This NASA data recipe by the Alaska Satellite Facility DAAC walks users through viewing Radiometrically Terrain-Corrected (RTC) images in ArcGIS.

Users can request RTC products On Demand in ASF's Vertex data portal, or make use of our Python SDK or API. SAR datasets inherently contain geometric and radiometric distortions due to terrain being imaged by a side-looking instrument.

Dec 3, 2024 · Terrain correction moves image pixels into the proper spatial relationship with each other. Radiometric terrain correction combines both corrections to produce a superior product for science applications.

Terrain correction is correcting geometric distortions introduced by side-looking radar imaging that lead to geolocation errors. These distortions are compounded by rugged terrain. Terrain correction moves image pixels into the proper spatial relationship with each other and the ground.

Dec 3, 2024 · This NASA data recipe from the Alaska Satellite Facility is for users who wish to generate an RTC image from Sentinel-1 data using easy-to-follow instructions in a graphical user interface (GUI). This recipe was written for version 8 of the SNAP Sentinel-1 Toolbox (S1TBX).

RTC30-Color: RGB compositions of from dual-pol (VV/VH) Sentinel-1 SAR RTC image products provided at 30 m resolution. CCD30: Change detection products relative to the first image of an event subscription (30 m resolution).

This data recipe is for users who wish to generate an RTC image from Sentinel-1 data using easy-to-follow instructions in a graphical user interface (GUI). This recipe was written for version 7 of the SNAP Sentinel-1 Toolbox.

This data recipe is for users who wish to view an RTC image in QGIS. The standard output of the RTC process is a gamma0 power image. This format supports statistical assessments of the data. However, when displayed in GIS software, data in power format is dark, making it difficult to use for visual analysis.

This document describes the specifications of the OPERA Level-2 Radiometric Terrain-Corrected (RTC) product that uses Sentinel-1 SLC data as the primary image-based input.

Using pre- and post-hurricane SAR RTC data, you can detect flooded areas by analyzing the backscatter for a copolarized band and a cross-polarized band. Low backscatter values correspond to dark colors while high backscatter values correspond to bright colors.