An Assessment of the SRTM Topographic Products - Jet Propulsion ...
An Assessment of the SRTM Topographic Products - Jet Propulsion ...
An Assessment of the SRTM Topographic Products - Jet Propulsion ...
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CHAPTER 1. OVERVIEW 16<br />
is as discussed in in great detail in Section 5.1. The residual geolocation errors are discussed<br />
in Section 5.2.<br />
Figure 1.2: Post-calibration height error residuals for a long ocean data take. The values shown<br />
are cross-track averages for each <strong>of</strong> <strong>the</strong> four <strong>SRTM</strong> beams. The time scale shown corresponds to a<br />
spatial scale <strong>of</strong> approximately 9000 km<br />
1.3.2 Reduction <strong>of</strong> Static and Dynamic Errors<br />
The residual errors described in Section 1.3.1 can be compensated in three ways:<br />
Along-Track Calibration: Estimate <strong>the</strong> beam to beam height discontinuities, as described above.<br />
Dynamic Calibration: Use <strong>the</strong> know ocean topography (including tidal effects) to estimate static<br />
phase screens and time changing residual phase and roll errors and to generate ocean ground<br />
control points.<br />
Mosaic: Use <strong>the</strong> calibration data, toge<strong>the</strong>r with o<strong>the</strong>r GCPs (including a subset <strong>of</strong> <strong>the</strong> kinematic<br />
GPS GCPs), and pass-to-pass tie-points, to perform a continent scale weighted least squares<br />
adjustment to reduce residual height errors. The mosaic correction estimates system phase<br />
(or, equivalently, roll) errors, and corrects <strong>the</strong> data in height and position given <strong>the</strong> estimated<br />
phase errors. The adjustment implies that residual errors will have some correlation over long<br />
scales. Due to <strong>the</strong> lack <strong>of</strong> an extensive GCP data base in continent interiors, <strong>the</strong> errors are<br />
best constrained at <strong>the</strong> oceans and less constrained in <strong>the</strong> interiors.<br />
As an example <strong>of</strong> <strong>the</strong> mosaic/calibration error reduction, Figure 1.4 shows <strong>the</strong> errors after static<br />
calibration, but prior to least-squares adjustments. The dominant errors are swath to swath differences,<br />
as is evident from <strong>the</strong> obvious swath patterns in <strong>the</strong> data. Figure 1.5 shows <strong>the</strong> residual<br />
errors after adjustments. This figure shows that most swath discontinuities have disappeared, and