Quality in the GLIMS Glacier Database

Abstract

Global Land Ice Measurements from Space (GLIMS) is an international initiative to map the world’s glaciers and to build a geospatial database of glacier vector outlines that is usable via the World Wide Web. The GLIMS initiative includes glaciologists at 82 institutions, organized into 27 Regional Centers (RCs), who analyze satellite imagery to map glaciers in their regions of expertise. The results are collected at the U.S. National Snow and Ice Data Center (NSIDC) and ingested into the GLIMS Glacier Database. A concern for users of the database is data quality. The process of classifying multispectral satellite data to extract vector outlines of glaciers has been automated to some degree, but there remain stages requiring human interpretation. To quantify the repeatability and precision of data provided by different RCs, we designed a method of comparative image analysis whereby analysts at the RCs and NSIDC could derive glacier outlines from the same set of images, chosen to contain a variety of glacier types. We carried out four such experiments. The results were compiled, compared, and analyzed to quantify inter-RC analysis consistency. These comparisons have improved RC ability to produce consistent data, and in addition show that in the lower reaches of a glacier, precision of glacier outlines is typically 3 to 4 pixels. Variability in the accumulation area and over parts of the glacier that are debris covered tends to be higher. The ingest process includes quality control steps that must be passed before data are accepted into the database. These steps ensure that ingested data are well georeferenced and internally consistent. The GLACE experiments and ingest time quality control steps have led to improved quality and consistency of GLIMS data. This chapter presents the GLACE experiments and the quality control steps incorporated in the data ingest process. More recent similar studies are referenced.