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Performance of Landsat 8 Operational Land Imager for Mapping Ice Sheet Velocity.

ABSTRACT: Landsat imagery has long been used to measure glacier and ice sheet surface velocity, and this application has increased with increased length and accessibility of the archive. The radiometric characteristics of Landsat sensors, however, have limited these measurements generally to only fast-flowing glaciers with high levels of surface texture and imagery with high sun angles and cloud-free conditions, preventing wide-area velocity mapping at the scale achievable with synthetic aperture radar (SAR). The Operational Land Imager (OLI) aboard the newly launched Landsat 8 features substantially improves radiometric performance compared to preceding sensors: enhancing performance of automated Repeat-Image Feature Tracking (RIFT) for mapping ice flow speed. In order to assess this improvement, we conduct a comparative study of OLI and the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) performance for measuring glacier velocity in a range of surface and atmospheric conditions. To isolate the effects of radiometric quantization and noise level, we construct a model for simulating ETM+ imagery from OLI and compare RIFT results derived from each. We find that a nonlinearity in the relationship between ETM+ and OLI radiances at higher brightness levels results in a particularly large improvement in RIFT performance over the low-textured interior of the ice sheets, as well as improved performance in adverse conditions such as low sun-angles and thin clouds. Additionally, the reduced noise level in OLI imagery results in fewer spurious motion vectors and improved RIFT performance in all conditions and surfaces. We conclude that OLI imagery should enable large-area ice sheet and glacier mapping so that its coverage is comparable to SAR, with a remaining limitation being image geolocation.

SUBMITTER: Jeong S

PROVIDER: S-EPMC6505706 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Performance of Landsat 8 Operational Land Imager for Mapping Ice Sheet Velocity.

Jeong Seongsu S Howat Ian M IM

Remote sensing of environment 20150926

Landsat imagery has long been used to measure glacier and ice sheet surface velocity, and this application has increased with increased length and accessibility of the archive. The radiometric characteristics of Landsat sensors, however, have limited these measurements generally to only fast-flowing glaciers with high levels of surface texture and imagery with high sun angles and cloud-free conditions, preventing wide-area velocity mapping at the scale achievable with synthetic aperture radar (S ...[more]

PMID: 31080298

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Project description:Measuring microbial abundance in glacier ice and identifying its controls is essential for a better understanding and quantification of biogeochemical processes in glacial ecosystems. However, cell enumeration of glacier ice samples is challenging due to typically low cell numbers and the presence of interfering mineral particles. We quantified for the first time the abundance of microbial cells in surface ice from geographically distinct sites on the Greenland Ice Sheet (GrIS), using three enumeration methods: epifluorescence microscopy (EFM), flow cytometry (FCM), and quantitative polymerase chain reaction (qPCR). In addition, we reviewed published data on microbial abundance in glacier ice and tested the three methods on artificial ice samples of realistic cell (10(2)-10(7) cells ml(-1)) and mineral particle (0.1-100 mg ml(-1)) concentrations, simulating a range of glacial ice types, from clean subsurface ice to surface ice to sediment-laden basal ice. We then used multivariate statistical analysis to identify factors responsible for the variation in microbial abundance on the ice sheet. EFM gave the most accurate and reproducible results of the tested methodologies, and was therefore selected as the most suitable technique for cell enumeration of ice containing dust. Cell numbers in surface ice samples, determined by EFM, ranged from ~ 2 × 10(3) to ~ 2 × 10(6) cells ml(-1) while dust concentrations ranged from 0.01 to 2 mg ml(-1). The lowest abundances were found in ice sampled from the accumulation area of the ice sheet and in samples affected by fresh snow; these samples may be considered as a reference point of the cell abundance of precipitants that are deposited on the ice sheet surface. Dust content was the most significant variable to explain the variation in the abundance data, which suggests a direct association between deposited dust particles and cells and/or by their provision of limited nutrients to microbial communities on the GrIS.

Dataset Information

Performance of Landsat 8 Operational Land Imager for Mapping Ice Sheet Velocity.

Publications

Performance of Landsat 8 Operational Land Imager for Mapping Ice Sheet Velocity.

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