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Many elements of the cryosphere respond to changes in climate, but mountain glaciers are particularly good indicators of climate change, because they respond more quickly than most other ice bodies on Earth. Changes in glaciers are easily noticed by specialists and non-specialists alike, in ways that other climate indicators, such as ocean temperature or statistics of atmospheric circulation indices, are not. Remote sensing methods are capable of measuring many parameters of mountain glaciers and the changes they exhibit, leading to greater insight into processes affecting changes in glaciers and, hence, climate. Field-based measurements are indispensable, as they yield high-precision data and give key insights into processes. However, due to expense and difficult logistics, such measurements are limited to a small number of sites. Remote sensing can cover large numbers of glaciers per image, and some long-term data collections (e.g., Landsat) are available for free. Algorithms and computational resources are now capable of producingmaps of glacier boundaries at useful accuracy over large regions in a short time.New sensors will be coming online soon that will continue and extend this capability. Mass balance is an important parameter indicating the health of a glacier. Mass balance can be estimated fromsatellite data by the “geodeticmethod” of measuring volume changes, where the change in volume is estimated by subtracting two digital terrain models of the glacier surface. A more recent approach to detect mass changes in land ice is through measurement of the gravitational field using the Gravity Recovery and Climate Experiment (GRACE) satellite system, which measures changes in mass below the orbit track. Advances have been made recently in remote sensing of glaciers on a number of fronts, including more complete and more accurate glacier inventories, improved glacier mapping techniques, and new insights fromgravimetric satellites.Through international cooperative

Global Land Ice Measurements from Space (GLIMS) is an international initia- tive 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 derived 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 compar- isons have improved RCs’ 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 into the data ingest process. More recent similar studies are referenced.

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 acquiring, processing, and representing digital elevation data, and the identification and quantification of DEM error and uncertainty.

Spectral, and not least multi-spectral satellite data represent the backbone of spaceborne glacier mapping and monitoring, and have allowed for substantial progress of global glacier observations in recent years. In this chapter we give an overview of the information contained in, for the most part, ASTER or Landsat type spectral data, and of methods to qualitatively and quantitatively analyze this information for glacier studies. Besides multispectral techniques based on the visible, and near- and short-wave infrared sections of the spectrum, we also shortly discuss methods based on 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 over glaciers, with special attention to a novel image differencing technique. Finally, we give an overview of satellite-image based measurement of glacier flow, a group of methods that we view as a category of spectrally-based change detection.

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.

In this Chapter we present how satellite data were applied in four countries of the European Alps (Austria, France, Italy, and Switzerland) to better understand glaciers in this region and their changes since the Little Ice Age. By combining remote sensing data with field observations and numerical modelling, several important results have been obtained. Fields of research include creation of glacier inventories and analysis of glacier-specific area changes, determination of elevation changes and flow velocity, mapping of snow lines and mass balance assessment, as well as studying supra-glacial lakes, thermal properties of debris-cover, and components of the surface energy balance. The regional studies and field evidence confirm that glacier area loss in the Alps was widespread and massive over the past decades and accompanied by strong losses in glacier volume.

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.

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.