GCRI · Oceans and Coasts
Ports and maritime infrastructure
Ports, coastal roads, power plants, airports and defences sit at the shoreline because they need the sea or the flat land beside it. That location exposes them to storm surge, waves, wind and rising sea level, and port disruption interrupts trade, fuel and food supply. This page sets out how coastal infrastructure is affected by ocean hazards, how exposure is assessed, and what evidence serves the authorities and operators responsible.
Ports and maritime infrastructure in seven parts.
- 01The questionPorts and maritime infrastructure: how the risk develops
- 02Across the domainsPorts connect the sea to every domain on land
- 03IndicatorsWhat is measured, and how well
- 04SourcesWhere the evidence comes from
- 05DecisionsWho decides, and what the evidence serves
- 06Core questionsThe questions experts ask
- 07MechanismsHow ports are disrupted
Ports and maritime infrastructure: how the risk develops.
Coastal transport and continuity. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Ports are exposed by design
Ports sit at the water’s edge with low quays, cranes and storage. Storm surge and waves flood terminals, damage equipment and close channels.
Wind and waves stop operations
Cranes stop above wind limits, and pilots and ships cannot enter in high waves. Operational downtime can exceed physical damage in cost.
Rising seas reduce margins
Quay heights and drainage designed for past sea levels lose freeboard as the sea rises, so the same storm floods more often.
Coastal assets connect inland
Ports depend on roads, rail, power and fuel supply that may also flood. Disruption spreads inland through supply chains.
Ocean state in Pacific Island states.
Marine heat, chlorophyll and sea temperature over Pacific Island states, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Ocean state, for this page
About this layer
- Evidence
- Observed
- Source
- GHRSST MUR25 (NASA JPL PO.DAAC)
- Provider
- NASA JPL PO.DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite analysis
- Newest at build
- 2026-10-12
- Resolution
- about 2 km grid
- Uncertainty
- Satellite analysis of how far sea temperature departs from its usual value for the date shown; a marine heat indicator, not a coral bleaching alert.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds and sun glint leave gaps)
- Source
- MODIS Aqua ocean colour (NASA OB.DAAC)
- Provider
- NASA OB.DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite retrieval; clouds and sun glint leave gaps
- Newest at build
- 2026-10-13
- Resolution
- about 1 km grid
- Uncertainty
- Satellite estimate of chlorophyll-a near the sea surface on the day shown, an indicator of plankton and ocean productivity; not a measure of fish stocks or harmful blooms.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- GHRSST MUR (NASA JPL PO.DAAC)
- Provider
- NASA JPL PO.DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite analysis
- Newest at build
- 2026-10-12
- Resolution
- about 1 km grid
- Uncertainty
- Gap-filled satellite analysis of sea surface temperature for the date shown; not a reef or species condition report.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Estimated
- Source
- Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
- Provider
- NASA SEDAC (CIESIN, Columbia University)
- Licence
- CC BY 4.0
- Vintage
- null; Census-based estimate, static (2020)
- Resolution
- about 1 km grid
- Uncertainty
- Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Ocean state, framed on Pacific Island states.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA PACE OCI · NASA JPL OPERA DIST-ALERTSources and licences
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- GHRSST Level 4 MUR analyses, NASA Jet Propulsion Laboratory; distributed by the NASA Physical Oceanography DAAC (PO.DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- MODIS Aqua ocean colour, NASA Ocean Biology Processing Group; distributed by the NASA Ocean Biology DAAC (OB.DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Live: NASA EONET Events are indicative, not authority warnings.
- Observed (EO): NASA PACE OCI. We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
- Optional layers (10 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Sea surface temperature anomaly: GHRSST MUR25, NASA JPL PO.DAAC · 12 Oct 2026
- Ocean chlorophyll-a concentration: MODIS Aqua ocean colour, NASA OB.DAAC · 12 Oct 2026
- Sea surface temperature: GHRSST MUR, NASA JPL PO.DAAC · 12 Oct 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
Ports connect the sea to every domain on land.
Port analyses are designed for the Strategic Systems series. UNCTAD’s maritime review (2024) and the ISPS Code frame operations and security; operators keep sensitive layouts.
- Port disruption records.
- Climate adaptation plans for ports.
Coastal adaptation pathways.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Coastal adaptation pathways
Ports and maritime infrastructure · Coastal zone A · Sea level scenario set
Flood extent by scenario
illustrative coastline
Relative sea level
Adaptation pathways
| Dune nourishment | 0.4 | 1 | Raise seawall | Overtopping twice in 5 yr |
| Raise seawall | 0.7 | 10 | Managed realignment | Seawall at design limit |
| Managed realignment | 1.3 | 11 | Relocate assets | Community decision |
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Quay elevation above extreme sea level | metres | per assessment | Port surveys and sea-level analysis | ESTIMATED |
| Operational downtime from weather | hours per year | annual | Port operational records | OBSERVED |
| Coastal infrastructure in flood hazard zones | count and value | per assessment | Asset maps and hazard maps | ESTIMATED |
| Storm damage to port facilities | events with recorded damage | annual | Port and insurance records | REPORTED |
| Wave height at harbour entrance | metres | hourly | Wave buoys and models | OBSERVED |
| Ports with climate adaptation plans | count | per assessment | Port authority disclosures | DECLARED |
A shock through an input-output economy.
A loss of output in one sector propagates through the technical coefficients to its suppliers and customers, and recovers at the rate you set; the coefficients are teaching values, not national accounts. Teaching model with stated illustrative values, not a prediction. The map on this page shows Pacific Island states; the model itself is not tied to a place.
Controls
- Sector hit first (position in the list)
- 0
- Size of the shock
- 30% of its output
- Duration of the shock
- 30 days
- Recovery rate
- 0.08 per day
- Days simulated
- 180 days
Readouts
- Output lost over the run
- 0.73% of a year’s output
- Total over direct (multiplier)
- 1.58 times
- Most affected other sector
- Trade
- Its peak inoperability
- 3.1%
Numbers, methods and sources
| Sector | Peak inoperability (%) | Output weight (%) |
|---|---|---|
| Agriculture | 30.14 | 19.7 |
| Energy | 0.59 | 12.4 |
| Manufacturing | 2.64 | 14.7 |
| Transport and ports | 0.89 | 21.2 |
| Trade | 3.15 | 17.9 |
| Services | 0.70 | 14.1 |
Methods
- Input-output analysis Leontief (1936); Miller and Blair (2009), Input-Output Analysis, Cambridge University Press
- Inoperability input-output model Haimes and Jiang (2001), Journal of Infrastructure Systems 7
- Dynamic inoperability and recovery Lian and Haimes (2006), Systems Engineering 9
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
- Seaports Natural Earth
- Maritime chokepoints Nexus (named straits and canals at their published coordinates)
- Railways Natural Earth
- Major roads Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Oceans and Coasts in Foundry
- Tested at Oceans and Coasts in Universe
- Codified in Climate and Earth Systems in Standards
- Published in Oceans and Coasts in Reports
- Taught in Faculty of Earth and Environmental Sciences in Academy
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| UNCTAD climate adaptation of ports reports and surveys | Port exposure and adaptation practice | Public, UNCTAD terms (to check) |
| PIANC guidance on climate change adaptation for waterborne transport infrastructure | Engineering guidance for ports and waterways | Licence per publication |
| Copernicus Marine Service wave and sea level products | Wave and water level hindcasts and forecasts | Free, Copernicus Marine licence |
| IMF PortWatch | Port activity and disruption estimates | Public, IMF terms (to check) |
| Coastal infrastructure from OpenStreetMap | Locations of ports, roads and facilities | Open, ODbL |
Model ports and maritime infrastructure as a system. Run the cascade.
Assembled from the Nexus Standards area profile Oceans and coasts risk standards: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
- Sea-level rise
- Storm surge
- Coastal erosion
- Heatwave
- Ocean acidification
- Harmful algal bloom
- Extreme fire weather (set off downstream)
- Wildfire (set off downstream)
- Heat-driven grid stress (set off downstream)
- Agricultural drought (set off downstream)
- Flash drought (set off downstream)
- Snow drought (set off downstream)
- Ground-level ozone episode (set off downstream)
- Meteorological drought (set off downstream)
- River flood (set off downstream)
- Coastal flood (set off downstream)
- Estuary flood (set off downstream)
- Mass displacement (set off downstream)
Systems and couplings
- Oceans and coasts risk standards
- Supply chain and trade risk Cascade
- Food and agriculture risk standards Cascade
- Climate risk standards Common driver and feedback
- Cities and urban systems risk standards Exposure
Controls
NS-0Constitution and principlesNS-1The UNI and the artefact catalogue (grammar v0.2: domain, sector, region and environment segments)NS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-3bDataset and product metadata profile (STAC, DCAT, PROV-O)NS-5Figure, map and visualisation standard (with the UI/UX kit)NS-9Contextual UNIs (deployments, instances, programme instances)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NRS-X3Oceans and coasts riskNRS-H11Hazard family: Coastal and sea-level hazards (NHS-1 water.coastal)NRS-H79Hazard family: Mental health crises (NHS-1 health.mental)NRS-H12Hazard family: Ocean-state extremes (NHS-1 water.ocean-state)NRS-H67Hazard family: Ocean circulation and marine tipping (NHS-1 planet.ocean-tipping)NRS-K18Domain pack profile: Oceans coastal (DOMAIN-018)
Observation
- Copernicus Marine Service ocean products (listed for reference)
- Coral Reef Watch daily 5 km heat stress products (listed for reference)
- PSMSL tide gauge mean sea level records (listed for reference)
- GEBCO global bathymetric grid (listed for reference)
- Argo float profiles (listed for reference)
- Average marine acidity (pH) measured at agreed suite of representative sampling stations
- Index of coastal eutrophication and floating plastic debris density
- Direct economic loss attributed to disasters in relation to GDP, including damage to critical infrastructure
Example geography
- Pacific Island states: 150 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Surface air temperature, daytime (AIRS), NASA GIBS
Who decides, and what the evidence serves.
Oceans and Coasts prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Port authorities and operators | Which adaptation measures to invest in and when | Exposure assessments; downtime analyses |
| Ministries of transport | Which coastal assets need protection or relocation | Infrastructure hazard overlays |
| Coastal engineers and designers | Which design sea levels and wave conditions to adopt | Extreme sea level and wave evidence |
Outputs this topic produces
- Port exposure assessments to surge, waves and sea-level rise
- Operational downtime analyses from wave and wind data
- Design sea level reviews for port upgrades
- Evidence notes on port adaptation
How ports and maritime infrastructure is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
Earth observation chain
How a satellite or sensor record becomes evidence on ports and maritime infrastructure, and where each step adds uncertainty.
- 01 · Acquireorbit, sensor and revisitUncertainty: gaps from cloud and orbit
- 02 · Calibrateradiometric and geometricUncertainty: sensor drift
- 03 · Correctatmosphere and terrainUncertainty: aerosol and slope assumptions
- 04 · Retrieve or classifythe variable or the classUncertainty: model and training error
- 05 · Validateagainst ground truthUncertainty: sample design and size
- 06 · Publishwith error bars and lineageUncertainty: stated, never hidden
The questions experts ask.
- Which port functions are critical, and which hazards can stop them?
- How long can a port be closed before supply of fuel, food or medicines is affected?
- Do quay heights, breakwaters and drainage still perform under higher sea levels?
- How do port disruptions propagate through shipping networks and inland logistics?
- Which dependencies on power, communications and labour create hidden single points of failure?
How ports are disrupted.
Direct physical damage comes from surge and wave overtopping, wind damage to cranes and warehouses, and scour of foundations. Many disruptions are indirect: navigation channels silt up after storms, power or communications fail, access roads flood, or workers cannot reach the port. Heat affects equipment and workers, and low river levels can disrupt inland waterway connections that feed coastal ports.
Shipping networks transmit disruption. A closure at a hub port causes vessels to divert or queue, congestion spreads to neighbouring ports, and schedules take weeks to recover. Islands and remote coasts served by a single port can face shortages quickly. Sea-level rise lowers the effective freeboard of quays and breakwaters, so design margins chosen decades ago shrink.
Ports also shape the coast around them. Dredging, reclamation and breakwaters alter sediment transport and habitats, so port development and adaptation have ecological effects that feed back into flood exposure and fisheries along neighbouring shores.
Engineering and network analysis.
Fragility and design
Fragility curves relate hazard intensity to damage for port assets; design standards set heights and loads.
Shipping and logistics models
Network models of routes and hinterland connections estimate how closures propagate.
Vessel tracking
Automatic identification system data show vessel movements and port calls; access and coverage vary.
Limits: port asset data are often commercially sensitive or incomplete, fragility data for port equipment are limited, and network models simplify how shippers and operators adapt.
How it is studied, and what the methods cannot say.
- 01Ocean and coastal scienceRegional sea-level budgets · Marine heatwave analysis · Wave climate assessmentApplied here
- 02Extreme value theory and tail riskExtreme sea level return levels · Amplification factors · Extreme wave heightsApplied here
- 03Water and environmental engineeringCoastal defence options · Coastal wastewater planning · Adaptation pathwaysApplied here
- 04Geospatial information systemsCoastal exposure mapping · Marine spatial planning layers · Fishing effort mappingApplied here
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
Why are ports vulnerable to climate change?
What is freeboard?
Can ports adapt?
Does the platform assess individual ports?
Is port engineering the platform’s focus?
Where is port continuity tested?
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