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The Power of Combining Information from SAR and Imagery

Jason Wolfe

While optical imagery is a critical component of geospatial analysis, it’s limited by cloud cover and darkness. SAR transcends these limitations by penetrating haze, clouds, and smoke, and by capturing data both day and night. In addition, SAR can provide information not easily obtained with other data sources. By combining SAR with optical imagery, you can ensure comprehensive image data analysis.

Enhance Your Analysis with ENVI SAR Essentials

With the release of ENVI® SAR Essentials, integrating Synthetic Aperture Radar (SAR) data into your ENVI workflows has never been easier. This new toolset empowers users to seamlessly process and analyze both SAR data and optical imagery within ENVI to create powerful, value-added products. In this blog, I will highlight a couple examples -- showing how ENVI SAR Essentials can provide additional insights and unprecedented accuracy to land-cover classification and terrain characterization.

Land-cover Classification – Achieve Greater Accuracy

Incorporating SAR and multispectral data can significantly improve the accuracy of land-cover classification. SAR sensors capture surface roughness, texture, and soil moisture – details that optical imagery alone cannot provide.

Experiment Highlights

Without SAR: Using spectral data only, I performed a Minimum Distance supervised classification on a Sentinel-2 image with thirteen visible-to-shortwave infrared bands and achieved an overall accuracy of 78.6%.

 

With SAR: By adding two Sentinel-1 magnitude SAR images (VV and VH polarizations) to the Sentinel-2 dataset and processing it with ENVI SAR Essentials, the overall accuracy increased to 95.7%. Radar signals reflect and scatter differently with vegetation, flat surfaces, wet soils, tall structures, and other materials. Thus, SAR magnitude images can help distinguish between different surface types, making image data analysis even more precise for applications like land-cover classification.

Terrain Characterization: Unveil Hidden Features

SAR’s phase component is invaluable for characterization of local terrain. By using overlapping SAR datasets with similar acquisition geometries, you can generate detailed Digital Surface Models (DSMs), which cannot be created with optical data alone.

Example Workflow:

DSM Creation: Using the SAR DSM Generation workflow in ENVI SAR Essentials, two overlapping Umbra scenes of Iran (Single Look Complex datasets) were processed. These scenes had ascending orbits, VV polarization, and similar incidence and azimuth angles.

Resulting DSM:

Topographic Shading:
The ENVI Topographic Shading tool was used to create a shaded-relief image from the DSM.

Contour Mapping:
Contour lines were plotted on the DSM for detailed terrain analysis.

Viewshed Analysis:
Using the DSM with the Viewshed Tool, areas visible (green) and hidden (red) from a point atop a hill were revealed.

Seamless Integration for Enhanced Analysis

Output products created with ENVI SAR Essentials can be further exploited with ENVI’s analytical tools, enhancing your image data analysis with advanced capabilities. Installed directly with ENVI, ENVI SAR Essentials ensures that all processing is done within one application, which streamlines your workflow and increases efficiency

By integrating SAR and optical imagery into your analysis, you unlock new dimensions of geospatial intelligence, making your data more comprehensive and actionable. Explore the possibilities of ENVI SAR Essentials and elevate your analytical capabilities.