Description

These data contain vertical rates (mm/yr) of surface land displacements and their associated uncertainties from 2015-03-15 to 2019-06-01.

They are associated with Buzzanga, B. A., Bekaert, D. P. S., Hamlington, B. D., and Sanga, S. (2020), "Towards Sustained Monitoring of Subsidence at the Coast Using InSAR and GNSS: An Application in Hampton Roads, Virginia submitted to Geophysical Research Letters.

Document Type

Dataset

File Format

.zip (.GTiff)

File Size

1 MB

Date

2020

Funder

Commonwealth Center for Recurrent Flooding Resiliency

Publisher

Old Dominion University

Methodology

Vertical land subsidence rates are produced using the methodology of Interferometric Synthetic Aperture Radar (InSAR). The input data are 163 Sentinel-1 derived interferograms produced using the Advanced Rapid and Imaging system of NASA JPL, available at: https://asf.alaska.edu. These data are accessed and preprocessed using the ARIA-tools library (https://github.com/aria-tools/ARIA-tools). The data are then subject to time-series processing using the Small Baseline Subset algorithm as implemented in the MintPy software (https://github.com/insarlab/MintPy). Details on pixel selection and geodetic tie-ins are included in the Supplementary Materials of the published manuscript.

Referenced by

Buzzanga, B. A., Bekaert, D. P. S., Hamlington, B. D., and Sanga, S. (2020). Towards Sustained Monitoring of Subsidence at the Coast Using InSAR and GNSS: An Application in Hampton Roads, Virginia. Geophysical Research Letters.

Location

Hampton Roads, VA (SNWE: 36.75, 37.225, -76.655, -75.928)

Language

English

Comments

The zipped file contains the following files:

Vup.Gtiff (1.9 MB): The vertical land displacement rates (mm/yr) in Hampton Roads, Virginia.

Vup_std. Gtiff (1.9 MB): The vertical land displacement rate uncertainties (mm/yr; 1-sigma) in Hampton Roads, Virginia.

README.txt (4.0 KB): A readme file describing the included data.

License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

DOI

10.25776/5yxq-w948

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Article Location

 
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