Autonomous detection of cryospheric change with hyperion on-board Earth Observing-1

Doggett, T.; Greeley, R.; Chien, Steve; Castaño, Rebecca; Cichy, B.; Davies, A. G.; Rabideau, Gregg; Sherwood, Robert; Tran, Daniel; Baker, Victor R.; Dohm, J. M.; Ip, F.

doi:10.1016/j.rse.2005.11.014

Cited by 46 publications

(22 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…5 originated from non-water surface. Based on an experimental NDSI threshold (Griffin et al 2005;Doggett et al 2006) for classification (approximate water < 0.4), we note that the delineation of lake ice boundary matches fairly well as shown by a false-color image (Fig. 6b).…”

Section: Remote Sensing Imagery and The Normalized Difference Snow Insupporting

confidence: 58%

Envisat Altimetry Radar Waveform Retracking of Quasi-Specular Echoes over the Ice-Covered Qinghai Lake

Tseng¹,

Shum²,

Yi³

et al. 2013

Terr. Atmos. Ocean. Sci.

View full text Add to dashboard Cite

The use of satellite radar altimetry has long been extended to areas other than the deep-ocean primarily because of the advances in radar waveform retracking methodologies. However, the retracking algorithms are limited to a handful shapes of return echoes over assumed known surfaces, while numerous unknown waveforms exist due to the complexity of real-world land cover and other surfaces. Measurements over a surface with seasonal or ephemeral patterns could thus degrade in accuracy due to varying characteristics from the corresponding radar backscatters. In this study, we demonstrate that the Qinghai Lake, an alpine water body with distinct seasonal variation between water and ice causes inaccurate surface-height estimates when using Envisat radar altimetry and conventional retracking techniques. Following the characterization of the lake surface using EO-1 and Landsat multispectral analysis, we hypothesize that the overestimation of the lake level during winter and early spring is not from the snow accumulation; rather it is due to an error of the onboard retracker (ICE-1) which is unable to properly model the quasi-specular waveforms. Hence, we first build a classification algorithm to identify the anomalous waveforms, and then use an empirical retracking gate correction to mitigate the ice contamination. The accuracy of the 20% threshold retracker (TR) after applying suggested gate correction has a significant improvement with a root-mean-square error (RMSE) of 6 ± 7 cm and a correlation of 0.98 compared with the in situ gauge data. The improvement in accuracy is 54% better than the ICE-1 and 85% than the OCEAN retrackers, respectively.

show abstract

Section: Remote Sensing Imagery and The Normalized Difference Snow Insupporting

confidence: 58%

Envisat Altimetry Radar Waveform Retracking of Quasi-Specular Echoes over the Ice-Covered Qinghai Lake

Tseng¹,

Shum²,

Yi³

et al. 2013

Terr. Atmos. Ocean. Sci.

View full text Add to dashboard Cite

show abstract

“…The classification of Hyperion data using the SVM algorithm provides satisfying results for the classes snow and bare ice (user's accuracies of 90 and 70 %), confirming the successful use of Hyperion for snow and ice monitoring (Bindschadler and Choi, 2003;Casey et al, 2012;Doggett et al, 2006;Negi et al, 2013;Zhao et al, 2013). For other land cover classes (e.g., rocks and debris cover), a lower user's accuracy was obtained (60-70 %), probably due to both the coarse spatial resolution (30 m) of Hyperion for mapping these classes and the spectral similarity between the two classes.…”

Section: Discussionmentioning

confidence: 63%

Impact of impurities and cryoconite on the optical properties of the Morteratsch Glacier (Swiss Alps)

et al. 2017

View full text Add to dashboard Cite

Abstract. The amount of reflected energy by snow and ice plays a fundamental role in their melting processes. Different non-ice materials (carbonaceous particles, mineral dust (MD), microorganisms, algae, etc.) can decrease the reflectance of snow and ice promoting the melt. The object of this paper is to assess the capability of field and satellite (EO-1 Hyperion) hyperspectral data to characterize the impact of light-absorbing impurities (LAIs) on the surface reflectance of ice and snow of the Vadret da Morteratsch, a large valley glacier in the Swiss Alps. The spatial distribution of both narrow-band and broad-band indices derived from Hyperion was analyzed in relation to ice and snow impurities. In situ and laboratory reflectance spectra were acquired to characterize the optical properties of ice and cryoconite samples. The concentrations of elemental carbon (EC), organic carbon (OC) and levoglucosan were also determined to characterize the impurities found in cryoconite. Multi-wavelength absorbance spectra were measured to compare the optical properties of cryoconite samples and local moraine sediments. In situ reflectance spectra showed that the presence of impurities reduced ice reflectance in visible wavelengths by 80-90 %. Satellite data also showed the outcropping of dust during the melting season in the upper parts of the glacier, revealing that seasonal input of atmospheric dust can decrease the reflectance also in the accumulation zone of the glacier. The presence of EC and OC in cryoconite samples suggests a relevant role of carbonaceous and organic material in the darkening of the ablation zone. This darkening effect is added to that caused by fine debris from lateral moraines, which is assumed to represent a large fraction of cryoconite. Possible input of anthropogenic activity cannot be excluded and further research is needed to assess the role of human activities in the darkening process of glaciers observed in recent years.

show abstract

“…Several onboard science algorithms are associated with ASE for detecting dynamic events. Phenomena detected include volcanic eruptions [5], floods [9] and cryosphere events [6].…”

Section: Autonomous Sciencecraft Experimentsmentioning

confidence: 99%

“…The manually constructed cryosphere classifier was developed by a domain expert [6] and will be called the expert-dervied classifier hereafter. This classifier was designed to be run in sequence after a first classifier identified all the cloud pixels.…”

Section: Manual Classifiermentioning

confidence: 99%

See 1 more Smart Citation

Onboard classifiers for science event detection on a remote sensing spacecraft

Castaño

Mazzoni

Tang

et al. 2006

Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

View full text Add to dashboard Cite

Typically, data collected by a spacecraft is downlinked to Earth and pre-processed before any analysis is performed. We have developed classifiers that can be used onboard a spacecraft to identify high priority data for downlink to Earth, providing a method for maximizing the use of a potentially bandwidth limited downlink channel. Onboard analysis can also enable rapid reaction to dynamic events, such as flooding, volcanic eruptions or sea ice break-up.Four classifiers were developed to identify cryosphere events using hyperspectral images. These classifiers include a manually constructed classifier, a Support Vector Machine (SVM), a Decision Tree and a classifier derived by searching over combinations of thresholded band ratios. Each of the classifiers was designed to run in the computationally constrained operating environment of the spacecraft. A set of scenes was hand-labeled to provide training and testing data. Performance results on the test data indicate that the SVM and manual classifiers outperformed the Decision Tree and band-ratio classifiers with the SVM yielding slightly better classifications than the manual classifier.The manual and SVM classifiers have been uploaded to the EO-1 spacecraft and have been running onboard the spacecraft for over a year. Results of the onboard analysis are used by the Autonomous Sciencecraft Experiment (ASE) of NASA's New Millennium Program onboard EO-1 to automatically target the spacecraft to collect follow-on imagery. The software demonstrates the potential for future deep space missions to use onboard decision making to capture short-lived science events.

show abstract

Autonomous detection of cryospheric change with hyperion on-board Earth Observing-1

Cited by 46 publications

References 19 publications

Envisat Altimetry Radar Waveform Retracking of Quasi-Specular Echoes over the Ice-Covered Qinghai Lake

Envisat Altimetry Radar Waveform Retracking of Quasi-Specular Echoes over the Ice-Covered Qinghai Lake

Impact of impurities and cryoconite on the optical properties of the Morteratsch Glacier (Swiss Alps)

Onboard classifiers for science event detection on a remote sensing spacecraft

Contact Info

Product

Resources

About