Understanding Glacier Characteristics in Rocky Mountains Using Remote Sensing Yang Qing

Introduction and Background Glaciers are an essential part of the global hydrological cycle and play a major role in global and regional climate change. Glaciers are a significant factor of sea level rise and climate change, although mountain glaciers only make up a small portion of the whole ice in the world, they still are an essential part acting on sea level rise and climate change and other environmental hazards. Many efforts have been put to understand global glaciers using Remote sensing techniques, with a focus on the Himalayas in central Asia, the Andes in South America and the Alps in Europe. The study area is Rocky Mountains which are a major mountain system in North America, I’ll focus on northern Rockies in Montana and western Canada where the glaciers are abundant.

Objectives To understand the glacier characteristics using remote sensing imagery with a focus on the glaciers classification and mass balance estimation. Several different classification methods will be performed on remote sensing imagery, different results will be compared and validated by in situ observations. Mass balance estimates will be compared with historical documents. Which classification approach is the most appropriate one? Is there a significant mass change during the years, and is it accurate?

Methodology 1. Select a suitable remote sensing data source based on the sensor’s ground coverage, revisiting period, spatial resolution, spectral resolution. For example, ASTER or Landsat ETM+ / DEM from SRTM. 2. A supervised classification will be performed on the image, different classifiers such as PLDA will be used and compared, terrain attributes such as slope and north-exposedness will be included to yield higher accuracy. 3. An unsupervised classification using ISODATA method will be performed on the image as well, the result classes will be named or labeled based on in situ spectra collection and observation.

Methodology 4.In the classification process, NDSI or other band ratios thresholds will be used to help identify and delineate boundaries. PCA and other linear combinations may be used to decide the most important bands information in classification. 5.To cope with debris cover classification problems, maybe hyperspectral or thermal remote sensing imagery is needed, or the error will be largely reduced by incorporating terrain attributes. 6.The geodetic approach will be used to estimate the mass balance. This method consists in measuring elevation changes over time (δh/δt) from various DEMs constructed over the glacier surface, hence the mass change will be computed by multiplying the elevation change by pixel size then by density.

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