Abstract
dc:description.abstractATM, ETM+ and MODIS radiance data collected for the surface of Langjokull during August 2007. Radiance data from the three different instruments was then converted to surface broadband albedo using a number of different methods. The differences between the methods used to derive the surface albedo were then compared, followed by an analysis of the impact of spatial resolution and sample size on the differences between the derived surface albedo. Analysis of the different datasets combined with transect sample analyses of the derived surface albedos indicated that the most precise methods of deriving albedo from the ATM and ETM+ instruments was through the use of FLAASH for the ATM and dark pixel atmospheric correction or 6S atmospheric correction for the ETM+. These first analyses also indicated that the MODIS data was broadly in agreement with these two datasets. However, analysis of the differences between the different spatial resolution datasets across the three different spatial extents revealed a number of differences between the datasets. At the smallest scale the lower resolution datasets were shown to contain a bias towards representing certain areas in individual pixels. Consequently, the correlation between the datasets was reduced across greater sample sizes. Moreover, this bias was shown to prevent the ETM+ and MODIS imagery from averaging highly variable surfaces. The result of these measurement characteristics was for the low resolution instruments to overestimate the albedo value of snow in the accumulation area, greatly underestimate the albedo in the firn zone and struggle to capture the spatial variability in the ablation zone. The implications of these characteristics for lower resolution data have consequently been outlined, with the extent of the differences between both the low resolution datasets and the ATM dataset, indicating that where possible ETM+ imagery should be used to monitor surface albedo characteristics as it was the most closely correlated with the ATM data.
Degree
thesis:*- Name dc:type.qualificationname
- MPhil
- Level dc:type.qualificationlevel
- masters
- Grantor dc:publisher.institution
- University of Cambridge
- Year dc:date.issued
- 2013
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Pope, Ed
Subjects
dc:subject × 2Rights
dc:rightsIdentifiers
dc:identifier.*- DOI dc:identifier.doi
- https://doi.org/10.17863/CAM.59357
- OAI identifier oai:identifier
- oai:www.repository.cam.ac.uk:1810/312265