ABSTRACT. Deriving glacier outlines from satellite data has become increasingly popular in the past decade. In particular when glacier outlines are used as a base for change assessment, it is important to know how accurate they are. Calculating the accuracy correctly is challenging, as appropriate reference data (e.g. from higher-resolution sensors) are seldom available. Moreover, after the required manual correction of the raw outlines (e.g. for debris cover), such a comparison would only reveal the accuracy of the analyst rather than of the algorithm applied. Here we compare outlines for clean and debriscovered glaciers, as derived from single and multiple digitizing by different or the same analysts on very high-(1 m) and medium-resolution (30 m) remote-sensing data, against each other and to glacier outlines derived from automated classification of Landsat Thematic Mapper data. Results show a high variability in the interpretation of debris-covered glacier parts, largely independent of the spatial resolution (area differences were up to 30%), and an overall good agreement for clean ice with sufficient contrast to the surrounding terrain (differences $5%). The differences of the automatically derived outlines from a reference value are as small as the standard deviation of the manual digitizations from several analysts. Based on these results, we conclude that automated mapping of clean ice is preferable to manual digitization and recommend using the latter method only for required corrections of incorrectly mapped glacier parts (e.g. debris cover, shadow).

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Promotor hypermethylation is a common event in human cancer. O 6 -Methylguanine-DNA Methyltransferase (MGMT) is a gene involved in DNA repair, which is methylated in a variety of cancer types. In colorectal cancer and lung cancer, hypermethylation of MGMT has been correlated with p53 mutation. In the present study, 132 samples of esophageal adenocarcinoma and 58 samples of normal esophageal tissue were investigated for MGMT hypermethylation status by methylation-specific real-time PCR and results were correlated to clinicopathological parameters, patient's survival, p53 mutation and expression of p53 protein and MGMT protein. In the carcinomas, hypermethylation of MGMT was found in 63.6% of cases and loss of MGMT protein expression in 48.5% of cases. Furthermore, MGMT hypermethylation was found in 5.7% of normal esophageal smooth muscle tissue, in 20.0% of esophageal squamous epithelium and in 61.5% of nonneoplastic Barrett's mucosa. In the carcinomas, hypermethylation of the MGMT gene was correlated with loss MGMT protein expression (p < 0.0001) and with high tumor differentiation (p 5 0.0079). In contrast, no correlation between MGMT hypermethylation, Lauren's classification, WHO classification, tumor size, gender, age, pT category and pN category, and p53 status was found. Neither MGMT hypermethylation nor loss of MGMT protein expression was correlated with patient's survival. In conclusion, MGMT hypermethylation in esophageal adenocarcinoma is a frequent event that is associated with loss of MGMT protein expression but not with patient's outcome. ' 2006 Wiley-Liss, Inc.Key words: esophageal adenocarcinoma; MGMT; hypermethylation; prognosis; p53During the last few years, cancer researchers have focused on methylation of cytosine residues within a CpG island. Methylation of cytosine per se is not only found in cancer cells but also in all normal cells in which 3-4% of cytosines are methylated. However, methylation of CpG islands in normal cells occurs only in a limited number of conditions, e.g. in the case of gene imprinting. 1 Since CpG islands are mostly located in promotor regions, i.e. the 5 0 untranslated region or the exon 1 of a gene, CpG island methylation often has an influence on gene expression. 2 Promotor methylation of tumor supressor genes or DNA repair genes has been found within various types of cancer. Additionally it has been shown that promotor methylation of certain genes may be tumor specific and tissue specific. [3][4][5][6] One gene whose promotor has been found methylated in 20-30% of human tumor cell lines is that of the enzyme O 6 -methylguanine-DNA methyltransferase (MGMT; E.C. 2.1.1.63). 7 MGMT, a DNA repair enzyme, removes methyl-or alkyl-groups from guanine after chemical modification and therefore protects cells from G to A mutations. 8 For that reason, hypermethylation of the MGMT promotor can promote the accumulation of mutations within the cell. Previous investigations indicated that MGMT hypermethylation can facilitate G:C to A:T mutations in the tumor suppressor gene p53 i...

Abstract.The maximum glacier extent during the 'Little Ice Age" (mid 18th century AD) in Jotunheimen, southern Norway, was mapped using remote sensing techniques. Interpretation of existing glaciochronological studies, analysis of geomorphological maps, and own GPS-field measurements were applied for validation of the mapping. The length of glacier centrelines and other inventory data were determined using a Geographical Information System (GIS) and a Digital Elevation Model. "Little Ice Age" maximum extent for a total of 233 glaciers comprising an overall glacier area of about 290 km 2 was mapped. Mean length of the centreline was calculated to 1.6 km. Until AD 2003, the area and length shrank by 35% and 34%, respectively, compared with the maximum "Little Ice Age" extent.

The only complete inventory of New Zealand glaciers was based on aerial photography starting in 1978. While there have been partial updates using 2002 and 2009 satellite data, most glaciers are still represented by the 1978 outlines in contemporary global glacier databases. The objective of this project is to establish an updated glacier inventory for New Zealand. We have used Landsat 8 OLI satellite imagery from February and March 2016 for delineating clean glaciers using a semi-automatic band ratio method and debris-covered glaciers using a maximum likelihood classification. The outlines have been checked against Sentinel-2 MSI data, which have a higher resolution. Manual post processing was necessary due to misclassifications (e.g. lakes, clouds), mapping in shadowed areas, and combining the clean and debris-covered parts into single glaciers. New Zealand glaciers cover an area of 794 ± 34 km2 in 2016 with a debris-covered area of 10%. Of the 2918 glaciers, seven glaciers are >10 km2 while 71% is <0.1 km2. The debris cover on those largest glaciers is >40%. Only 15 glaciers are located on the North Island. For a selection of glaciers, we were able to calculate the area reduction between the 1978 and 2016 inventories.