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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.

This book focuses on the complexities of glaciers as documented via satellite observations. The complexities drive much scientific interest in the subject. The essence—that the world’s glaciers and ice caps exhibit overwhelming retreat—is also developed by this book. In this introductory chapter, we aim at providing the reader with background information to better understand the integration of the glacier-mapping initiative known as Global Land Ice Measurements from Space (GLIMS, http://www.glims.org ) within the framework of internationally coordinated glacier-monitoring activities. The chapter begins with general definitions of perennial ice on land and its global coverage, followed by a section on the relation between glaciers and climate. Brief overviews on the specific history of internationally coordinated glacier monitoring and the global monitoring strategy for glaciers and ice caps are followed by a summary of available data. We introduce the potential and challenges of satellite remote sensing for glacier monitoring in the 21st century and emphasize the importance of integrative change assessments. Lastly, we provide a synopsis of the book structure as well as some concluding remarks on worldwide glacier monitoring.

We review the use of spaceborne imagery and digital elevation models (DEMs) to evaluate glacier thinning and retreat in the Canadian Cordillera, an area that includes the provinces of British Columbia (BC), Alberta, and Yukon Territory. Glaciers in Alberta and British Columbia lost 11.1 ± 3.8 % of their area over the period 1985–2005, which represents an approximate annual shrinkage rate of 0.55 %. For the period 1985–1999 the average thinning rate of sampled glaciers was 0.78 ± 0.19 m/year water equivalent (w.e.), which equates to an annual volume loss of 22.48 ± 5.53 km3. Mean annual ice loss in the Yukon between 1977 and 2007 was 5.5 ± 1.7 km3/year, while the average mass balance for Yukon glaciers over this period was −0.45 ± 0.09 m/year. We also summarize changes in glacier extents and surface elevation from 1965 to 2005, and include examples of surging glaciers in the Yukon and glacier hazards in British Columbia.

This chapter presents an overview of some of the changes recently observed on glaciated areas in the tropical Andes of South America. Tropical glaciers are exceptional indicators of shifts in tropical climate, and the Andes are home to almost 99 % of the world’s tropical ice cover (Kaser et al. 1996). Many of the glaciated cordilleras in the northern Andes are mere remnants of what existed 50 years ago. Here we present a history of deglaciation of the Quelccaya Ice Cap in Peru, the largest body of ice in the tropics, which has lost approximately 30 % of its total area in the last 35 years; the Cordillera Blanca, a glaciated range in Peru, which has lost over 20 % of its area in the same period; glaciers in Colombia that have lost between 20–50 % or more of their area in the last few decades; Tres Cruces, a glaciated area in Bolivia, which has lost over half of its area; and one glacier in Venezuela that has lost over 90 % of its area. These changes are quite representative of overall glacier retreat throughout the tropical Andes.

This chapter summarizes the current state of remote sensing of glaciers in the India, Nepal, and Bhutan regions of the Himalaya, and focuses on new methods for assessing glacier change. Glaciers in these Himalaya regions exhibit complex patterns of changes due to the unique and variable climatic, topographic, and glaciological parameters present in this region. The theoretical understanding of glaciers in the Himalaya is limited by lack of sufficient observations due to terrain breadth and complexity, severe weather conditions, logistic difficulties, and geopolitics. Mapping and assessing these glaciers with satellite imagery is also challenging due to inherent sensor limitations and information extraction issues. Thus, we still lack a complete understanding of the magnitude of feedbacks, and in some places even their sign, between climate changes and glacier response in this region. In this chapter we present the current status of glaciers in various climatic regimes of the Himalaya, ranging from the monsoon-influenced regions of the central-eastern Himalaya (Nepal, Garhwal, Sikkim, and Bhutan) through the monsoon transition zone of Himachal Pradesh (India), to the dry areas of Ladakh (western Himalaya). The case studies presented here illustrate the use of remote sensing and elevation data coupled with glaciermapping techniques for glacier area and elevation change detection and ice flow modeling in the context of the Himalaya.

Multispectral satellite data represent the primary data source for spaceborne glacier mapping and monitoring, and remote-sensing studies have generated significant results regarding global glacier observations and understandings. In this chapter we provide an overview of the use of multispectral data and the methods typically applied in glacier studies. Besides multispectral techniques based on the visible and near-infrared section and the shortwave infrared section of the spectrum, we also briefly discuss methods for analyzing thermal and radar data, with special emphasis on the mapping of debris-covered glacier ice. A further focus is on spectral change detection techniques applied to multitemporal data, with special attention to a novel image-differencing technique. Then we provide an overview of satellite image-based measurement of glacier flow. Finally, we offer a suggestion for a new combination of glacier observations to be made by both multispectral and radar/microwave remote-sensing sensors.

The Earth’s topography results from dynamic interactions involving climate, tectonics, and surface processes. In this chapter our main interest is in describing and illustrating how satellite-derived DEMs (and other DEMs) can be used to derive information about glacier dynamical changes. Along with other data that document changes in glacier area, these approaches can provide useful measurements of, or constraints on glacier volume balance and—with a little more uncertainty related to the density of lost or gained volume—mass balance. Topics covered include: basics on DEM generation using stereo image data (whether airborne or spaceborne), the use of ground control points and available software packages, postprocessing, and DEM dataset fusion; DEM uncertainties and errors, including random errors and biases; various glacier applications including derivation of relevant geomorphometric parameters and modeling of topographic controls on radiation fields; and the important matters of glacier mapping, elevation change, and mass balance assessment. Altimetric data are increasingly important in glacier studies, yet challenges remain with availability of high-quality data, the current lack of standardization for methods for requiring, processing, and representing digital elevation data, and the identification and quantification of DEM error and uncertainty.