Remote Sensing and Imagery Analysis is one of the powerhouse capabilities in GIS, and ArcGIS Pro offers a strong suite of tools for working with satellite, aerial, and drone imagery. Let’s break this down, and you can tell me what part you’re most interested in.
What is Remote Sensing in GIS?
It’s the process of acquiring information about the Earth’s surface without direct contact — typically through sensors on satellites, aircraft, or drones — and analyzing that imagery data for environmental monitoring, land use mapping, agriculture, disaster management, and more.
In ArcGIS Pro, this typically involves:
- Managing large imagery datasets
- Performing image classification
- Conducting change detection
- Extracting features
- Conducting raster and spectral analysis
Types of Imagery You Can Work With:
| Data Type | Examples |
|---|---|
| Satellite Imagery | Landsat, Sentinel-2, MODIS, WorldView |
| Aerial Photography | Orthophotos, NAIP imagery |
| Drone Imagery | Processed orthomosaics, DSMs, point clouds |
| Multispectral / Hyperspectral Data | Landsat 8 bands, AVIRIS, Sentinel MSI |
| Thermal Imagery | Landsat TIR, drone-based thermal images |
Core Imagery Tools in ArcGIS Pro:
| Task | Tool / Capability |
|---|---|
| Image Classification | Image Classification Wizard, Train Support Vector Machine Classifier |
| Change Detection | Change Detection Wizard, Raster Calculator |
| Band Combinations | Custom band composites for highlighting features |
| Vegetation Analysis | NDVI, SAVI, MSAVI via Raster Function or Raster Calculator |
| Orthomapping | Drone imagery processing |
| Supervised/Unsupervised Classification | Using training samples or clustering |
| Image Enhancement | Stretching, sharpening, filtering |
| Raster Analysis | Zonal statistics, surface analysis |
| Time Series Analysis | Working with image time slices to detect changes |
Example: Create a Normalized Difference Vegetation Index (NDVI)
Formula:NDVI = (NIR - Red) / (NIR + Red)
Workflow:
- Add multispectral imagery (e.g., Landsat 8)
- Open the Raster Calculator
- Enter the NDVI formula using appropriate band names: pythonCopyEdit
("Band5" - "Band4") / ("Band5" + "Band4") - Save output raster and apply a colormap for visualization.
Image Classification Types:
| Type | Description |
|---|---|
| Supervised | You define training areas for known land cover types. |
| Unsupervised | The software clusters pixels into groups based on spectral similarity. |
| Object-based | Segments image into objects before classification (via Image Analyst extension). |
Pro Tips:
- Use Raster Functions for real-time, on-the-fly image processing without creating new rasters.
- Integrate ArcGIS Image Analyst extension for advanced tools like object detection, stereo mapping, and multidimensional analysis.
- Use Mosaic Datasets to manage large collections of imagery efficiently.
- For drone data, use Orthomapping Workspace for stitching and 3D products.
- Perform cloud masking and atmospheric correction on satellite imagery before analysis for best results.
Advanced Remote Sensing Workflows:
- Time series NDVI trend analysis
- Burn scar mapping using NBR (Normalized Burn Ratio)
- Urban sprawl detection
- Change detection using Image Difference / Image Ratio
- Water body extraction using NDWI
Supported Sensors and Imagery in ArcGIS:
- Landsat, Sentinel-2
- NAIP, WorldView
- PlanetScope, SkySat
- Drone imagery (processed into orthomosaics)
- Thermal and LiDAR
