Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China

Hwang, Cheinway; Yang, Yuande; Kao, Ricky; Han, Jian; Shum, C. K.; Galloway, Devin L.; Sneed, Michelle; Hung, Wei Chia; Cheng, Yuh Jen; Li, Fēi

doi:10.1038/srep28160

Cited by 43 publications

(47 citation statements)

References 37 publications

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Section: Discussionmentioning

confidence: 99%

“…An increase in elevation gradient will lead to an increase in ice velocity, while a decrease in elevation gradient will lead to a decrease in ice velocity [30]. In this research, the new, enhanced, repeat-track method developed by Hwang et al [31] was used to calculate the multi-temporal elevations of the upstream part of the PRG from Envisat Sensor Geophysical Data Record (SGDR) data and CryoSat-2 data. The resolution for the bin spacing was about 0.08333°.…”

Section: Ice Velocity Variabilitymentioning

confidence: 99%

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Ice Velocity Variations of the Polar Record Glacier (East Antarctica) Using a Rotation-Invariant Feature-Tracking Approach

2017

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Abstract:In this study, the ice velocity changes from 2004 to 2015 of the Polar Record Glacier (PRG) in East Antarctica were investigated based on a feature-tracking method using Landsat-7 enhanced thematic mapper plus (ETM+) and Landsat-8 operational land imager (OLI) images. The flow field of the PRG curves make it difficult to generate ice velocities in some areas using the traditional normalized cross-correlation (NCC)-based feature-tracking method. Therefore, a rotation-invariant parameter from scale-invariant feature transform (SIFT) is introduced to build a novel rotation-invariant feature-tracking approach. The validation was performed based on multi-source images and the making earth system data records for use in research environments (MEaSUREs) interferometric synthetic aperture radar (InSAR)-based Antarctica ice velocity map data set. The results indicate that the proposed method is able to measure the ice velocity in more areas and performs as well as the traditional NCC-based feature-tracking method. The sequential ice velocities obtained present the variations in the PRG during this period. Although the maximum ice velocity of the frontal margin of the PRG and the frontal iceberg reached about 900 m/a and 1000 m/a, respectively, the trend from 2004 to 2015 showed no significant change. Under the interaction of the Polar Times Glacier and the Polarforschung Glacier, both the direction and the displacement of the PRG were influenced. This impact also led to higher velocities in the western areas of the PRG than in the eastern areas. In addition, elevation changes and frontal iceberg calving also impacted the ice velocity of the PRG.

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Section: Discussionmentioning

confidence: 99%

Section: Ice Velocity Variabilitymentioning

confidence: 99%

Ice Velocity Variations of the Polar Record Glacier (East Antarctica) Using a Rotation-Invariant Feature-Tracking Approach

2017

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“…Within a bin, the selected height measurements are fitted by the surface function and waveform parameters (Hwang et al, )

\begin{matrix} centertrue \\ H_{i}^{j} (φ, λ, t) + v_{i}^{italicj} = H_{0} (φ_{0}, λ_{0}) + s_{x} (φ - φ_{0}) + s_{y} (λ - λ_{0}) + s_{italicxx} {((), φ - φ_{0})}^{2} + \\ s_{italicyy} {((), λ - λ_{0})}^{2} + s_{italicxy} (φ - φ_{0}) (λ - λ_{0}) + Δ H {((), ‐ 1)}^{{AD}_{j}} + C_{b} (b - \overset{true¯}{b}) + C_{l} (l - \overset{true¯}{l}) + \\ C_{t} (τ - \overset{true¯}{τ}) + {\overset{h}{true}}_{I} (t - t_{0}) + e_{normalI} cos [2 π ω (t - t_{0})] + f_{normalI} sin [2 π ω (t - t_{0})] \end{matrix}

where

H_{i}^{j}

is retracked height from Envisat; j is ground track number; i is the i th measurement from track j in the bin; Δ H is ascending‐descending height difference; AD j is 1 when track j is ascending and 0 for descending track; Δ H is used to absorb systematic errors between height measurements from ascending and descending tracks; ϕ 0 , λ 0 is geodetic latitude and longitude of the bin center or the grid location; ϕ , λ , t is geodetic latitude and longitude and time of

…”

Section: Grace and Envisat Datamentioning

confidence: 99%

“…After the parameters were determined over a bin, we computed terrain and waveform parameter corrected heights as (Hwang et al, )

H_{i}^{j} ((),,, φ_{0}, λ_{0}, t) = H_{i}^{j} ((),,, φ, λ, t) - T ((),, s_{x} \dots s_{italicxy}) - g ((), b, l, τ)

where T represents the lateral height correction, so that now

H_{i}^{j} ((),, ϕ_{italic0}, λ_{italic0,} t)

is a height at the bin center at time t and g is a correction function containing ( b , l , τ ) in equation . Finally, at each bin, we obtained a daily mean from all height measurements in the same day.…”

Section: Grace and Envisat Datamentioning

confidence: 99%

“…In addition, the rate of ice snow compaction induced by temporal variations in the rate of firn compaction is required but ignored, because it is much smaller than the rate of HC over the GrIS (Zwally et al, ). In section , our altimeter data processing has included the terms that can reduce the impact of firn compaction by estimating the backscatters and two waveform parameters (Hwang et al, ; Mémin et al, ). Furthermore, the mass balance rate from GRACE,

\overset{E}{true}

(

italicEW H_{c}^{'}

rate derived from equation ), can be expressed as

\overset{E}{true} ρ_{W} = {\dot{h}}_{i} ρ_{i} + {\dot{h}}_{s} ρ_{s}

where ρ i , ρ s , and ρ w are the densities of ice, snow, and water ( ρ w = 1,000 kg/m 3 ), respectively.…”

Section: Grace and Envisat Datamentioning

confidence: 99%

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Space‐Time Evolution of Greenland Ice Sheet Elevation and Mass From Envisat and GRACE Data

Yang

Hwang

et al. 2019

JGR Earth Surface

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Precise measurements of height changes (HCs) are important for improved estimates of mass balance of the Greenland Ice Sheet (GrIS). Here we determine 10 years of precise, high‐resolution HCs of the GrIS from Envisat radar altimeter using a subwaveform retracker and a modified repeat‐track method. The HCs show clear seasonal changes and monotonic declines over glaciers on the coasts such as Zachariae Isstrøm. We enhance mass change estimates from Gravity Recovery and Climate Experiment (GRACE) data using HCs and densities from interannual correlations between GRACE‐derived mass changes and HCs. We estimate the mass changes of eight drainage basins with our combined mass change. The largest mass change between 2002 and 2012 occurred in the northwest basin and the smallest in the northeast basin. We separate the ice and snow HC rates to derive a ratio (f) between them to characterize the relative importance of ice or snow to mass change. The snow HC rates are mostly positive over the GrIS, except on the margins of the west coast and Zachariae Isstrøm. The mean ice HC rate is −6.6 ± 3.9 cm/year over 2002–2006, which accelerated to −13.9 ± 2.4 cm/year over 2007–2012. The f factors show a clear post‐2006 ice dominance in the GrIS mass loss, particularly on the west coast, with a mean 91.4% ice contribution over 2002–2006, increasing to 94.5% over 2007–2012. This indicates increasing mass loss after 2006. A coincident radar altimeter and gravimetry mission is important for studying mass balance and separating snow and ice contributions over space and time.

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Overcoming the Challenges of Water, Waste and Climate Change in Asian Cities

Rahmasary

Robert

Chang

et al. 2019

Environmental Management

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Unprecedented challenges in urban management of water, waste and climate change—amplified by urbanisation and economic growth—are growing in Asia. In this circumstance, cities need to be aware of threats and opportunities to improve their capacity in addressing these challenges. This paper identifies priorities, barriers and enablers of these capacities. Through the City Blueprint ® Approach—an integrated baseline assessment of the urban water cycle—11 Asian cities are assessed. Three cities are selected for an in-depth governance capacity analysis of their challenges with a focus on floods. Solid waste collection and treatment and access to improved drinking water and sanitation can be considered priorities, especially in cities with considerable slum populations. These people are also disproportionately affected by the impacts of climate-related hazards. The high variation of water management performance among Asian cities shows high potential for city-to-city learning by sharing best practices in water technology and governance. Combining interventions, i.e., by exploring co-benefits with other sectors (e.g., transport and energy) will increase efficiency, improve resilience, and lower the cost. Although governance capacities varied among cities, management of available information, monitoring and evaluation showed to be reoccurring points for improvement. Cities are also expected to increase implementation capacities using better policy, stricter compliance and preparedness next to promoting community involvement. Consequently, the city transformation process can be more concrete, efficient and inclusive.

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Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China

Cited by 43 publications

References 37 publications

Ice Velocity Variations of the Polar Record Glacier (East Antarctica) Using a Rotation-Invariant Feature-Tracking Approach

Ice Velocity Variations of the Polar Record Glacier (East Antarctica) Using a Rotation-Invariant Feature-Tracking Approach

Space‐Time Evolution of Greenland Ice Sheet Elevation and Mass From Envisat and GRACE Data

Overcoming the Challenges of Water, Waste and Climate Change in Asian Cities

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