Monitoring glacier parameters on the Antarctic Peninsula : a centerline approach combining satellite and GIS data - Arigony Neto, Jorge (2006)
Drastic changes were detected in glacial systems of the Antarctic Peninsula in the last decades. The observed phenomena comprise a significant warming trend, changes in precipitation patterns, reduction of seasonal sea ice, disintegration of ice shelves, retreat of glacier fronts, upward shift of the dry snow line, and increasing trend in duration of melting conditions. Although the time response of such processes to climate change remains uncertain, the dependence of the detected glacial changes on variations in climate parameters seems to be evident. However, due to the lack of consistent systematic observations in particular of the higher parts of the glacial systems, it is difficult to predict further responses of glaciers to climate change. This thesis focuses on the development of methods for semi-automatic extraction of glacier parameters (i.e., boundaries between glacier zones and glacier frontal position) on the Antarctic Peninsula using multi-temporal and multi-sensor remote sensing datasets. To expand the current monitoring of a few glaciers unevenly distributed along the peninsula to a representative set in the near future, a new methodological approach is proposed. The so-called centerline approach simplifies the current methodology based on analyses of entire glacier catchments, facilitating the pre-processing and classification of remote sensing data acquired on glaciers. A multi-sensor processing chain to extract the above mentioned glacier parameters from satellite imagery using the centerline approach is described. Routines are implemented to reduce the analyst interaction with image processing software and database system, resulting in an application called IceTools. In addition, the developed algorithms for the classification of SAR (i.e., ERS-1/2 SAR and Envisat ASAR) and optical imagery (i.e., Landsat TM/ETM+ and Terra ASTER) are explained. The modular structure of the implemented processing chain enables an unproblematic integration of algorithms for classifying datasets from future ...