scholarly journals Ice Roughness Estimation via Remotely Piloted Aircraft and Photogrammetry

2021 ◽  
Author(s):  
James Ehrman ◽  
Shawn Clark ◽  
Alexander Wall
Keyword(s):  
Land Surface ◽  
Ice Cover ◽  
Ice Thickness ◽  
Sampled Data ◽  
High Definition ◽  
Field Methods ◽  
Inter Quartile Range ◽  
Quartile Range ◽  
Ice Roughness ◽  
Remotely Piloted Aircraft

Abstract. Structure-from-Motion Photogrammetry conducted with images obtained via Remotely Piloted Aircraft (RPA) has revolutionized the field of land surface monitoring. RPA-Photogrammetry can quickly and easily capture a full 3D representation of a study area. The result of this process is a high-definition Digital Elevation Model (DEM) representing the land surface of a given study area. It is particularly useful in applications where land surface data collection would otherwise be expensive or dangerous. The monitoring of fluvial ice covers can be time-intensive, dangerous, and costly, if detailed data are required. Fluvial ice roughness is a sensitive parameter in hydraulic models and is incredibly difficult to measure directly using traditional field methods. This research hypothesized that the surface roughness of a newly-frozen fluvial ice cover is indicative of subsurface roughness. The hypothesis was tested through a comparison of ice roughness determined through the statistical analysis of RPA-photogrammetry DEMs to ice roughness values predicted by the Nezhikhovskiy equation. The Nezhikhovskiy equation is a widely used empirical method for estimating ice roughness based on observed ice thickness. Hydraulic and topographic data were collected over two years of field research on the Dauphin River in Manitoba, Canada. Various statistical metrics were used to represent the roughness of the DEMs. Strong trends were identified in the comparison of ice cover roughness values determined through RPA-photogrammetry and those calculated via the Nezhikhovskiy equation, as well as with ice thickness. The inter-quartile range of observed roughness heights was determined to be the most representative roughness metric. The maximum peak value performed better in some cases, but the fact that this metric would be heavily influenced by outliers led to it being rejected as a representative metric. Three distinct forms of surface ice roughness were noted: rough, smooth, and ridged. Statistical properties of the DEMs of fluvial ice covers were calculated. No DEMs were found to be normally distributed. k-means clustering analysis was used to group sampled data into two categories, which were interpreted as rough and smooth ice. The inter-quartile range of the smooth and rough categories were found to be 0.01–0.05 meters and 0.07–0.12 meters, respectively. RPA-photogrammetry was concluded to be a suitable method for the monitoring of fluvial ice covers. Other applications of RPA-photogrammetry for the characterization of fluvial ice covers are proposed.

scholarly journals Prediction of the date, magnitude and affected area of impending strong earthquakes using integration of multi precursors earthquake parameters

2011 ◽  
Vol 11 (4) ◽  
pp. 1109-1119 ◽  
Author(s):  
M. R. Saradjian ◽  
M. Akhoondzadeh
Keyword(s):  
Land Surface ◽  
Earthquake Precursors ◽  
Electron Content ◽  
Total Electron ◽  
Earthquake Parameters ◽  
Strong Earthquakes ◽  
Affected Area ◽  
Inter Quartile Range ◽  
Quartile Range

Abstract. Usually a precursor alone might not be useful as an accurate, precise, and stand-alone criteria for the earthquake parameters prediction. Therefore it is more appropriate to exploit parameters extracted from a variety of individual precursors so that their simultaneous integration would reduce the parameters's uncertainty. In our previous studies, five strong earthquakes which happened in the Samoa Islands, Sichuan (China), L'Aquila (Italy), Borujerd (Iran) and Zarand (Iran) have been analyzed to locate unusual variations in the time series of the different earthquake precursors. In this study, we have attempted to estimate earthquake parameters using the detected anomalies in the mentioned case studies. Using remote sensing observations, this study examines variations of electron and ion density, electron temperature, total electron content (TEC), electric and magnetic fields and land surface temperature (LST) several days before the studied earthquakes. Regarding the ionospheric precursors, the geomagnetic indices Dst and Kp were used to distinguish pre-earthquake disturbed states from the other anomalies related to the geomagnetic activities. The inter-quartile range of data was utilized to construct their upper and lower bound to detect disturbed states outsides the bounds which might be associated with impending earthquakes. When the disturbed state associated with an impending earthquake is detected, based on the type of precursor, the number of days relative to the earthquake day is estimated. Then regarding the deviation value of the precursor from the undisturbed state the magnitude of the impending earthquake is estimated. The radius of the affected area is calculated using the estimated magnitude and Dobrovolsky formula. In order to assess final earthquake parameters (i.e. date, magnitude and radius of the affected area) for each case study, the earthquake parameters obtained from different earthquake precursors were integrated. In other words, for each case study using the median and inter-quartile range of earthquake parameters, the bounds of the final earthquake parameters were defined. For each studied case, a close agreement was found between the estimated and registered earthquake parameters.

scholarly journals Ice roughness estimation via remotely piloted aircraft and photogrammetry

2021 ◽  
Vol 15 (8) ◽  
pp. 4031-4046
Author(s):  
James Ehrman ◽  
Shawn Clark ◽  
Alexander Wall
Keyword(s):  
Flow Resistance ◽  
Water Levels ◽  
Aerial Images ◽  
Ice Thickness ◽  
Ice Roughness ◽  
Remotely Piloted Aircraft ◽  
Ice Surface Roughness ◽  
Elevation Model ◽  
Surface Ice ◽  
Statistical Metrics

Abstract. The monitoring of fluvial ice covers can be time intensive, dangerous, and costly if detailed data are required. Ice covers on a river surface cause resistance to water flow, which increases upstream water levels. Ice with a higher degree of roughness causes increased flow resistance and therefore even higher upstream water levels. Aerial images collected via remotely piloted aircraft (RPA) were processed with structure from motion photogrammetry to create a digital elevation model (DEM) and then produce quantitative measurements of surface ice roughness. Images and surface ice roughness values were collected over 2 years on the Dauphin River in Manitoba, Canada. It was hypothesized that surface ice roughness would be indicative of subsurface ice roughness. This hypothesis was tested by comparing RPA-measured surface ice roughness values to those predicted by the Nezhikhovskiy equation, wherein subsurface ice roughness is proportional to ice thickness. Various statistical metrics were used to represent the roughness height of the DEMs. Strong trends were identified in the comparison of RPA-measured ice surface roughness to subsurface ice roughness values predicted by the Nezhikhovskiy equation, as well as with comparisons to ice thickness. The standard deviation and interquartile range of roughness heights were determined to be the most representative statistical metrics and several properties of the DEMs of fluvial ice covers were calculated and observed. No DEMs were found to be normally distributed. This first attempt at using RPA-derived measurements of surface ice roughness to estimate river ice flow resistance is shown to have considerable potential and will hopefully be verified and improved upon by subsequent measurements on a wide variety of rivers and ice covers.

Subglacial topography and thickness of ice caps on the Argentine Islands

2019 ◽  
Vol 31 (6) ◽  
pp. 332-344 ◽  
Author(s):  
Jānis Karušs ◽  
Kristaps Lamsters ◽  
Anatolii Chernov ◽  
Māris Krievāns ◽  
Jurijs Ješkins
Keyword(s):  
Land Surface ◽  
Geological Structure ◽  
Aerial Images ◽  
Ice Thickness ◽  
Ice Caps ◽  
The North ◽  
Prevailing Wind Direction ◽  
Aerial Vehicle ◽  
Subglacial Topography ◽  
Ground Penetrating

AbstractThis study presents the first subglacial topography and ice thickness models of the largest ice caps of the Argentine Islands, Wilhelm Archipelago, West Antarctica. During this study, ground-penetrating radar was used to map the thickness and inner structure of the ice caps. Digital surface models of all studied islands were created from aerial images obtained with a small-sized unmanned aerial vehicle and used for the construction of subglacial topography models. Ice caps of the Argentine Islands cover ~50% of the land surface of the islands on average. The maximum thickness of only two islands (Galindez and Skua) exceeds 30 m, while the average thickness of all islands is only ~5 m. The maximum ice thickness reaches 35.3 m on Galindez Island. The ice thickness and glacier distribution are mainly governed by prevailing wind direction from the north. This has created the prominent narrow ice ridges on Uruguay and Irizar islands, which are not supported by topographic obstacles, as well as the elongated shape of other ice caps. The subglacial topography of the ice caps is undulated and mainly dependent on the geological structure and composition of magmatic rocks.

scholarly journals Spatial-Temporal Distribution of the Freeze–Thaw Cycle of the Largest Lake (Qinghai Lake) in China Based on Machine Learning and MODIS from 2000 to 2020

2021 ◽  
Vol 13 (9) ◽  
pp. 1695
Author(s):  
Weixiao Han ◽  
Chunlin Huang ◽  
Juan Gu ◽  
Jinliang Hou ◽  
Ying Zhang
Keyword(s):  
Machine Learning ◽  
Land Surface ◽  
Temporal Dynamics ◽  
Temporal Distribution ◽  
Ice Cover ◽  
Qinghai Lake ◽  
Gap Filling ◽  
Thaw Cycle ◽  
Break Up ◽  
Ice Phenology

The lake ice phenology variations are vital for the land–surface–water cycle. Qinghai Lake is experiencing amplified warming under climate change. Based on the MODIS imagery, the spatio-temporal dynamics of the ice phenology of Qinghai Lake were analyzed using machine learning during the 2000/2001 to 2019/2020 ice season, and cloud gap-filling procedures were applied to reconstruct the result. The results showed that the overall accuracy of the water–ice classification by random forest and cloud gap-filling procedures was 98.36% and 92.56%, respectively. The annual spatial distribution of the freeze-up and break-up dates ranged primarily from DOY 330 to 397 and from DOY 70 to 116. Meanwhile, the decrease rates of freeze-up duration (DFU), full ice cover duration (DFI), and ice cover duration (DI) were 0.37, 0.34, and 0.13 days/yr., respectively, and the duration was shortened by 7.4, 6.8, and 2.6 days over the past 20 years. The increased rate of break-up duration (DBU) was 0.58 days/yr. and the duration was lengthened by 11.6 days. Furthermore, the increase in temperature resulted in an increase in precipitation after two years; the increase in precipitation resulted in the increase in DBU and decrease in DFU in corresponding years, and decreased DI and DFI after one year.

scholarly journals Trends and abrupt changes in 104 years of ice cover and water temperature in a dimictic lake in response to air temperature, wind speed, and water clarity drivers

2016 ◽  
Vol 20 (5) ◽  
pp. 1681-1702 ◽  
Author(s):  
Madeline R. Magee ◽  
Chin H. Wu ◽  
Dale M. Robertson ◽  
Richard C. Lathrop ◽  
David P. Hamilton
Keyword(s):  
Wind Speed ◽  
Water Temperature ◽  
Air Temperature ◽  
Water Clarity ◽  
Ice Cover ◽  
Ice Thickness ◽  
Lake Mendota ◽  
The Third ◽  
Abrupt Changes ◽  
Hypolimnetic Heating

Abstract. The one-dimensional hydrodynamic ice model, DYRESM-WQ-I, was modified to simulate ice cover and thermal structure of dimictic Lake Mendota, Wisconsin, USA, over a continuous 104-year period (1911–2014). The model results were then used to examine the drivers of changes in ice cover and water temperature, focusing on the responses to shifts in air temperature, wind speed, and water clarity at multiyear timescales. Observations of the drivers include a change in the trend of warming air temperatures from 0.081 °C per decade before 1981 to 0.334 °C per decade thereafter, as well as a shift in mean wind speed from 4.44 m s−1 before 1994 to 3.74 m s−1 thereafter. Observations show that Lake Mendota has experienced significant changes in ice cover: later ice-on date(9.0 days later per century), earlier ice-off date (12.3 days per century), decreasing ice cover duration (21.3 days per century), while model simulations indicate a change in maximum ice thickness (12.7 cm decrease per century). Model simulations also show changes in the lake thermal regime of earlier stratification onset (12.3 days per century), later fall turnover (14.6 days per century), longer stratification duration (26.8 days per century), and decreasing summer hypolimnetic temperatures (−1.4 °C per century). Correlation analysis of lake variables and driving variables revealed ice cover variables, stratification onset, epilimnetic temperature, and hypolimnetic temperature were most closely correlated with air temperature, whereas freeze-over water temperature, hypolimnetic heating, and fall turnover date were more closely correlated with wind speed. Each lake variable (i.e., ice-on and ice-off dates, ice cover duration, maximum ice thickness, freeze-over water temperature, stratification onset, fall turnover date, stratification duration, epilimnion temperature, hypolimnion temperature, and hypolimnetic heating) was averaged for the three periods (1911–1980, 1981–1993, and 1994–2014) delineated by abrupt changes in air temperature and wind speed. Average summer hypolimnetic temperature and fall turnover date exhibit significant differences between the third period and the first two periods. Changes in ice cover (ice-on and ice-off dates, ice cover duration, and maximum ice thickness) exhibit an abrupt change after 1994, which was related in part to the warm El Niño winter of 1997–1998. Under-ice water temperature, freeze-over water temperature, hypolimnetic temperature, fall turnover date, and stratification duration demonstrate a significant difference in the third period (1994–2014), when air temperature was warmest and wind speeds decreased rather abruptly. The trends in ice cover and water temperature demonstrate responses to both long-term and abrupt changes in meteorological conditions that can be complemented with numerical modeling to better understand how these variables will respond in a future climate.

scholarly journals Long-term changes of the ice regime of rivers in Latvia

2016 ◽  
Vol 47 (4) ◽  
pp. 782-798
Author(s):  
Inese Latkovska ◽  
Elga Apsīte ◽  
Didzis Elferts
Keyword(s):  
Regional Differences ◽  
Severity Index ◽  
Ice Cover ◽  
Ice Thickness ◽  
Positive Trend ◽  
The West ◽  
Climate Conditions ◽  
Long Term Changes ◽  
Ice Regime

The ice regime of rivers is considered a sensitive indicator of climate change. This paper summarises the results of research on the long-term changes in the ice regime parameters under changing climate conditions and their regional peculiarities in Latvia from 1945 to 2012. The ice cover duration on Latvian rivers has decreased during recent decades. The research results demonstrated that there is a positive trend as regards the formation of the ice cover and in 31.8% of the cases the trend is statistically significant at p < 0.05. As regards the breaking up of ice, there is a statistically significant negative trend in 93.2% of the cases at p < 0.05. This indicates an earlier ice break-up date, which in turn, displays a strong correlation with the increase of the air temperature. The same pattern applies to the reduction of the length of ice cover (a statistically significant trend in 86.4% of the cases at p < 0.05). In approximately 60% of the cases, there is a statistically significant reduction of the ice thickness. The estimated winter severity index indicates warmer winters over the last 20 years as well as regional differences in the west–east direction.

Abstract 4496: Percutaneous Coronary Intervention in Stable Coronary Heart Disease: Value of Nt-Probnp for Stratification of Long-Term Risk

Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
Pedro Carmo ◽  
Carlos Aguiar ◽  
Jorge Ferreira ◽  
Luis Raposo ◽  
Pedro Goncalves ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Percutaneous Coronary Intervention ◽  
Heart Disease ◽  
Coronary Intervention ◽  
Inter Quartile Range ◽  
Quartile Range ◽  
Stable Coronary Heart Disease ◽  
Percutaneous Coronary

Purpose: N-terminal fragment of the B type-natriuretic peptide (NT-proBNP) is an established tool for assessing acute dyspnoea and stratifying risk in heart failure, acute coronary syndromes (ACS), and stable coronary heart disease (SCHD). The aim of this study was to determine the value of NT-proBNP in predicting long-term risk of patients (Pts) submitted to elective percutaneous coronary intervention (PCI) in the setting of SCHD. Methods: We prospectively studied 291 Pts (age 64.3±9.6 years, 64 female) with SCHD submitted to successful elective PCI, and determined NT-proBNP immediately before PCI. Pts were divided into 2 groups according to NT-proBNP level: group T3 formed by Pts with NT-proBNP level in the highest tertile and group T1+T2 formed by all remaining Pts. The study endpoint was time to the first occurrence of death (D) or non-fatal myocardial infarction (MI) during the mean follow-up of 568 ± 322 days. Multivariable analyses were performed to adjust the prognostic value of NT-proBNP for the effects of factors known to influence NT-proBNP (age, gender, renal function, body mass index) and of other potential predictors of outcome (cardiovascular risk factors, prior cardiovascular events, left ventricular ejection fraction, and PCI characteristics). Results: NT-proBNP ranged from 5 pg/ml to 104 pg/ml in the 1st tertile (T1), 105 pg/ml to 358 pg/ml in the 2nd tertile (T2), and 364 pg/ml to 33.991 pg/ml in the 3rd tertile (T3). During follow-up, 8 Pts died and 11 suffered a non-fatal MI. NT-proBNP was significantly higher in Pts who experienced an adverse outcome (440 pg/ml [inter-quartile range, 104 –1712] vs 174 pg/ml [inter-quartile range, 78 – 460) in Pts with uneventful follow-up; P= 0.007). An NT-proBNP level ≥364 pg/ml was associated with a higher endpoint rate (13.4% vs 3.1% in group T1+T2) and independently predicted outcome: adjusted hazard ratio 3.11, 95% CI, 1.15– 8.37, P=0.025. The sensitivity, specificity, predictive positive value, and negative predictive value for the criterion NT-proBNP ≥364 pg/ml were 68.4%, 69.1%, 13.4%, and 96.9%, respectively. Conclusion: In the setting of SCHD, the level of NT-proBNP is a powerful prognostic marker even after successful PCI.

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