The study examines the Osaka Plain and the Kyoto and Nara basins, a metropolitan region of approximately 15 million people overlying an extensive groundwater system exceeding 3,000 square kilometres. Intensive extraction from the 1920s through the 1960s lowered water levels by as much as 30 metres and produced more than 2 metres of cumulative subsidence across much of the area. Groundwater regulation introduced in the early 1960s was followed by multi-decadal recovery, while most subsidence stabilised by the mid-1970s. Because the region has retained measurable deformation during this recovery, it offers a rare opportunity to examine how groundwater reinflation reshapes the surface of a major urban basin.

Interferometric synthetic aperture radar observations formed the spatial backbone of the analysis. The researchers processed 293 Sentinel-1 images acquired from December 2016 through December 2021 and combined them with co-located global navigation satellite system measurements, producing vertical and east-west displacement fields at 10-metre resolution. The mapped vertical rate averaged 4.0 plus or minus 2.5 millimetres per year across the region, with local values reaching 12 millimetres per year. Rather than changing gradually, uplift was divided into broad domains, often larger than 100 square kilometres, separated by boundaries less than 100 metres wide. Such sharp transitions indicate that underground structures exert a first-order control on the deformation.

Mapped faults coincide with several of the largest contrasts. Across the east-dipping Uemachi reverse fault in the Osaka Plain, average uplift reached 6 to 7 millimetres per year on its eastern, hanging-wall side but only 3 to 4 millimetres per year to the west. A similarly abrupt change follows the Ujigawa Fault in the Kyoto Basin. The average difference in uplift rate across the major structures was approximately 6.5 millimetres per year. By contrast, bedrock along the western margin of the Osaka Plain rose by only 0 to 1 millimetre per year, implying that a substantial component of the inland motion was associated with basin-scale processes rather than regional tectonic uplift alone.

Groundwater observations reveal a matching pattern. The researchers analysed groundwater-head changes from 44 monitoring wells screened at depths between 10 and 561 metres, using records extending from 1985 to 2025 where available. All 31 evaluated wells in the Osaka Plain recorded net rises, but average increases were 0.3 metres per year on the eastern, upstream side of the Uemachi Fault and 0.1 metres per year on the western, downstream side. The contrast persisted in individual records: eight of nine wells west of the fault experienced a marked decline between 1991 and 1998, associated with large-scale underground construction, whereas no comparable decline appeared in the eastern wells. The asymmetry is consistent with a fault acting as a hydraulic barrier and promoting groundwater accumulation on its upstream side.

The Kyoto Basin provides another natural test. Across 12 wells with records from 2000 to 2023, heads north of the Ujigawa Fault rose by an average 0.54 metres per year, while those south of it increased by only 0.01 metres per year on average; several southern wells continued to decline. The largest observed recovery occurred at well NKY, where the level rose 23.4 metres between 2000 and 2010, corresponding to approximately 2.3 metres per year. Across major faults in the combined dataset, upstream wells rose by roughly 0.30 metres per year and were associated with about 6.0 millimetres per year of uplift. Downstream wells rose by about 0.06 metres per year alongside roughly 2.2 millimetres per year of uplift. Although the spatial agreement alone does not establish causation, it is consistent with a mechanical linkage between groundwater recovery and surface movement mediated by faults.

The researchers then compared three classes of elastic deformation model: slip on a shallow fault, tensile opening at depth and distributed volumetric expansion within an aquifer. A fault-slip model could reproduce the direction of vertical motion across the Uemachi Fault, but it necessarily predicted strong east-west convergence that the observations did not contain. Shallow reverse-fault creep was therefore rejected as an adequate explanation. Aquifer-expansion models, by contrast, reproduced both the amplitude and spatial pattern of vertical uplift and the accompanying horizontal deformation in fault-bounded areas around the Uemachi and Arima-Takatsuki structures and in the Nara and Oji regions. The results do not uniquely establish the mechanism, but they show that shallow elastic expansion of recovering aquifers is physically consistent with the observations.

Model sensitivity placed the dominant deformation sources at depths shallower than about 500 metres. This constraint was strongest along the sharp edges of uplifting domains; broad, nearly uniform uplift provided much less information about source depth. Deeper aquifers may still contribute, but the fitted geometry indicates that they were unlikely to be the principal source of the observed motion. The models simplify the geology by assuming spatially uniform mechanical properties and do not explicitly represent groundwater flow, layered aquitards or lateral variations in permeability. Nevertheless, the agreement with both vertical and horizontal motion supports elastic expansion of fault-bounded aquifers as a plausible mechanism. A simple pressure-to-strain estimate also produces several millimetres of annual uplift, matching the scale of the satellite observations.

Fault effects may evolve through time. Within the Arima-Takatsuki Fault Zone, a wedge-shaped area now rising by as much as 10 millimetres per year had subsided rapidly after the 1995 Kobe earthquake, with rates of minus 5 to minus 10 millimetres per year observed from 1998 to 2010. At well IKD, groundwater declined at an average 0.16 metres per year from 1998 to 2012 before reversing to a rise of 0.23 metres per year through 2019. A nearby well outside the rapid-uplift zone showed no equivalent reversal, instead recording a steady 0.07 metres per year of increase from 1997 to 2025. One plausible explanation is that coseismic and early postseismic damage increased fault-zone permeability, allowing trapped groundwater to drain, whereas subsequent healing reduced permeability and allowed water to accumulate again. The available observations cannot uniquely distinguish this explanation from other changes in fault properties.

The high-resolution deformation data may also reveal faults absent from conventional maps. In the Nara Basin, a 12-kilometre-long, northeast-trending boundary less than 100 metres wide separates fast uplift from slower deformation, yet it does not coincide with a mapped surface fault. Its pronounced linearity and high angle to the basin drainage are difficult to explain through lithological heterogeneity alone, and independent borehole evidence supports a subsurface discontinuity in the area. The findings have practical implications for cities pursuing managed aquifer recovery: ending excessive extraction can allow sustained reinflation, but the resulting uplift may be spatially uneven rather than uniform. The study therefore supports considering fault-controlled groundwater connectivity when anticipating differential movement of infrastructure and planning land use in urban basins.

Subject of Research: Fault-associated groundwater recovery and land uplift in Greater Osaka, Japan

Article Title: Rapid urban land uplift enhanced by crustal faults during groundwater recovery

Article References: Fukunishi, S., Kearse, J., Kaneko, Y., & Barbot, S. (2026). Rapid urban land uplift enhanced by crustal faults during groundwater recovery. Communications Earth & Environment, 7(1), Article 761. https://doi.org/10.1038/s43247-026-03915-z

Image Credits: AI Generated

DOI: 10.1038/s43247-026-03915-z

Keywords: groundwater recovery, urban land uplift, crustal faults, land subsidence, Greater Osaka, InSAR, aquifer deformation, hydraulic barriers, GNSS, pore pressure, Rapid, urban

The central concern is an “underground monitoring gap” created by three linked failures: cities often cannot directly observe subsurface change, relevant information is scattered across incompatible agencies and technical systems, and ownership, regulatory authority, and responsibility for resulting effects can remain unclear. Tunnels, basements, utility corridors, foundations, geothermal installations, and other underground development can add occupied volume or intensify urban functions without altering a city’s visible footprint. This creates an incomplete picture of urban growth, including cumulative effects on groundwater, subsurface temperature, ground stability, essential services, and communities that may experience disruption or unequal exposure to risk.

The proposed monitoring system treats the city as a three-dimensional system rather than a surface plan with a hidden layer. Its first analytical dimension, spatial occupation, asks what exists below ground, where it is located, and how its volume, depth, function, and use change over time. The second examines environmental interaction, including underground development’s relationships with groundwater, heat, and ground conditions. The third addresses infrastructure interdependence by tracing shared corridors, service dependencies, maintenance access, emergency access, and the possibility that a change in one buried system could create cascading risks elsewhere. The fourth asks whether responsibility can be traced to identifiable owners, operators, regulators, and other institutions, including for maintenance, emergency action, remediation, and eventual decommissioning.

Social consequences cut across all four dimensions, the paper says. A volumetric inventory may reveal that underground construction affects particular neighborhoods more severely, interrupts essential services, or limits public access to information about works and risks. Reliable monitoring therefore requires more than a spatial database: records from different sources need shared identifiers and spatial references, clear provenance, explicit uncertainty, and designated custodians who can keep them current. Under the proposed standards, an institutional indicator should not treat the mere assignment of a duty as proof that it has been fulfilled. Measurements, modeled effects, and inferred causes must also be labeled separately, particularly where several processes could produce the same surface signal.

Earth observation has a focused but limited role in the system. Interferometric synthetic aperture radar, or InSAR, and related techniques can detect ground deformation and other surface responses associated with underground activity. These signals can support initial screening, identify areas requiring investigation, and monitor possible surface impacts. They cannot, by themselves, reveal the geometry, function, or condition of most underground assets or establish what caused an observed deformation. The framework therefore combines satellite observations with boreholes, sensors, field measurements, engineering records, environmental models, asset inventories, and institutional documents. Attribution still requires technical and environmental evidence, while decisions about legal status and responsibility depend on complementary land and administrative records.

The framework also proposes “responsible visibility,” a governance mechanism for determining who should receive underground information and at what level of detail. Operators and emergency responders may need detailed operational data, while public authorities may require asset-level information for permitting and coordination. Researchers and affected communities may need enough access to conduct analysis, oversight, and response without exposing sensitive infrastructure. Public reporting can focus on broader indicators such as development, risk, compliance, and assigned responsibility. Any restriction should have a narrow justification, a defined group of authorized users, and a scheduled review, with redaction, aggregation, or controlled access used where appropriate.

“Volumetric accountability” supplies the second governance mechanism by connecting an underground asset and its effects to identifiable actors and enforceable obligations. Approval and operating records should specify duties for monitoring, maintenance, remediation, and closure, including procedures for transferring those duties when an operator or institution changes. Where obligations may persist for many years, the paper argues, financial assurance or cost-recovery arrangements can help preserve the resources needed for monitoring, remediation, or closure. Communities also need procedures through which they can obtain information, raise concerns, and seek corrective action. The framework identifies responsible actors without assuming that formal assignments are adequately funded, enforced, or completed in practice.

Operationally, the Perspective arranges these elements into a five-stage cycle. The first establishes a baseline inventory of assets, institutional records, uncertainties, and missing information, distinguishing verified facts from outdated, estimated, or incomplete records. The second maps priorities and risks by identifying intersections among underground occupation, hazards, infrastructure dependencies, and exposed populations. The third integrates evidence and assigns responsibility, linking assets to ownership, regulatory authority, environmental information, and data stewards while preserving provenance and uncertainty. The fourth establishes access classifications, disclosure practices, and safeguards. The fifth applies the evidence to decisions and periodic review, checking whether lifecycle duties, inspections, maintenance, financial assurance, decommissioning plans, and remediation obligations have been fulfilled.

The paper presents three cities as illustrative starting points rather than completed demonstrations of the system. New York City’s recent work on subway flooding, service disruption, and coastal-flood resilience could be connected to records of subway assets, drainage conditions, and institutional duties. In Lyon, records of basements and other underground structures offer an entry point for examining cumulative effects on groundwater flow, model uncertainty, and responsibility for responses. Singapore’s detailed records of underground utilities, already linked to legal rights, responsibilities, and organizational roles, could be extended with environmental conditions, infrastructure dependencies, information-access rules, and long-term accountability. These cases show how cities might begin with capabilities they already possess, although the article does not report a completed implementation or measured governance outcome in any of them.

The proposal is significant because it changes what counts as urban expansion and what cities must measure to govern it. Conventional indicators can register little change while underground occupation, environmental effects, infrastructure pressures, and public obligations continue to grow. Implementation will nevertheless vary with the quality of local records and the ability of institutions to coordinate information, and the framework has not yet been validated as a universal system. The paper argues that cities could begin with high-risk assets in transit corridors, flood-prone districts, or places experiencing subsidence or groundwater stress, then expand coverage as records, responsibilities, and update procedures improve. Comparative research would still need to test which indicators work consistently across cities and whether the approach improves the continuity and traceability of evidence and responsibility. The immediate advance is therefore conceptual and operational: it supplies a disciplined way to detect hidden urban change, combine evidence, protect sensitive information, and reduce the chance that long-term underground costs and obligations remain unresolved.

Subject of Research: Proposed framework for monitoring and governing durable growth in urban underground space.

Article Title: Seeing cities in depth: subsurface urban expansion and the case for volumetric monitoring and accountability

Article References: Gil, A. G. C. (2026). Seeing cities in depth: subsurface urban expansion and the case for volumetric monitoring and accountability. Frontiers in Sustainable Cities, 8, Article 1878583. https://doi.org/10.3389/frsc.2026.1878583

Image Credits: AI Generated

DOI: 10.3389/frsc.2026.1878583

Keywords: subsurface urban expansion, volumetric monitoring, underground space, urban governance, remote sensing, InSAR, ground deformation, groundwater, infrastructure accountability, responsible visibility, Seeing, cities

The Algeciras Fault System stretches roughly 540 kilometers in a northeast-southwest direction along the eastern flank of Colombia’s Central Cordillera, cutting through the departments of Meta, Huila, Cauca, Nariño, Caquetá, and Putumayo. It is a transpressional structure, meaning it combines sideways strike-slip motion with vertical compression, and it marks part of the boundary zone where the Nazca and South American plates grind against each other. The fault system passes beneath towns including Uribe, Algeciras, Neiva, Gigante, Pitalito, Sibundoy, Mocoa, and Ipiales, across terrain that rises from 600 meters to more than 3,000 meters above sea level. Historical records document destructive earthquakes in the Huila-Caquetá region, and instrumental monitoring confirms persistent moderate-to-strong seismicity along its trace.

What makes the new study unusual is its data sources. The researchers drew on monthly gravity solutions from NASA’s GRACE mission and its successor GRACE Follow-On, which measure tiny changes in Earth’s gravitational field from orbit. Because those satellites also see the weight of water moving through rivers, soils, and aquifers, the team subtracted hydrological contributions using the Global Land Data Assimilation System, or GLDAS, a land-surface model driven by meteorological and satellite observations. Even after this correction, the authors caution that residual non-tectonic signals cannot be fully excluded, so the gravity signals they interpret must be treated carefully.

To check the quality of the satellite gravity data, the researchers compared it against airborne gravimetric surveys flown by Colombia’s National Hydrocarbons Agency in 2006 and 2009 over the Yari-Caguán and Putumayo basins. At coarse regional scales, the agreement was remarkably tight: when the airborne data were smoothed with a 500-kilometer upward-continuation filter, average differences from the satellite solutions dropped to between roughly 0.49 and 1.54 percent. This cross-check supported the team’s decision to use the GFZ-processed RL06 solutions at full 96-by-96 spherical harmonic resolution, which preserve small-amplitude spatial variations that stronger filtering would erase.

The seismic side of the analysis drew on 14,592 earthquakes recorded by the Colombian Geological Survey between May 2002 and July 2020. The team converted moment magnitudes to local magnitudes where necessary and estimated the energy released by each event. When they sorted earthquakes by whether they occurred in areas of gravity increase or gravity decrease, a clear asymmetry emerged: 52.1 percent of events fell in gravity-decrease zones, but those zones accounted for 93.1 percent of the total released seismic energy. Stronger, shallower earthquakes were especially concentrated where gravity was falling.

The most dramatic result came from combining radar interferometry with gravity. Using 85 processed Sentinel-1 satellite images and the Small Baseline Subset technique, the researchers mapped vertical ground motion across the fault corridor and compared it month by month with GRACE-derived gravity variations. They identified two kinds of domains: direct-correlation areas, where gravity and elevation move up or down together, and inverse-correlation areas, where one rises as the other falls. When they tallied the earthquakes falling within each domain type, they found that areas of simultaneous decrease in both gravity and elevation accounted for approximately 99 percent of the total seismic energy released in the analyzed subset. For earthquakes of magnitude 3.0 or larger at depths of 20 kilometers or less, 89 percent of events occurred in these gravity-and-elevation-decrease zones.

This pattern is geophysically meaningful. Simultaneous gravity loss and ground subsidence can indicate mass redistribution at depth, whether through compaction, fluid migration, or the elastic response of the crust to tectonic loading. The authors suggest that such zones may reflect a closer spatial association between mass redistribution and crustal deformation during seismically active periods. Comparable gravity-deformation relationships have been documented in other settings, including Mount Etna in Italy and regions of nonlinear land subsidence, suggesting the pattern is not unique to the Colombian Andes but may be a general feature of actively deforming crust.

The team also cross-correlated gravity variations with ground displacements measured at nine permanent GNSS stations from Colombia’s GeoRED network. Correlation coefficients ranged from nearly zero to 0.61, with time lags stretching up to 45 months. The vertical component showed the strongest correlations of any measured quantity, with the LAB1 station recording a maximum direct correlation of 0.6143 at a four-month lag and a maximum inverse correlation of -0.5593 at six months. Stations close to the main fault trace, like LAB1, tended to show rapid responses consistent with elastic deformation of the upper crust, while stations farther away, like QUIL and OVSC, showed longer-delayed correlations that may reflect deeper viscoelastic processes or rheological differences along the fault corridor.

As a case study, the researchers examined the magnitude 6.0 Mesetas earthquake of December 24, 2019, which struck at a depth of about 13 kilometers. In the months surrounding the event, the GRACE-derived gravity time series displayed a distinctive W-shaped fluctuation, bounded by the two most abrupt gravity variations in the entire 2002-2020 record. At the earthquake location, the team noted a temporal coincidence between a gravity decrease of 0.461 milligal and an elevation change of -0.062 meters. Spectral analysis using the Fast Fourier Transform showed that most of the signal’s power was concentrated at low frequencies, with a dominant peak at roughly 0.2 cycles per month, corresponding to a period of about five months. The authors interpret this sequence as potentially compatible with stress accumulation, rupture, and post-event crustal readjustment, though they emphasize that the coarse spatial resolution of GRACE and possible residual hydrological effects mean the observation is exploratory rather than conclusive.

The study’s authors, Edwin Mauricio Pinzon Monroy and Carlos Alberto Vargas Jiménez, are careful to frame their results as associations rather than causal proof. Satellite gravimetry resolves features hundreds of kilometers wide, far larger than the rupture zone of a magnitude 6 earthquake, and hydrological models cannot perfectly remove water-related signals. GNSS time series vary in length and continuity, and InSAR measurements can be affected by atmospheric conditions and topographic artifacts. Yet the convergence of independent data streams, satellites weighing the Earth from orbit, radar measuring the ground’s rise and fall, and seismometers tallying where energy is released, offers a template that can be applied to other active fault systems worldwide. As gravity missions improve in resolution and longer geodetic records accumulate, this kind of multi-source approach may become a standard tool for identifying which segments of a fault are quietly loading up, and which are already letting go.

Subject of Research: Integration of satellite gravimetry, GNSS, InSAR, and seismicity to analyze the Algeciras Fault System in Colombia

Article Title: Seismic – Gravimetric analysis of the Algeciras fault system (Colombia): spatio-temporal correlations from GRACE and GNSS-InSAR

Article References: Pinzon Monroy, E. M., & Vargas Jiménez, C. A. (2026). Seismic – Gravimetric analysis of the Algeciras fault system (Colombia): spatio-temporal correlations from GRACE and GNSS-InSAR. Frontiers in Earth Science, 14, Article 1938095. https://doi.org/10.3389/feart.2026.1938095

Image Credits: AI Generated

DOI: 10.3389/feart.2026.1938095

Keywords: Algeciras Fault System, GRACE, GRACE Follow-On, GNSS, InSAR, satellite gravimetry, seismicity, Colombia, tectonic deformation, Mesetas earthquake, GLDAS, seismic hazard

Developed by Qingsong Du and released under the GNU General Public License, LiCSAR-WinFetch version 1.3.0 is a Python workflow that handles the unglamorous but critical stage between the public archive and the time-series analysis packages researchers actually use. It discovers and resolves remote products, downloads a selected single-frame dataset, organises the results into the exact directory hierarchy expected by LiCSBAS — the widely adopted open-source package for quality control, displacement time-series estimation and velocity mapping — and validates the structure of what has arrived on disk. Crucially, it also does something most downloaders do not: it can plan a wide-area study entirely from inventory metadata before a single large raster file is transferred.

The motivation is practical. A single LiCSAR frame can contain hundreds of acquisition dates and thousands of interferogram pairs, and a browser-based retrieval session or a minimal script offers little protection against interrupted connections, partially written files, repeated transfers and uncertainty about which missing objects are actually required. For a time-series analysis to work, every interferogram pair needs both its unwrapped-phase raster and its coherence raster; if either is absent, the pair is structurally incomplete. An optional atmospheric correction product, by contrast, should be reported as unavailable without being misclassified as a failed required pair. LiCSAR-WinFetch keeps these product roles strictly separate, ending each file in an explicit state: downloaded, already complete, planned, unavailable or failed.

The tool also confronts a messier reality of public archives: they change. The COMET-LiCS portal reported a storage-system migration in October 2025 and advised users to update their download code. During such transitions, an expected file may appear as a direct object, a redirected target, or a small HTML or plain-text manifest containing the real object URL. A naive client that treats every entry as an ordinary directory can falsely classify available data as missing. LiCSAR-WinFetch’s resolver tests the expected URL and supported storage variants, resolves HTML anchors relative to the final response location, searches plain-text manifests for absolute targets, and de-duplicates candidates before any transfer begins. Its behaviour under these cases is pinned down by a fifteen-test deterministic suite, all of which passed for version 1.3.0.

Download integrity receives equally careful treatment. Transfers run through a configurable thread pool, with bytes first written to a temporary .part file; the final filename appears only after a size check against the remote object succeeds. If a partial file exists, the client sends an HTTP Range request to resume from the local byte count, and if a server ignores that request and returns a complete object, the temporary file is reopened cleanly rather than corrupted by incompatible appending. Every run produces a machine-readable CSV report of file-level outcomes, a text summary and a log — records that can be archived alongside a study so that a later investigator can distinguish a changed remote object from an interrupted local transfer or a deliberately excluded optional product.

The most scientifically interesting component, however, is the multi-frame temporal planner. Wide-area studies often span many adjacent radar frames, and those frames may cover different date ranges. If neighbouring frames sample different seasonal windows or event intervals, a nominally common analysis can silently compare incomparable things. The planner scans the remote inventories of an entire frame group and computes the maximum common calendar interval shared by all frames, the exact intersection of acquisition dates and interferogram-pair networks within a same-orbit group, and a retention statistic describing how much of the smaller pair network survives strict common-pair selection. It then evaluates four temporal-selection modes of increasing strictness — independent, common-period, common-epochs and exact common-pairs — and reports the graph-theoretic consequences of each.

A demonstration on 22 LiCSAR frames covering the Qilian Mountains — eleven ascending and eleven descending frames in twelve relative-orbit groups — shows why this planning layer matters. All 22 inventory scans completed without downloading any imagery, revealing a 22-frame maximum common calendar interval from November 2014 to September 2023. Across the ten two-frame groups, exact common-pair retention ranged from 71.4 percent to 97.1 percent, and nine of the resulting networks stayed connected. But the 106D group delivered a cautionary result: it retained 94.0 percent of the smaller within-period pair network — 1,970 of 2,096 pairs — yet the strict filtering fragmented the graph into four connected components and left three common acquisition dates isolated. Two of those dates were already isolated in the shorter frame’s independent network; the third, August 2023, became isolated only after pair intersection. A high retention percentage, in other words, can coexist with hidden fragmentation that would only surface after terabytes of data had been downloaded.

The package’s interoperability claims were tested against the maintained LiCSBAS step 01 downloader on a bounded benchmark: frame 124D_04854_171313 over four acquisition epochs in September and October 2016, yielding six interferogram pairs. Both tools produced all 20 expected output paths, and 19 of the 20 files were byte-identical by SHA-256 hashing, including all 12 interferogram products. The single difference was the representative multilook-intensity raster, traced to a differing source-epoch selection rule rather than an incomplete transfer. The LiCSAR-WinFetch output then passed through LiCSBAS’s step 02 preprocessing script under Ubuntu 22.04 on the Windows Subsystem for Linux without any manual renaming, processing all six interferograms and returning exit code zero. Cross-platform continuous integration on Windows, Ubuntu and macOS under Python 3.10 and 3.12 passed all six jobs, confirming that the tool, though born on Windows desktops, is genuinely platform-neutral.

The authors are careful about scope. LiCSAR-WinFetch does not generate interferograms, assess phase-unwrapping quality, estimate deformation time series, harmonise cross-frame references, mosaic results, model the atmosphere or perform line-of-sight decomposition. A structurally complete directory certifies only that the requested products are present and organised, not that the underlying geophysical measurements are sound. The validation is bounded to the tested archive representations, frame selections and LiCSBAS step 02, and says nothing about transfer speed or future archive compatibility. Yet within those limits, the tool changes the order of operations for wide-area Sentinel-1 studies: researchers can now check calendar overlap, network connectivity and pair retention before committing storage and processing resources, and archive the machine-readable evidence of every decision. For studies of tectonic deformation, volcanic unrest, subsidence and infrastructure monitoring, that makes the path from remote inventory to analysis-ready input explicit, inspectable and reproducible — a quiet but meaningful advance in how satellite radar science gets done.

Subject of Research: Open-source software for reproducible acquisition, temporal planning and LiCSBAS-ready organisation of Sentinel-1 InSAR products from the COMET-LiCS portal

Article Title: LiCSAR-WinFetch: Reproducible LiCSAR acquisition, multi-frame temporal planning, and LiCSBAS-ready organisation of LiCSAR products

Article References: Du, Q. (2026). LiCSAR-WinFetch: Reproducible LiCSAR acquisition, multi-frame temporal planning, and LiCSBAS-ready organisation of LiCSAR products. SoftwareX, 36, Article 103119. https://doi.org/10.1016/j.softx.2026.103119

Image Credits: AI Generated

DOI: 10.1016/j.softx.2026.103119

Keywords: InSAR, LiCSAR, LiCSBAS, Sentinel-1, LiCSAR-WinFetch, open-source software, radar interferometry, ground deformation, reproducibility, temporal planning, COMET-LiCS portal, FAIR data

The study, summarized in a Research Briefing in the same journal, draws on interferometric synthetic aperture radar, or InSAR, a technique that has transformed how scientists measure ground deformation. By comparing the phase of radar signals reflected back to satellites as they pass over the same location on repeated orbits, researchers can detect millimeter-scale changes in the distance between the satellite and the ground. Stacked over months and years, these measurements produce detailed maps of vertical land motion for entire metropolitan regions, at spatial resolutions far finer than any network of ground-based surveying instruments could achieve. The approach has matured rapidly over the past decade, as reviewed in the Earth-Science Reviews literature, and it now underpins national and continental assessments of subsidence in places ranging from the United States coastline to China’s largest cities.

What distinguishes the new work is its global scope and its attention to temporal dynamics. Earlier studies demonstrated that subsidence is widespread in individual countries or regions; this analysis extends the view to 465 major cities across every inhabited continent, ranking them by the severity of their sinking. The results place Southern North America, Southeast Asia and West-Central Asia at the top of the severity ranking, regions where a combination of geology, groundwater extraction and rapid urban growth appears to drive pronounced downward motion. In Southeast and East Asia, the analysis uncovered a more nuanced picture: rather than uniform sinking, many hotspots display a mixture of accelerating and decelerating subsidence, suggesting that local management interventions, changing patterns of water extraction and shifting urban development are actively reshaping the trajectory of ground motion in these cities.

The physical causes of urban subsidence are well understood in principle, even if their global expression is only now being mapped in detail. The dominant driver in most cities is the compaction of unconsolidated sediments when groundwater is extracted faster than it can be replenished. Sandy and silty layers that once supported water in their pore spaces collapse as the water pressure drops, transferring the load to the mineral skeleton and permanently reducing the thickness of the aquifer system. Because this compaction is largely irreversible, subsidence caused by over-extraction cannot simply be undone by later recharging of the aquifer, although the rate of sinking can often be slowed dramatically. Other contributors include the natural consolidation of young deltaic sediments under the weight of buildings and infrastructure, the drainage and oxidation of organic soils, mining activity, and the loading of the crust by massive urban construction.

The regional patterns identified in the study align with these mechanisms. Southern North America includes cities built on soft coastal and deltaic sediments where decades of groundwater pumping have compounded natural compaction, a pattern already documented in detail by InSAR studies of United States coastal cities published in Nature in 2024. Southeast Asia contains some of the world’s most rapidly subsiding urban areas, many of them situated on low-lying deltas where dense populations, intense groundwater demand and soft Holocene deposits coincide. West-Central Asia’s inclusion among the most severely affected regions reflects cities in arid basins where heavy reliance on groundwater has caused aquifer-system compaction on a large scale. In each of these regions, the new global dataset provides a consistent yardstick, allowing the severity of subsidence in one city to be compared directly with that in another using the same satellite-based methodology.

The finding that subsidence dynamics are mixed in Southeast and East Asia deserves particular attention. Accelerating subsidence in a hotspot signals that the underlying drivers are intensifying, whether through increased extraction, continued sediment loading or expanding built-up area, and it flags places where intervention is most urgent. Decelerating subsidence, by contrast, can indicate that mitigation measures are working. Several cities in East Asia have implemented aggressive groundwater management over recent decades, restricting pumping, importing surface water and operating managed aquifer recharge schemes, and the slowing of subsidence in some hotspots is consistent with the success of such policies. The fact that both accelerating and decelerating signals coexist within the same broad region underscores a central message of the study: subsidence is not an inevitable fate but a manageable process, and its trajectory responds to human decisions about water and land use.

For coastal cities, the arithmetic of relative sea-level rise makes subsidence an urgent concern. When land sinks while the ocean rises, the two effects add together, and in many subsiding coastal cities the local rate of relative sea-level rise far exceeds the global average of a few millimeters per year. Research published in Nature Sustainability in 2022 quantified this problem for major coastal cities, showing that subsidence can contribute a substantial fraction, sometimes the majority, of the total relative sea-level rise experienced locally. The new global analysis reinforces that message at scale: cities in Southeast Asia and elsewhere face combined rates of relative sea-level rise that could translate into dramatically earlier thresholds of chronic flooding, saltwater intrusion and storm-surge damage than global projections alone would suggest. For the residents of such cities, what matters is not the global mean but the local sum, and that sum is increasingly dominated by sinking land.

The technical achievement behind the study rests on careful handling of the known pitfalls of InSAR. Atmospheric delays, orbital errors, phase unwrapping ambiguities and decorrelation over vegetated or rapidly changing surfaces can all contaminate the measurements, and comparing results across hundreds of cities requires consistent processing and calibration. The authors built on established calibration strategies that anchor satellite-derived relative land-level subsidence to independent prior knowledge, such as tide-gauge records or GNSS measurements, improving the reliability of cross-city comparisons. They have also made the dataset explorable through a public visualization platform, the Global Urban Subsidence tool hosted on Google Earth Engine, which allows users to examine subsidence patterns for each of the 465 cities. This kind of open infrastructure matters, because subsidence data are most valuable when they reach the planners, engineers and water managers who can act on them.

The study arrives at a moment when related assessments are converging on a shared conclusion. A national-scale analysis of 82 major Chinese cities published in Science in 2024 found that a significant share of urban land in China is subsiding, with particularly rapid motion in some of the country’s largest and most water-stressed metropolitan areas. The United States coastal study reached similar conclusions for North American shorelines. By extending the analysis to a global sample of cities and by explicitly characterizing whether subsidence is accelerating or decelerating, the new work adds the temporal dimension that earlier snapshots lacked. Trajectory matters for policy: a city sinking slowly but steadily needs different investments than one whose sinking is speeding up, and a city where subsidence is decelerating offers evidence that mitigation pays off.

For a century, urban subsidence was documented city by city, famously in places where sinking ground forced costly engineering responses. Satellite radar has now turned that fragmented record into a coherent global picture, and the picture shows that the problem is both widespread and dynamic. The most severe sinking clusters in Southern North America, Southeast Asia and West-Central Asia, but the mixed trajectories across Asian hotspots demonstrate that the future of subsidence is not predetermined. Where groundwater is managed, subsidence slows; where extraction intensifies, it accelerates. As climate change raises the baseline of the sea and urban populations continue to grow in the very deltas and basins most prone to compaction, the new global dataset offers something increasingly precious: a consistent, repeatable measurement of how the ground beneath hundreds of cities is moving, and an early-warning framework for the places where the descent is quickening. The ground under the world’s cities is sinking, but for the first time, humanity can watch it happen in near real time, city by city, and act before the descent becomes irreversible.

Subject of Research: Global satellite-based assessment of land subsidence patterns and temporal dynamics in 465 major cities

Article Title: Global patterns and temporal dynamics of urban subsidence

Article References: Global patterns and temporal dynamics of urban subsidence. (2026). Nature Cities. https://doi.org/10.1038/s44284-026-00528-7 (Author names are not included in the publisher’s citation export.)

Image Credits: AI Generated

DOI: 10.1038/s44284-026-00528-7

Keywords: urban subsidence, InSAR, satellite radar, groundwater extraction, sea-level rise, Nature Cities, Southeast Asia, West-Central Asia, land motion, coastal cities, aquifer compaction, urban geohazards

The technical achievement at the heart of the study lies in its methodology. The researchers drew on interferometric synthetic aperture radar, or InSAR, a technique that compares phase differences between radar images of the same location captured at different times by the European Sentinel-1 satellites. Because the radar signal travels to the ground and back, even millimeter-scale shifts in the surface alter the phase of the returning wave. By combining thousands of such acquisitions in a small-baseline time-series framework, the team constructed high-resolution maps of what they call relative local land subsidence for every city in their sample, all processed with a single, uniform pipeline.

That consistency matters. Earlier global assessments relied on heterogeneous data sources and varying methods, making it difficult to compare one city with another or to prioritize interventions. Previous regional studies had documented dramatic cases—Jakarta’s sinking districts, Mexico City’s century-long descent, the subsiding metropolises of coastal China and Iran’s depleting aquifer basins—but a globally coherent baseline was missing. The new work fills that gap, providing velocity estimates, coherence metrics, and uncertainty measures for all 465 cities, and offering them through an interactive visualization platform built on Google Earth Engine, alongside downloadable maps and publicly released processing code.

One of the study’s central methodological challenges is the distinction between relative and absolute motion. InSAR measures ground movement relative to a reference point, and because radar satellites orbit the Earth rather than sit on it, the resulting velocities can carry systematic biases related to satellite orbits, atmospheric delays, and the choice of reference frame. To address this, the team aligned their relative local land subsidence maps to a global vertical land motion product derived from a worldwide network of GNSS stations. The correction anchors the satellite measurements to an absolute terrestrial reference frame, allowing subsidence in, say, Manila to be compared directly with subsidence in Houston.

Instructively, the researchers found that the broad spatial patterns of subsidence remained largely consistent after this vertical land motion alignment—although the correction introduced additional uncertainty. This is a valuable lesson for the field: relative measurements, carefully referenced, can capture the geography of sinking ground even without absolute anchoring, but the absolute version is essential when subsidence must be combined with sea-level rise projections to estimate flood risk. For coastal cities, where the ocean sets a fixed datum, the difference between relative and absolute subsidence is not academic; it determines how quickly dry land becomes inundated land.

The geographic findings are striking. Southeast Asia emerges as one of the most severely affected regions, a result consistent with decades of local studies implicating intensive groundwater extraction from compressible deltaic sediments. West and Central Asia also stand out, where aquifer depletion beneath arid, rapidly growing cities has produced some of the fastest sinking rates ever measured. North America’s inclusion among the hotspots reflects both well-documented cases, such as Houston’s ongoing descent tied to groundwater pumping and oil extraction, and newer analyses revealing that sizable stretches of the United States coastline are quietly subsiding, compounding the threat of rising seas.

Equally important is what the study reveals in places that have rarely been measured. South America, Africa, and Russia—regions historically under-represented in subsidence literature—show clear signals of ground deformation in the new global maps. This matters because subsidence hazard has often been assumed to be a problem of specific geographies: deltas, coastal plains, and arid zones with heavy irrigation. The new dataset suggests the phenomenon is far more widespread, and that cities without monitoring infrastructure or historical records may nonetheless harbor significant, unrecognized risk. Filling these blind spots is precisely what a uniform global survey can do that scattered national studies cannot.

Beyond mapping where the ground is sinking, the study breaks new ground by tracking how subsidence is changing over time. Using changepoint detection and piecewise regression techniques, the team identified marked deceleration in many cities across Southeast and East Asia—a signal that, in some places, management interventions may be working. Tokyo’s famous turnaround, achieved through strict groundwater regulation after decades of sinking, has long served as the canonical example that subsidence can be halted. The new evidence of deceleration across multiple Asian cities hints that similar dynamics—reduced pumping, artificial aquifer recharge, surface water substitution such as China’s south-to-north water diversion project—may be leaving measurable fingerprints in the satellite record.

Yet the picture is not uniformly hopeful. The researchers found that substantial urban areas within those same regions continue to show accelerating subsidence, meaning that city-level averages can conceal neighborhoods where the ground is falling faster than ever. This spatial heterogeneity is one of the strongest arguments for high-resolution monitoring: a single number for a megacity cannot capture the difference between a district resting on stable bedrock and one sinking into soft lacustrine clay. The trajectory analysis, which distinguishes accelerating, decelerating, and stable zones within individual cities, gives planners a tool for targeting adaptation measures—flood defenses, building retrofits, water policy—where they are needed most.

The physical mechanism underlying most of this sinking is well understood. When groundwater is pumped from sand and gravel aquifers interbedded with clays and silts, water pressure that once supported the sediment grains drops, and the fine-grained layers compress. Crucially, much of this compaction is inelastic: once the aquifer skeleton collapses, it does not rebound when pumping stops, meaning lost aquifer storage capacity is permanently forfeited. Add the weight of dense urban construction, natural sediment compaction in deltas, drainage of organic soils, and in some places tectonic motion, and cities face a compound hazard in which sinking land amplifies every other consequence of climate change, from storm surge to river flooding.

What makes this study likely to resonate far beyond the geodesy community is its timing and its openness. With coastal populations growing and climate-driven sea-level rise accelerating, the intersection of sinking land and rising water is one of the defining risk multipliers of the century. By releasing the full subsidence maps, the code that produced them, and an interactive global viewer, the research team has transformed what was once scattered specialist knowledge into a shared public resource. City governments, insurers, and engineers can now locate themselves on a common global baseline, and the deceleration signals documented in parts of Asia offer something rare in climate adaptation: evidence that determined policy can visibly bend the curve of a hazard measured from orbit.

Subject of Research: Global satellite-based assessment of urban land subsidence and its changing trajectories in 465 major cities

Article Title: A global view of urban land subsidence and its changing trajectories

Article References: Wang, L., Ao, Z., Tao, S., Hu, X., Hu, X., Ran, Y., Wang, G., Zhao, K., Bai, H., Xiao, J., Xue, B., Zhao, X., Zhang, F., Jiang, K., Lin, Y., Huang, Y., Gao, Y., Jiang, T., Peng, Z., … Fang, J. (2026). A global view of urban land subsidence and its changing trajectories. Nature Cities. https://doi.org/10.1038/s44284-026-00527-8

Image Credits: AI Generated

DOI: 10.1038/s44284-026-00527-8

Keywords: land subsidence, InSAR, urban geohazards, Sentinel-1, groundwater extraction, vertical land motion, sea-level rise, Nature Cities, remote sensing, sinking cities, aquifer compaction, global mapping

The technological heart of the study is Multi-Temporal Interferometric Synthetic Aperture Radar, or MT-InSAR, a technique that has transformed how scientists monitor ground deformation. Synthetic aperture radar satellites bounce microwave signals off the Earth’s surface and record the phase of the returning waves. When the same point on the ground is imaged repeatedly over months or years, tiny changes in the distance between the satellite and the surface shift the phase of the reflected signal. By comparing these phase differences across many acquisitions, researchers can measure ground movement with millimetre-level precision, without ever setting foot on the unstable slope. The Cyprus team processed both ascending and descending orbit datasets, meaning the satellite flew over the study area from different directions, which allowed them to sample the movement of the ground along two distinct lines of sight and to build a more complete picture of the three-dimensional deformation field.

The researchers applied this technique to landslides already catalogued in an existing inventory of southwestern Cyprus, covering slopes classified as active, dormant and relict. This classification matters because it reflects the state of a landslide at the time of mapping: active landslides are currently moving, dormant ones have not moved recently but retain the potential to reactivate, and relict ones are ancient features formed under different climatic conditions that are generally considered stable. The team extracted the Line-of-Sight, or LOS, velocities for each landslide from the radar data and then asked whether the measured rates differed systematically between these activity classes. The answer was emphatic. The largest LOS velocities were observed in landslides characterised as active, followed by dormant and then relict landslides, a hierarchy that confirms the radar measurements are capturing genuine differences in slope behaviour rather than noise.

That validation is more important than it might sound. One of the persistent challenges in landslide science is that inventories are often compiled from aerial photographs, historical records and field visits, all of which involve a degree of subjective judgement. If satellite-derived velocities align cleanly with independently assigned activity classes, it suggests both datasets are reliable and, more intriguingly, that radar could in future be used to update and refine inventories automatically. For a country like Cyprus, where development continues to push onto marginal slopes, an objective, repeatable measure of which landslides are truly moving could directly inform planning decisions and early-warning strategies. The study effectively demonstrates that the velocity signal from space carries real diagnostic information about the state of a landslide.

The second major strand of the analysis asked which materials move fastest, and here the geology of Cyprus provides a striking answer. The largest displacement rates corresponded mostly to outcrops of fine-grained clastic rocks, including marls, radiolarian mudstones and mélange. These rock types share a critical property: weak shear strength. Marls, which are mixtures of clay and calcium carbonate, are notorious in engineering geology because they swell when wetted, slake when dried and lose strength dramatically as pore water pressure rises. Radiolarian mudstones and the chaotic, mixed rock assemblages known as mélange behave similarly, deforming readily under stress. When such weak materials sit on a slope, the resistance to sliding is low, and once movement begins, the ground can creep steadily for years. The radar data confirmed that these lithologies host the fastest-moving terrain in the study area, tying the observed deformation directly to the mechanical properties of the bedrock.

To move beyond simple correlations, the team turned to a machine-learning interpretability tool called Shapley Additive Explanations, or SHAP. Borrowed from cooperative game theory, SHAP analysis quantifies how much each input variable contributes to a model’s prediction for any individual case, distributing credit among factors in a way that is mathematically consistent. In the context of this study, the method allowed the researchers to rank the influence of geological, geomorphological, environmental and geotechnical factors on the measured LOS velocities. The headline finding was unambiguous: rainfall emerged as the primary factor influencing the increase in LOS velocity. In other words, while many ingredients conspire to create a landslide, precipitation is the dominant throttle controlling how quickly the ground moves once instability is established.

This result carries a profound implication for how landslide hazard should be understood and managed. The geological and geotechnical characteristics of a site determine whether a landslide can occur at all; they set the stage by providing weak materials, favourable orientations and susceptible slope geometries. But once a landslide has been initiated, the tempo of its movement is governed largely by the water delivered from above. Rainfall infiltrates the slope, raises pore water pressures within the sliding mass, reduces the effective stress that holds the material together and lubricates the failure surface. The Cyprus findings suggest that monitoring rainfall and incorporating precipitation records into deformation forecasts could substantially improve predictions of when slow-moving slides will accelerate, which is precisely the information that engineers and emergency managers need most.

Among the geotechnical indices examined, two stood out. The Plasticity Index, or PI, a standard measure of how much water a soil can absorb before it transitions between consistency states, generally exhibited a positive correlation with ground velocity. High-PI clays are more compressible, more prone to swelling and shrinkage, and more sensitive to moisture changes, so it makes intuitive sense that slopes founded on such materials move faster. Conversely, the Geological Strength Index, or GSI, a qualitative scale that characterises the overall strength of a rock mass based on its structure and the condition of its discontinuities, demonstrated a weak negative correlation with velocity. Stronger, more intact rock masses move more slowly, as expected, though the weakness of the correlation suggests that intact rock strength plays a secondary role compared with moisture conditions and the intrinsic weakness of fine-grained units.

The choice of Cyprus as a case study gives the work practical weight well beyond the island. Southwestern Cyprus is underlain by the Mamonia Complex and related units, a tectonically jumbled assemblage of weak sedimentary rocks that has produced some of the island’s most problematic ground. Landslides in this region have damaged roads and infrastructure for decades, and the Geological Survey Department of Cyprus, whose scientists provided the geological and geotechnical data underpinning the study, maintains detailed records of the affected areas. The research was funded through the European Union’s Horizon 2020 programme under a Marie Skłodowska-Curie grant, reflecting the European dimension of the problem: weak, clay-bearing formations and intensifying rainfall extremes threaten slopes across the entire Mediterranean basin, from Italy and Greece to Turkey and North Africa.

What makes the study resonate beyond its regional focus is the methodological template it offers. By fusing freely available satellite radar data with conventional geological mapping and laboratory-derived geotechnical indices, and by interrogating the relationships with a modern interpretability framework, the researchers have shown how the pieces of the landslide puzzle can be assembled quantitatively rather than anecdotally. The approach requires no expensive ground instrumentation, can be repeated as new satellite acquisitions arrive, and scales naturally from a single slope to an entire country. As climate change intensifies rainfall variability across the Mediterranean and elsewhere, the ability to identify which slopes are moving, how fast, and what drives their acceleration will become an essential tool for protecting communities. The Cyprus study suggests that the answer, at least for the fastest-moving hazards, may literally be falling from the sky.

Subject of Research: Statistical correlation of InSAR-derived landslide ground movement rates with activity class and geological, geotechnical and climatic causal factors in southwestern Cyprus

Article Title: Correlating InSAR-derived ground movement rates with landslide activity class and causal factors: a case study from Cyprus

Article References: Tzampoglou, P., Loukidis, D., Tolomei, C., & Svigkas, N. (2026). Correlating InSAR-derived ground movement rates with landslide activity class and causal factors: a case study from Cyprus. Scientific Reports. https://doi.org/10.1038/s41598-026-74387-6

Image Credits: AI Generated

DOI: 10.1038/s41598-026-74387-6

Keywords: InSAR, landslides, Cyprus, MT-InSAR, rainfall, SHAP analysis, geotechnical indices, Plasticity Index, Geological Strength Index, marls, remote sensing, natural hazards

The study, published in the journal Natural Hazards, was led by Ademola Ibironke and Xing Wu of the Department of Civil and Environmental Engineering, together with Fayez Albalawi, Aawaz Gautam, and earth scientist Joseph Kruger. Their focus was Jefferson County, a low-lying expanse of Gulf Coast wetlands, refineries, and pipeline rights-of-way where even modest vertical ground motion can threaten buried infrastructure, alter drainage patterns, and amplify flood risk. Rather than relying on a single snapshot of the terrain, the team exploited a powerful but underused resource: two independent airborne LiDAR surveys of the county, one acquired in 2006 by the Texas Water Development Board and another in 2017, eleven years apart.

Airborne LiDAR works by firing hundreds of thousands of laser pulses per second from an aircraft toward the ground and timing the returning echoes to reconstruct the three-dimensional shape of the landscape as a dense point cloud. When two such surveys are captured years apart, subtracting one from the other yields a map of surface-elevation change at decimeter-scale vertical resolution, far finer than most satellite or surveying alternatives. The catch is the data volume. A single LiDAR tile covering a fraction of a county can contain tens of millions of points, each tagged with coordinates, classification codes, and metadata. Aligning two point clouds acquired with different sensors, flight paths, and classification conventions, then computing reliable elevation differences, is exactly the kind of repetitive computational choreography that humans perform slowly and inconsistently.

The researchers set up a head-to-head comparison between two workflows. The first was a conventional approach built in ArcGIS Pro, the industry-standard geographic information system, in which an analyst manually loads the LAS-format point clouds, filters them, interpolates them into digital elevation models, and runs the differencing tools step by step. The second was a Python-enhanced workflow that wrapped the same core geoprocessing operations into an automated script, chaining together point-cloud processing, spatial matching between the two survey epochs, and the final elevation-change calculations without continuous human supervision. The goal was not to invent new science so much as to industrialize an existing one, turning a bespoke analysis into something a monitoring agency could run repeatedly across hundreds of tiles.

The headline result is strikingly simple: for a representative single LiDAR tile processed through both pipelines, the Python-enhanced workflow cut processing time by approximately 77 percent. That figure matters because the bottleneck in LiDAR-based change detection has never been the physics of the laser; it has been the hours of analyst time consumed by clicking through menus, waiting for tools to finish, and re-running steps when parameters change. By automating the chain, the team effectively converted a multi-hour manual session into a largely hands-off computation, while producing spatial patterns of elevation loss and gain that were broadly comparable between the two methods. The authors are careful to note that localized differences appeared at the level of individual points, a reminder that automation changes the numerical details even when the big picture holds steady.

Those spatial patterns themselves tell an interesting story. Across the pipeline corridors of Jefferson County, the differenced LiDAR surfaces revealed a patchwork of elevation loss and gain rather than a uniform regional signal. Some stretches of ground dropped measurably between 2006 and 2017, while adjacent areas rose, reflecting the competing influences of sediment deposition, land development, excavation, vegetation change, and possibly deeper-seated compaction. This spatial variability is precisely why a screening tool is valuable: instead of assuming the entire corridor behaves the same way, operators can use automated change maps to flag specific hotspots where the surface has moved enough to warrant a closer look with field instruments.

The team did not stop at the LiDAR comparison. They also qualitatively cross-checked their results against two entirely independent sources of vertical-motion information: repeated RTK and GNSS survey measurements on geodetic benchmarks in the county, and interferometric synthetic aperture radar, or InSAR, which measures ground deformation from satellites. The authors are refreshingly candid about the limits of this comparison. Because the GNSS, InSAR, and LiDAR datasets differ in acquisition periods, spatial resolution, measurement characteristics, and the locations of their observations, they cannot serve as direct validation of the LiDAR-derived rates. Instead, they function as independent sanity checks, and the broad agreement in the general pattern of motion lends confidence without overstating precision.

Equally notable is what the researchers refuse to claim. Observed elevation losses along the corridors were not interpreted as confirmed land subsidence, because land development, erosion, deposition, and other localized surface modifications can all imprint themselves on a differenced terrain model. A bulldozed pad site, a dredged canal, or a freshly deposited layer of sediment can look, in a LiDAR difference map, remarkably like genuine ground sinking. By framing their output as a screening product rather than a subsidence diagnosis, the team has drawn a scientifically defensible line that many remote-sensing studies blur. The maps identify where to look; they do not, by themselves, explain why the ground moved.

The broader context makes the work timely. Southeast Texas sits on sediments deposited by ancient and modern river deltas, and the northern Gulf of Mexico coast has documented some of the fastest relative subsidence rates in the United States, driven by fluid withdrawal, sediment compaction, and sea-level rise. Previous work by co-author Joseph Kruger and colleagues has used repeated GPS measurements of National Geodetic Survey benchmarks to chart subsidence rates for flood-risk planning in the region, and recent satellite-based vertical land motion studies in Greater Houston have highlighted how infrastructure itself can be monitored from orbit. The Lamar study adds a complementary, high-resolution aerial perspective that can zoom in on the narrow corridors where pipelines actually run, a scale at which regional satellite products and sparse benchmark networks leave gaps.

For pipeline operators, the practical appeal is scalability. A corridor network spanning hundreds of kilometers crosses many LiDAR tiles, and a workflow that requires an analyst to babysit every tile simply does not scale to routine monitoring. A scripted workflow that can be re-run whenever a new survey flies, with consistent parameters and reproducible outputs, turns multi-temporal LiDAR from a one-off research exercise into an operational screening capability. The authors suggest that the automated approach can help prioritize locations for further field investigation and for complementary ground-deformation monitoring, whether that means leveling surveys, GNSS campaigns, or targeted InSAR time-series analysis at flagged hotspots. In an era when coastal infrastructure faces rising seas, intensifying storms, and slow but relentless ground motion, teaching a script to find the sinking spots first may prove one of the quiet but consequential wins of modern geospatial automation.

Subject of Research: Automated multi-temporal LiDAR analysis of surface-elevation changes along pipeline corridors

Article Title: Automated multi-temporal LiDAR analysis of surface-elevation changes along pipeline corridors using ArcGIS Pro and Python

Article References: Ibironke, A., Albalawi, F., Gautam, A., Wu, X., & Kruger, J. (2026). Automated multi-temporal LiDAR analysis of surface-elevation changes along pipeline corridors using ArcGIS Pro and Python. Natural Hazards, 122(21), Article 668. https://doi.org/10.1007/s11069-026-08429-7

Image Credits: AI Generated

DOI: 10.1007/s11069-026-08429-7

Keywords: LiDAR, land subsidence, pipeline monitoring, Python automation, ArcGIS Pro, point-cloud processing, remote sensing, Jefferson County Texas, infrastructure monitoring, InSAR, ground deformation, geospatial analysis

The tectonic backdrop is dramatic. Off the Pacific coast, the Nazca Plate slides obliquely beneath the South American Plate, and the collision of the buoyant Carnegie Ridge with the margin pushes a sliver of crust, the Northern Andean Sliver, northeastward at 5.8 to 9.5 millimeters per year relative to stable South America. For decades, geoscientists assumed that most of this sliver motion was absorbed along its great eastern boundary faults, such as the Chingual-Cosanga-Pallatanga-Puná system in Ecuador and the Cayambe-Afiladores-Sibundoy system in Colombia. But more recent GPS-based block models have revealed a more fragmented picture: the sliver itself is broken into several independently moving microblocks, each bounded by faults that must absorb their share of the deformation. One of these, the Quito-Latacunga microblock, sits in the Inter-Andean valley, home to Quito and hundreds of thousands of people living near active faults and volcanoes.

Geodetic models predicted about 3 millimeters per year of right-lateral strain along the microblock’s northern edge, near the border between Ecuador and Colombia. The problem was that no one knew which faults actually carried that motion. GPS stations in the region are spaced tens of kilometers apart, far too sparse to resolve whether the strain is concentrated on one through-going structure or smeared across many. The distinction is critical for hazard assessment. A single, long, mature fault with a high slip rate could produce very large earthquakes at relatively short intervals, whereas a family of smaller, segmented faults would limit rupture size but spread the hazard across a wider area, complicating everything from building codes to emergency planning.

The catalyst for the new work came on 25 July 2022, when a magnitude 5.6 earthquake struck about 10 kilometers northeast of El Angel and roughly 15 kilometers southeast of the Chiles-Cerro Negro volcanic complex. The earthquake was remarkably shallow, with a hypocentral depth of less than 5 kilometers, and its focal mechanism indicated almost purely strike-slip motion. Using interferometric synthetic aperture radar, or InSAR, from both the European Sentinel-1 C-band satellites and the Japanese ALOS-2 L-band sensor, the research team mapped the coseismic deformation in unprecedented detail. The interferograms revealed a surface rupture oriented roughly east-northeast, with line-of-sight displacements of 5 to 13 centimeters. In the eastern section, a discrete rupture trace extended over 5 kilometers, while to the west the deformation splintered into en-echelon strands and diffuse off-fault deformation, a signature of a fault zone that is young, immature, and geometrically complex.

Field reconnaissance three months after the earthquake confirmed the InSAR mapping in a limited way: subvertical cracks a few centimeters wide were found on the walls of an irrigation channel precisely where the radar data placed the rupture. Dense vegetation in the El Angel ecological reserve and landslide-blocked roads made the terrain difficult to survey, and the thick, organic-rich Andisol soils, which can deform ductilely, likely absorbed much of the shallow slip. But the earthquake had done its job as a scientific beacon, pointing the team toward a previously underappreciated fault, now named the 25 July fault, that cuts across glacial moraines near the microblock’s northern edge.

To place this rupture in context, the researchers turned to remote sensing at multiple scales. They used 4- and 5-meter digital terrain models from lidar and GeoSAR surveys, satellite imagery, and, crucially, new high-resolution terrain models built from Pleiades tri-stereo satellite images processed with the NASA Ames Stereo Pipeline. These data revealed a swarm of southwest-to-northeast-trending lineaments within a zone roughly 70 kilometers wide, oblique to the better-known north-trending thrust faults of the region. Two structures stood out: the Reservoir fault and the Polylepis fault, both north of and subparallel to the 2022 rupture. Along the Reservoir fault, the Pleiades models showed fault scarps up to 3 meters high, sag ponds where streams had been dammed, landslides, and, most tellingly, glacial lateral moraines and stream channels offset right-laterally by measured amounts ranging from about 5 to 37 meters.

Dating those offset landforms required two independent geochronological tools. The team sampled large, fresh andesitic and basaltic boulders embedded in the moraine crests and measured cosmogenic helium-3 in pyroxene grains, which records how long the boulders have been exposed to cosmic rays since glaciers deposited them. The exposure ages clustered between roughly 11.9 and 20.4 thousand years, consistent with deglaciation at the end of the last glacial maximum in the tropical Andes. Dividing the measured offsets by these ages yields slip rates on the Reservoir fault between about 0.8 and 6.1 millimeters per year, depending on which offset and age combinations are used. Notably, the higher end of this geologic range exceeds the 3 millimeters per year predicted by the geodetic block model, an intriguing discrepancy that the authors attribute, at least in part, to the influence of the nearby volcano.

Roadcut exposures along the Reservoir fault provided a paleoseismic record. A vertical fault zone cuts through post-glacial sediments and volcanic soils, with three stacked colluvial wedges marking three separate surface-rupturing earthquakes. Radiocarbon dating of organic-rich Páramo soils, analyzed with Bayesian modeling in OxCal, brackets the events at about 7,030, 4,890, and 4,320 years before present, implying an average recurrence interval of roughly 2,300 years for large ruptures. Scaling relations linking rupture length and displacement to magnitude suggest these prehistoric earthquakes were between magnitude 6.3 and 7.0. Significantly, the Reservoir, Polylepis, and 25 July faults all fall within the proposed epicentral area of the destructive 15 August 1868 earthquake, estimated at magnitude 6.4 to 6.8, which damaged the town of El Angel. The fresh-looking surface expression and recent landslides along the Polylepis fault lead the team to speculate that it may have hosted that event, though dedicated paleoseismic trenching will be needed to confirm it.

Perhaps the most provocative element of the study is the proposed link between faulting and volcanism. The Chiles-Cerro Negro volcanic complex has been inflating since 2014, with InSAR documenting uplift rates of up to 2.9 centimeters per year and ground spreading away from a north-south axis through the volcano. The researchers argue that this inflation could mechanically load the adjacent faults, inducing right-lateral shear on the 25 July fault and potentially triggering earthquakes through elevated pore fluid pressures, a mechanism previously invoked for a 2014 magnitude 5.6 event south of the volcano. If volcanic unrest periodically accelerates slip, the geologic slip rates over the Holocene could legitimately exceed the decadal geodetic averages, resolving the apparent mismatch between the two datasets. The same logic may explain why ancient terrane-bounding suture zones near Chiles-Cerro Negro are not being reactivated, while in southern Colombia, near the Galeras volcano, the Romeral shear zone is being reactivated as active right-lateral reverse faults such as the Buesaco and Aranda faults, which slip at 0.7 to 2.6 millimeters per year.

Taken together, the results portray the northern boundary of the Quito-Latacunga microblock as a crustal-scale distributed shear zone rather than a discrete plate-boundary-style fault. No sharp velocity gradient appears in the InSAR data, seismicity is diffuse rather than aligned, and the mapped faults are discontinuous, segmented, and spread over tens of kilometers. For the communities of El Angel, Tulcán, Ibarra, Pasto, and Túquerres, the message is sobering but actionable: the hazard is real, distributed, and comes from multiple sources, each capable of magnitude 7 events, and possibly modulated by the breathing of the volcanoes above them. The study’s open dataset, including the Pleiades terrain models, offset measurements, and dating results, now provides a foundation for the denser GPS networks, systematic paleoseismic trenching, and refined hazard models that this tectonically restless corner of the northern Andes urgently needs.

Subject of Research: Distributed right-lateral faulting and earthquake hazard at the northern boundary of the Quito-Latacunga microblock in Ecuador and Colombia

Article Title: Distributed right-lateral strain at the northern boundary of the Quito-Latacunga microblock

Article References: Harrichhausen, N., Marconato, L., Audin, L., Lacan, P., Baize, S., Jomard, H., Alvarado, A., Hollingsworth, J., Blard, P.-H., Mothes, P. A., Rolandone, F., & Ortiz Martin, I. D. (2026). Distributed right-lateral strain at the northern boundary of the Quito-Latacunga microblock. Solid Earth, 17(5), 763-787. https://doi.org/10.5194/se-17-763-2026

Image Credits: AI Generated

DOI: 10.5194/se-17-763-2026

Keywords: Ecuador, Colombia, Quito-Latacunga microblock, strike-slip faulting, InSAR, paleoseismology, cosmogenic dating, Chiles-Cerro Negro, Northern Andean Sliver, seismic hazard, tectonic blocks, volcano-tectonic interaction

Interferometric Synthetic Aperture Radar, or InSAR, has become the workhorse of subsidence science. By comparing radar signals returned from the same patch of ground on repeated satellite passes, InSAR can in principle map surface-elevation change across entire coastlines at fine resolution, something no network of ground instruments can match. But a team led by Guandong Li of Tulane University, together with Torbjörn E. Törnqvist and Jingyi Chen of the University of Texas at Austin, has found that two recent, independently produced InSAR datasets covering the same stretch of the Gulf Coast yield strikingly different pictures of where and how fast the land is moving.

The two datasets in question, published in 2024 by Ohenhen and colleagues and by Wang and colleagues, cover overlapping territory from Texas to western Mississippi. On paper, their headline numbers look reassuringly similar: mean surface-elevation change rates of −3.3 ± 1.8 and −2.8 ± 2.8 millimeters per year respectively. Yet when the researchers compared the maps pixel by pixel, converting the finer 50-meter resolution of one dataset to match the 1-kilometer resolution of the other, the spatial correlation between the two was almost nonexistent, with an R-squared of just 0.05. Nearly a third of the study area showed absolute differences in rate exceeding 3 millimeters per year, and 7 percent differed by more than 5 millimeters per year. A Kolmogorov-Smirnov test confirmed the two datasets follow statistically distinct distributions.

The pattern of agreement and disagreement was itself revealing. In medium to highly developed urban areas, where buildings and other hard structures act as strong, stable radar reflectors, the correlation between the two datasets rose above 0.5. In wetlands, agricultural land, and upland vegetation, it collapsed below 0.05. The explanation lies in the physics of radar scattering: dense vegetation and flooding destroy the phase coherence that InSAR depends on, while plant growth and sediment accretion mean the radar signal reflects the top of the vegetation canopy or the land surface rather than the stable foundation beneath. In such settings, InSAR measures surface-elevation change, a composite of subsidence offset by vertical accretion, rather than true vertical land motion. Independent field measurements in Louisiana’s coastal wetlands, combining rod surface-elevation tables with GNSS data, have found subsidence rates approaching −10 millimeters per year, far more negative than either InSAR dataset reports, underscoring how much of the sinking signal the satellite technique misses in vegetated landscapes.

To establish an independent benchmark, the team turned to the Global Navigation Satellite System. GNSS stations provide precise point measurements of vertical land motion, but in the Holocene sediments of coastal Louisiana their foundations, typically about 15 meters deep, sit above much of the shallow compaction, complicating interpretation. The researchers therefore focused on the Pleistocene uplands immediately inland of the coastal zone, ancient landscapes where sediment compaction and accretion are negligible and GNSS measurements can be taken as representative of the whole column. After excluding sites in Texas affected by groundwater and hydrocarbon extraction, and removing five additional sites with unusually high nearby withdrawal rates, they were left with 36 clean records averaging nearly 14 years of data.

The result was a remarkably uniform background subsidence rate of about −1.2 millimeters per year across the Pleistocene landscape. Neither InSAR dataset could reproduce it. In the portion of the uplands covered by both satellite products, the InSAR-derived mean rates clustered around −3.0 millimeters per year, significantly more negative than the GNSS benchmark, with distributional tests showing the differences were highly significant. Site-level comparisons confirmed the mismatch: one dataset was consistently offset from the GNSS values, while the other matched the averages better but correlated poorly site by site. The team also ruled out temporal variability as an explanation, showing that GNSS rates computed for 2007–2020 and 2017–2020, the respective windows of the two satellite datasets, were statistically indistinguishable.

With sediment compaction, fluid extraction, and faulting excluded, the prime suspect for the background sinking is glacial isostatic adjustment, the slow rebound of the Earth’s crust following the demise of the North American ice sheets, which tilts the Gulf Coast downward like the far end of a seesaw. Comparing the GNSS rates with two regional geophysical models, the researchers found the observations align best with a model that had been considered anomalously high when published in 2014. The implication is provocative: GIA-driven subsidence along the central Gulf Coast may be roughly twice as large as previously believed, in the neighborhood of −1.3 millimeters per year rather than −0.6. If so, some regional projections of long-term relative sea-level change may have underestimated the contribution of this deep Earth process, and the total subsidence budget of the region will need re-evaluation. Recent three-dimensional GIA modeling, which nearly doubles Gulf Coast estimates relative to simpler one-dimensional Earth models, lends further support to the higher rates.

Why do the satellite products disagree so badly? The authors point to a cascade of technical culprits. Tropospheric noise in individual interferograms over the Gulf Coast can reach 10 centimeters or more, while the signals of interest are measured in millimeters per year, demanding thousands of high-quality interferograms to average the noise down. Dense vegetation destroys coherence and limits exactly those observations. On top of that, the two studies made different processing choices: one fused L-band and C-band radar data while the other used C-band alone; they adopted different referencing strategies, coherence thresholds, phase-unwrapping methods, and atmospheric corrections. In low-coherence environments, even small variations in filtering or multi-looking can shift the resulting rates substantially. Both teams had validated their products against GNSS with reported uncertainties of roughly 1.5 to 2 millimeters per year, yet the internal inconsistencies between them far exceed those figures.

The practical consequences are immediate. Based on the differences between the two datasets even in the most reliable urban settings, the study recommends that vertical velocities below 5 millimeters per year derived from coastal InSAR be interpreted with utmost caution, and suggests an uncertainty of 5 millimeters per year for areas lacking nearby ground-truth stations. For planners deciding where to build levees, elevate roads, or prioritize wetland restoration, that margin is not trivial; it spans the difference between stable ground and meaningful hazard. The authors call for harmonized processing frameworks, standardized reporting of methods and assumptions, and systematic cross-calibration exercises modeled on successful community efforts such as the Coupled Model Intercomparison Project in climate science.

The study is a reminder that impressive maps are not the same as reliable measurements. InSAR remains an extraordinary tool, and in cities its performance is genuinely robust. But across the vegetated, subsiding deltas where the flood risk is most acute, the technique is still finding its footing. Until the discrepancies are resolved through open, reproducible pipelines and independent ground constraints, the sinking Gulf Coast will keep its secrets partially hidden, and the millions who live there will need every measurement they can trust.

Subject of Research: Evaluation of InSAR-derived surface-elevation change rates and background subsidence along the central U.S. Gulf Coast

Article Title: Evaluating InSAR-derived rates of surface-elevation change along the central U.S. Gulf Coast

Article References: Li, G., Törnqvist, T. E., & Chen, J. (2026). Evaluating InSAR-derived rates of surface-elevation change along the central U.S. Gulf Coast. Earth Observation, 1(1), 1-13. https://doi.org/10.5194/eo-1-1-2026

Image Credits: AI Generated

DOI: 10.5194/eo-1-1-2026

Keywords: InSAR, subsidence, Gulf Coast, GNSS, glacial isostatic adjustment, sea-level rise, vertical land motion, remote sensing, coastal hazards, Mississippi Delta, Sentinel-1, wetlands