Background

Due to their 24/7 observation capabilities, SAR data are relevant for a broad range of applications in environmental monitoring and emergency response. However, identifying changes in images with complex content is difficult, as the image content often masks the signatures of change. A simple and highly effective change detection approach is the so-called log-ratio scaling method. It is based on a differential analysis of repeated images and has shown to be effective in background suppression and change features enhancement.

Prerequisites

Materials List:

• Windows PC
• Two RTC images
  • Options to obtain images:
    • Download and unzip samples images Image 1 and Image 2 
    • Download and unzip RTC ALOS PALSAR images using Vertex
    • Process RTC images using Sentinel data
• ArcMap (ArcMap 10.4 was used in the recipe)

Note: To identify RTC images suitable for change detection, ensure images are from the same season. This is important for change detection operations as it avoids seasonal changes and focuses on true environmental changes in a change detection analysis.

Steps

Load Data

1. Open ArcMap 
2. Ensure that the Spatial Analyst Extension is enabled by navigating to Customize > Extensions and select Spatial Analyst
3. Import the two RTC images into the Data Frame using Add Data function
   1. In the top menu, navigate to File > Add Data and click on Add Data
   2. Select the HH polarization

Note: Do not create Pyramids when prompted.

Example Image

The resulting log-ratio image over Huntsville, Alabama, was created from a pair of images acquired on 7/17/2009 and 9/04/2010, approximately one year apart. As the data are seasonally coordinated, differences between the images should largely be due to environmental changes between the image acquisition times, such as urban development, changes in river flow, or differences in agricultural activity.

It can be seen that most of the original image content (city of Huntsville, hills and vegetation structures near town, etc.) was effectively suppressed from the image. In the log-ratio image, unchanged features have intermediate gray tones (gray value around zero) while change features are either bright white or dark black. Black features indicate areas where radar brightness decreased while in white areas, the brightness has increased.