanded Geographic Coverage
Satellite imagery offers a broad view of geographic areas covering a region, state, country, or even continent. Drones can obtain highly detailed images of a much smaller geographic area. Combining these technologies allows for detailed assessments of large-scale geographic areas.
Improved Detection and Visualization
Satellite imagery provides a good overview of an area, while drone imagery provides extremely high-resolution images of objects and environments within the area. When combined, satellite and drone imagery allow analysts to see the larger trends of an area down to the minute details of features such as cracks in roads, tree stress, or defective infrastructure.
Reduced Cost and Time to Conduct Analyses
Drone mapping of very large geographic areas can take a considerable amount of time and can also be quite expensive. Satellite imagery helps bridge the gaps in coverage of drone flights, thereby reducing the need for drone flights in the overall analysis process.
Improved Historical Data Review
Satellite imagery allows for the viewing and analysis of several years of historical imagery, thereby allowing for temporal trend analysis. Drone collections produce current images that can validate or modify the analyses of historical satellite-based collections.
Key Steps for Integrating Drone Imagery With Satellite Data
Determine Map Objectives
Before deploying drones or acquiring satellite data, clarify your project goals:
Do you need to track land-use changes?
Are you monitoring crop health?
Is the focus on infrastructure inspection or disaster assessment?
Clear objectives help determine the appropriate resolution, frequency, and data types required.
Choose Appropriate Satellite Data
The type of satellite imagery you use will depend on the level of detail required, the frequency of repeat visits to the same location, and your budget.
Among the most common types of satellite imagery are:
Free data- Landsat, Sentinel-2
Commercial high-resolution data- Maxar, Planet, Airbus
The following factors are important when selecting the right satellite data:
Spectral bands- (multispectral, hyperspectral)
Spatial resolution- (10m to 30cm; or finer resolution)
Temporal resolution- (daily to bi-weekly refresh)
Obtain High-Resolution UAV Imagery
Drones can collect imagery tailored to your project:
RGB for visual inspection
Multispectral for vegetation and environmental monitoring
Thermal for energy audits or water stress detection
LiDAR for elevation modeling
Ensure your drone flights meet mapping standards:
Adequate overlap (70–80% forward, 60–70% side)
Consistent altitude for uniform resolution
Proper ground control points (GCPs) for georeferencing
Preprocessing the Two Datasets
The datasets from both drones & satellites need to be preprocessed into a single format & reference system before the two types of data can be fused.
Some of the more common ways to preprocess data:
Correction of Radiometric & Geometric Errors
Orthorectification
Noise Reduction
Alignment with a common Coordinate System (e.g., WGS84 or UTM)
Merge data within GIS/Remote Sensing software.
There are several GIS/Remote Sensing applications available to assist with the merging of drone & satellite data:
Some of the more popular programs include:
ArcGIS Pro
ENVI
ERDAS IMAGINE
Pix4D
Agisoft Metashape
Common data fusion techniques include:
Layer stacking: Use of drone imagery as an overlay on the satellite base map.
Pan sharpening: Improves the spatial resolution of satellite images with the help of drone image data.
Data fusion algorithms: Create new multi-spectral images from a combination of drone and satellite images, as well as providing means to combine spatial features with spectral features.
Machine learning models: Detect objects, classify land types, segment features.
Build Composite Maps and Analytics
Once the data is fused, you can generate:
Orthomosaics in detail
Digital elevation models/digital terrain models (DEMs/DTMs) with a high level of accuracy
Vegetation indices (NDVI/SAVI)
Change detection maps
Infrastructure condition assessments
Land-use/land-cover (LULC) classifications
Combining this set of data allows for better decision-making over large areas.
Best Practices for Accurate and Scalable Results
Ground Control Points (GCPs) are used to adjust the geographical information for drone imagery to fit the geographical coordinates of an existing satellite image.
All of the necessary travel and environmental conditions related to your drone's data must be noted in your recordings. The following should be documented:
Date and Time of Acquisition
Coordinate Reference System
Sensor Used
Resolution
Flight Conditions
Drones create very large amounts of digital information. The recommended method for creating this data and storing it is to use:
Cloud Storage Services such as Amazon S3, Google Cloud, Microsoft Azure
Cloud-Native Geospatial Formats: Cloud Optimized GeoTIFF, Parquet, STAC
Create Automation for the common mapping tasks you will perform; these tasks are best automated prior to fieldwork or flying a drone.
Use the following programming platforms for the automation of your pre- and post-processing Workflows:
Python (GDAL, Rasterio, GeoPandas)
Google Earth Engine
Esri ModelBuilder
Validate Outputs
Perform accuracy assessments such as:
Confusion matrices for classification
RMSE calculations for elevation models
On-site inspections for critical infrastructure
Use Cases for Combined Drone + Satellite Mapping.
Agricultural Monitoring
Using a combination of a high-resolution drone obtained NDVI (Normalized Difference Vegetation Index) imagery and satellite-derived multispectral baseline images results in better early identification of crop stressors and optimization of irrigation.
Forestry Monitoring and Environmental Assessment
Satellite imagery can be used to identify large-scale deforestation, whereas drone imagery can assess small-scale disturbance events and provide information on wildlife habitat conditions.
Construction Monitoring and Infrastructure Assessment
Satellites provide a regional view of infrastructure, such as roads, pipelines, and power transmission lines, while drones provide detailed inspections.
Disaster Response
Satellite imagery can provide immediate pre- and post-disaster views, while drone imagery can provide ultra-high-resolution images for search, damage, and emergency response assessments.
The combination of drone-supplied imagery and satellite-supplied imagery will yield the most comprehensive large-scale mapping capability. Satellite data can provide large area data combined with the historical database of the same area, while drone-supplied imagery will provide extremely high-resolution data. Through the use of advanced image data merging techniques, such as Pre-processing (processing before using) and Geographic Information Systems (GIS), this combined imagery can provide a rich, usable dataset for effective decision-making in every type of industry.
By integrating and utilizing drone imagery with satellite imagery, organizations can achieve the level of detail and scale needed for both large area mapping as well as critical infrastructure assessment.
For more information or any questions regarding the drone imagery and satellite data, please don't hesitate to contact us at:
Email:
USA (HQ): (720) 702–4849
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