One of the ironies of the quality assurance process in the remote sensing industry is that the term seems to mean different things to different professionals, companies, and agencies. The varied interpretations of the process mean that, unfortunately, clients don’t always receive the same quality in quality assurance.

First, it’s important to understand the difference between quality control and quality assurance (QC/QA) when referencing the management of geospatial data. Quality control is an ongoing process to ensure the production of high-quality results. It’s a scripted process that takes place throughout the life of the project.

Quality assurance is a formal review of the results to ensure compliance. Often, QA is performed by a third party—an agency or consultant independent of the firm that produced the geospatial deliverable. We hold a number of contracts to perform QA for clients such as the U.S. Geological Survey. In some cases, the process involves random review of the data; in other cases we may be asked to review 100 percent of the data.

In every case, however, we strive to provide meaningful feedback and assistance. Our QA process does not simply point out that errors exist, or how many. We point out specific locations where errors in data exist so corrective action can be expedited—rather than expecting those producing the data to guess what was off the mark or where errors may be located within the data.

Our approach to QA is not only based on proven processes here at Dewberry, it’s based on a spirit of teamwork and collaboration. That’s the quality we expect.