Urban subsidence poses significant challenges for rapidly developing cities. Published InSAR data reveal Kathmandu as a prime example, demonstrating an alarming rate of subsidence during rapid urban expansion. To monitor the spatiotemporal evolution of recent subsidence, we use Sentinel-1 Synthetic Aperture Radar (SAR) data and the LiCSBAS open-source processing package. Vertical surface motion maps from 2015 to present reveal many localized zones with high subsidence rates (>100 mm year−1), while the mountains that surround the valley have experienced slight surface uplift of ~5 mm year−1. The highest subsidence rate is ~200 mm year−1 and occurs in the centre of the Kathmandu metropolitan area. The distribution of subsidence in the valley matches with areas of the Pliocene to recent sediment up to 500 m thick. The deep aquifer compaction is likely to be the main driver of subsidence in the Kathmandu Valley. Time-series data show a dominant linear subsidence signal with weak sinusoidal signal peaks associated with groundwater recharge of shallow aquifers during the monsoon season. Subsidence rates decrease in proximity to the main river channels, likely driven by the seasonal recharge into the distal floodplain. The distribution of subsidence in the Kathmandu Valley has significant implications for future flood risk and infrastructure in the city.
As a new member of the Editorial Board for the Journal of Ecology & Natural Resources (JENR), I am delighted to be invited to share my views on how Synthetic Aperture Radar (SAR) Remote Sensing could advance ecosystem monitoring and management. SAR remote sensing has emerged as a powerful tool in ecological research, providing critical insights into ecosystem dynamics. SAR operates effectively under all weather conditions and during both day and night, making it an excellent complementary tool to optical satellites images like the Landsat series and Sentinel-2
We report on a suite of geophysical surveys conducted on glacial sediments near Red Lodge, Montana. The University of Houston (with assistance from University of Calgary, GEDCO, and UT‐Austin personnel) conducted VSP and well log surveys in the 115m‐deep, PVC‐cased water well, GB‐1, located on the glacial benches. The multi‐offset VSP was undertaken using surface sources (an accelerated weight drop and sledge hammer) with a hydrophone string and downhole, wall‐clamping, 3‐component geophone. The well logs included measurements of conductivity, radioactivity (gamma ray), temperature, and sonic velocity. Sonic and VSP velocities ranged from 1500m/s in the very near surface to 3000m/s at 85m depth. A distinct black clay layer (with high conductivity, high gamma ray, and low velocity) was penetrated at 85m. High‐resolution 2D and 3D seismic surveys, using a sledge hammer source, showed a number of reflectors to about 150ms two‐way traveltime. On the L‐plot composite displaying well log data, synthetic seismograms, and the VSP corridor stack, a reflection at 80ms correlated with the 85m interface Various other reflections in the VSP and surface seismic data were interpreted to represent glacial deposit layers and water zones (from the perforation logs).
In recent years, the Quetta Valley and surrounding areas have experienced unprecedented levels of subsidence, which has been attributed mainly to groundwater withdrawal. However, this region is also tectonically active and is home to several regional strike-slip faults, including the north–south striking left-lateral Chaman Fault System. Several large earthquakes have occurred recently in this area, including one deadly Mw 6.4 earthquake that struck on 28 October 2008. This study integrated Interferometric Synthetic Aperture Radar (InSAR) results with GPS, gravity, seismic reflection profiles, and earthquake centroid-moment-tensor (CMT) data to identify the impact of tectonic and anthropogenic processes on subsidence and earthquake patterns in this region. To detect and map the spatial-temporal features of the processes that led to the surface deformation, this study used two Synthetic Aperture Radar (SAR) time series, i.e., 15 Phased Array L-band Synthetic Aperture Radar (PALSAR) images acquired by an Advanced Land Observing Satellite (ALOS) from 2006–2011 and 40 Environmental Satellite (ENVISAT) Advanced Synthetic Aperture Radar (ASAR) images spanning 2003–2010. A Small Baseline Subset (SBAS) technique was used to investigate surface deformation. Five seismic lines totaling ~60 km, acquired in 2003, were used to map the blind thrust faults beneath a Quaternary alluvium layer. The median filtered SBAS-InSAR average velocity profile supports groundwater withdrawal as the dominant source of subsidence, with some contribution from tectonic subsidence in the Quetta Valley. Results of SBAS-InSAR multi-temporal analysis provide a better explanation for the pre-, co-, and post-seismic displacement pattern caused by the 2008 earthquake swarms across two strike-slip faults.
'/%3e%3cpath fill='%23fff' d='m8.751-17.959 10.11 11.373L3.997-9.844l13.94-6.1-7.692 13.129z'/%3e%3c/svg%3e)
'%3e%3cpath fill='%23012169' d='M0 0v30h60V0z'/%3e%3cpath stroke='%23fff' stroke-width='6' d='m0 0 60 30m0-30L0 30'/%3e%3cpath stroke='%23C8102E' stroke-width='4' d='m0 0 60 30m0-30L0 30' clip-path='url(%23b)'/%3e%3cpath stroke='%23fff' stroke-width='10' d='M30 0v30M0 15h60'/%3e%3cpath stroke='%23C8102E' stroke-width='6' d='M30 0v30M0 15h60'/%3e%3c/g%3e%3c/svg%3e)
'/%3e%3cuse xlink:href='%23a' transform='translate(0 -400)'/%3e%3cuse xlink:href='%23a' transform='translate(0 -600)'/%3e%3cuse xlink:href='%23a' transform='translate(0 -800)'/%3e%3cuse xlink:href='%23a' transform='translate(0 -1000)'/%3e%3cuse xlink:href='%23a' transform='translate(0 -1200)'/%3e%3cpath d='M0 0h1400v800H0z' style='fill:%23010066'/%3e%3cpath d='M576 100c-166.146 0-301 134.406-301 300s134.854 300 301 300c60.027 0 115.955-17.564 162.927-47.783-27.353 9.44-56.71 14.602-87.271 14.602-147.327 0-266.897-119.172-266.897-266.01 0-146.837 119.57-266.01 266.897-266.01 32.558 0 63.746 5.815 92.602 16.468C696.217 118.91 638.305 100 576 100z' style='fill:%23fc0'/%3e%3cpath d='m914.286 471.429-99.538-53.25 29.43 108.982-66.575-91.165-20.77 110.96-20.428-111.024-66.857 90.96L699.314 418l-99.701 52.943 74.065-85.192-112.8 4.441 103.694-44.62-103.555-44.94L673.8 305.42 600 220l99.538 53.25-29.43-108.982 66.575 91.165 20.77-110.96 20.428 111.023 66.857-90.959L814.97 273.43l99.702-52.944-74.065 85.193 112.8-4.441-103.694 44.62 103.555 44.94-112.785-4.79z' style='fill:%23fc0' transform='matrix(1.2738 0 0 1.2423 -89.443 -29.478)'/%3e%3c/svg%3e)
'/%3e%3c/defs%3e%3cpath fill='%23012169' d='M0 0h10080v5040H0z'/%3e%3cpath stroke='%23fff' stroke-width='.6' d='m0 0 6 3m0-3L0 3' clip-path='url(%23b)' transform='scale(840)'/%3e%3cpath stroke='%23e4002b' stroke-width='.4' d='m0 0 6 3m0-3L0 3' clip-path='url(%23c)' transform='scale(840)'/%3e%3cpath stroke='%23fff' stroke-width='840' d='M2520 0v2520M0 1260h5040'/%3e%3cpath stroke='%23e4002b' stroke-width='504' d='M2520 0v2520M0 1260h5040'/%3e%3cg fill='%23fff'%3e%3cuse xlink:href='%23d' x='2520' y='3780'/%3e%3cuse xlink:href='%23a' x='7560' y='4200'/%3e%3cuse xlink:href='%23a' x='6300' y='2205'/%3e%3cuse xlink:href='%23a' x='7560' y='840'/%3e%3cuse xlink:href='%23a' x='8680' y='1869'/%3e%3cuse xlink:href='%23e' x='8064' y='2730'/%3e%3c/g%3e%3c/svg%3e)
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)