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Place data for real decisions

CityMETER

Explore buildings, prices, businesses, people, access and risk through real data, then open the place you need.

Measure What Matters. Make It Actionable.

Real CityMETER screen examples

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  1. Registered population. Age, sex and population-density structure. Registered population is not daytime, resident or live population
  2. 3D buildings in Suan Plu. Gross floor area, building count, height and floors. Open Buildings is not a building register and may not cover every structure
  3. Municipal revenue. Revenue sources, revenue per person and revenue per area. Revenue alone is not service quality or fiscal health
  4. Tourism demand. Visitors, spending, seasonality and province comparison. Visitor counts are not unique people and figures may be revised
Built formGFA · height · floorsBuilding metrics visible in the working implementation
Spatial detailProvince · locale · sensor stationOnly evidenced units are shown for each record
Open directly38 data views and modulesEach record states its own scope

Start with the decision

What are you trying to decide?

Choose a question to see a working example and the relevant data—no dataset names to memorise.

Open the real thing

Examples that lead back to the place and source

Start with real views that reveal what is interesting about a place, then open the sources, scope and details when you are ready to decide.

Business Dynamics: Headquarters, Branches & New Activity exampleHQ · branches · new activity
location

Business Dynamics: Headquarters, Branches & New Activity

Tell the 50,000-branch network story through headquarters, sectors, and newly registered branches

HQ–branch networkNew registered branchesTSIC sectors
A Thailand summary view is visible; source coverage is not stated
Open map
Road Network Archetypes exampleRoad types · dead ends · intersections
location

Road Network Archetypes

Pair coloured archetype areas on the satellite map with dead-end and intersection metrics

Derived modelNetwork archetypesDead-end ratio
Evidenced on the inspected Bangkok route; broader geographic coverage is not verified
Open map
Shopping Centers: Supply, GLA & Market Segment exampleGLA · tenants · segment
location

Shopping Centers: Supply, GLA & Market Segment

Compare retail structure through supply, leasable area, tenant scale, and market segment

Retail supplyGLATenant scale
A Thailand summary view is visible; source coverage is not stated
Open map
Buildings: Footprint, GFA & Height exampleGFA · height · floors
land

Buildings: Footprint, GFA & Height

Pair the province comparison map with GFA, height, and floor metrics to explain development intensity

Built formGFAHeight & floors
A Thailand summary view is visible; source coverage is not stated
Open map
Flood: Recurrent example14 years · recurrence · worst year
living

Flood: Recurrent

Use the 14-year timeline, recurrence count, and worst year as the historical risk baseline

HistoricalRecurrenceWorst year
A Thailand summary view is visible; source coverage is not stated
Open map
Population by Age & Sex exampleAge · sex · density
living

Population by Age & Sex

Use age-sex structure and density as baseline context for market reading and service planning

DemographicsAge & sexDensity
A Thailand summary view is visible; source coverage is not stated
Open map

Explore the data

Find the data that fits your question

Search by topic or browse a group to see examples, coverage and a direct link.

38 DATA VIEWS · 3 LENSES

One city, seen through three connected lenses

Land is the city’s base. Living is people, services and everyday life. Together they show how each Location differs—and how some patterns change over time.

Land12 views

Land · buildings · infrastructure

+
Living13 views

People · services · everyday life

Location13 views

Business · mobility · access

CityMETER

Organises 38 views so people can find, compare and inspect evidence in one place.

LandometerLocal Decisions

Shows what to check next and how to move a place decision forward.

landSpecialist source

Buildings: Footprint, GFA & Height

Explore 3D building intensity, GFA, height and floor counts in Suan Plu

Built formGFAHeight & floors
What you can do with this data
What this data helps you answer

See where buildings concentrate and compare gross floor area, height and floor counts to choose places for closer study.

Coverage
Start with the Suan Plu example, then check source coverage before comparing other places.
Spatial unit
View 3D buildings and area metrics, then check source completeness before relying on individual-building geometry.
Uses a specialist data source
Where the data comes from

Google Research — Open Buildings — CityMETER names Open Buildings directly, so this is an external source rather than GD Catalog lineage.

Before making a decision

Use it to compare building intensity, gross floor area, height and floors at summary level—not as a building register or verified footprint for every structure.

landVerifiedMonthly

Registered Housing Estates

Bring project counts, plot counts, and developer ranking into one frame

RegistryProjectsPlot counts
What you can do with this data
What this data helps you answer

Find permitted housing estates and compare their plot counts, developers and distribution across an area.

Coverage
Geographic coverage is not stated on the public page
Spatial unit
Project and plot counts are visible; project- or plot-level map detail is not verified
Source dataset verified
Where the data comes from

Department of Lands — Project, permit, developer, title-document and plot fields match the official land-allotment permit dataset.

What period the data covers

Monthly nationwide coverage; this card uses the land-allotment part of the package.

Before making a decision

Use it for permit history and project distribution. A permit does not prove completion, current availability or occupancy.

This badge confirms same-dataset lineage through an official owner channel. It does not mean every file was downloaded directly from the central GD Catalog.

landVerifiedSince 1992 · ongoing

EIA Projects & Reports

Compare IEE, EIA, and EHIA project counts alongside their location context

PlanningIEE / EIA / EHIAProjects
What you can do with this data
What this data helps you answer

Find projects with EIA records, compare project type, owner and approval date, and open the source documents for follow-up.

Coverage
A Thailand summary view is visible; source coverage is not stated
Spatial unit
The project is the evidenced record unit; map geometry and spatial detail are not verified
Source dataset verified
Where the data comes from

ONEP — Project, owner, report type, document, approval date, category and location fields match Smart EIA.

What period the data covers

Nationwide projects since 1992; the live API changes, so the card avoids a frozen total.

Before making a decision

CityMETER is a curated, geocoded snapshot. Approval does not prove construction, operation or current compliance.

This badge confirms same-dataset lineage through an official owner channel. It does not mean every file was downloaded directly from the central GD Catalog.

landCandidate source

Agriculture: Crop Area & Output (10,000 Rai)

See monthly cultivated area and output in Wiang Thong TAO, separated by crop and time period

Land useCrop area & outputTime period
What you can do with this data
What this data helps you answer

See which crops are grown, compare cultivated area and monthly output, and identify places that need closer field or service planning.

Coverage
Start with the Wiang Thong TAO example, then check source coverage before comparing other places.
Spatial unit
View village-level output and the area grid, then review the source transformation before comparing or aggregating results.
Related source identified
Where the data comes from

Department of Agricultural Extension production registry family (candidate) — The field family resembles DOAE production registries, but CityMETER's 2025–2026 monthly grain and taxonomy have not been reconciled to one exact package.

Before making a decision

Use as provisional crop-area and output context until the exact resource, taxonomy and coverage are reconciled.

landVerifiedUpdate cycle varies by province

Land Appraisal & Title Deeds

See the 3D land-appraisal pattern across Mueang Chonburi with deed counts and the price distribution

AppraisalTitle deedsDistribution
What you can do with this data
What this data helps you answer

Compare parcel location, area and official appraisal values to screen sites and prepare questions before parcel-level due diligence.

Coverage
Start with the Mueang Chonburi example, then check source coverage before comparing other places.
Spatial unit
View 3D appraisal zones and deed counts, then check the source before relying on individual parcel shapes.
Source dataset verified
Where the data comes from

Department of Lands / Treasury Department — Combines parcel location and area from the Department of Lands with official Treasury appraisal values.

What period the data covers

Versioned, transformed parcel layer; appraisal update dates vary by province.

Before making a decision

Useful for screening and reference checks before parcel due diligence; it does not prove ownership, encumbrances or transaction price.

This badge confirms same-dataset lineage through an official owner channel. It does not mean every file was downloaded directly from the central GD Catalog.

landExploratory

Land Listing Prices

Show listing supply and price-per-square-wah distribution as an asking-market signal

ListingPrice per areaDistribution
What you can do with this data
What this data helps you answer

Compare asking-price ranges and listing concentrations to shortlist areas for further market checks.

Coverage
Geographic coverage is not stated on the public page
Spatial unit
Listing counts are visible; listing-level coordinates or boundaries are not verified
Exploratory data view
Where the data comes from

Private listing layer — public lineage not yet verified — No exact government-dataset lineage was verified for the land asking-price layer.

Before making a decision

This is an asking-price signal, not a closing price. Verify source, collection date, duplicate handling and outlier treatment before comparison.

landExploratory

Apartment Rent

Use average rent and price ranges to compare rental-market signals between areas

Rental marketPrice rangeDistribution
What you can do with this data
What this data helps you answer

Compare sampled apartment rent ranges across areas before checking current offers in the market.

Coverage
Geographic coverage is not stated on the public page
Spatial unit
Apartment counts and rent statistics are visible; building- or listing-level detail is not verified
Exploratory data view
Where the data comes from

Public source lineage not yet verified — No public package or manifest currently reconciles apartment-rent records to a repeatable source.

Before making a decision

Treat it as a sampled rent-range signal, not the whole market or current rent for every building.

landVerified4-year cycle · checked Aug 2024

Condo Appraisal Prices

Use P25, P50, and P75 as a value baseline before comparing listing prices

AppraisalPercentilesDistribution
What you can do with this data
What this data helps you answer

Find official condominium appraisal values and use a consistent baseline when comparing projects or areas.

Coverage
Geographic coverage is not stated on the public page
Spatial unit
Building counts and price statistics are visible; building- or unit-level map detail is not verified
Source dataset verified
Where the data comes from

Treasury Department — Project/building schema and appraisal values align with the official condominium valuation dataset; CityMETER is a transformed snapshot.

What period the data covers

The source states a four-year cycle; the inspected resource was updated 14 Aug 2024.

Before making a decision

Use it as an official value baseline before market comparison; appraisal is neither listing nor latest transaction price.

This badge confirms same-dataset lineage through an official owner channel. It does not mean every file was downloaded directly from the central GD Catalog.

landCandidate source

Condo Listing Prices

Pair asking prices with appraisal values to reveal the gap before project-level analysis

ListingComparisonPrice range
What you can do with this data
What this data helps you answer

Compare asking prices with appraisal benchmarks to spot unusually high or low gaps for further review.

Coverage
Geographic coverage is not stated on the public page
Spatial unit
Listing-price statistics are visible; listing- or unit-level coordinates are not verified
Related source identified
Where the data comes from

Private asking-price layer + candidate Treasury benchmark — The appraisal benchmark is official, but condo/building IDs and the ETL join to private listings have not been fully evidenced.

Before making a decision

Use the gap as an exploratory signal; project-level use requires duplicate, unit and join-method checks.

landExploratory

Detached Listing Prices

Compare price ranges with land size so the detached-house story is not reduced to one number

ListingPrice rangeLand size
What you can do with this data
What this data helps you answer

Compare detached-house asking prices, land sizes and listing counts to understand market ranges and shortlist areas.

Coverage
Geographic coverage is not stated on the public page
Spatial unit
House and listing records are evidenced; item-level location detail is not verified
Exploratory data view
Where the data comes from

Private listing layer — public lineage not yet verified — No public source manifest yet states coverage, vintage or deduplication rules for detached-house listings.

Before making a decision

Price and land size help screen the market, but these are asking prices and sampling may vary by area.

landExploratory

Townhouse Listing Prices

Use listing counts and percentiles to show both supply and the price range

ListingPercentilesDistribution
What you can do with this data
What this data helps you answer

Compare townhouse listing counts and asking-price ranges to understand indicative supply across areas.

Coverage
Geographic coverage is not stated on the public page
Spatial unit
Listing records and price statistics are visible; item-level location detail is not verified
Exploratory data view
Where the data comes from

Private listing layer — public lineage not yet verified — No public manifest yet documents townhouse listing coverage, date, duplicates or outlier treatment.

Before making a decision

Listing counts and percentiles show supply and asking ranges, not sales volume or closing prices.

landSpecialist source

Condo Rent & Yield (RentWise)

Lead with rent, estimated yield, and investment-score cards rather than a wall of listings

Rental marketEstimated yieldInvestment score
What you can do with this data
What this data helps you answer

Compare estimated condominium rents and yields across areas to shortlist options for a fuller income-and-cost review.

Coverage
Geographic coverage is not stated on the public page
Spatial unit
A large set of listing records is visible; supported coordinate or project detail is not verified
Uses a specialist data source
Where the data comes from

LivingInsider / private listings — CityMETER names LivingInsider directly, so this is not GD Catalog lineage.

Before making a decision

Rent, yield and investment scores are listing-derived; verify assumptions, costs, vacancy and duplicates before decisions.

locationVerifiedApr 2024 – Apr 2025

Registered Companies: Status & Capital

Use company status and capital distribution to explain the business base for the stated period

RegistryStatusRegistered capital
What you can do with this data
What this data helps you answer

See where company registrations and dissolutions concentrate, and compare business types and registered capital across areas.

Coverage
A Thailand summary view is visible; source coverage is not stated
Spatial unit
The legal entity is the evidenced record unit; the smallest map geography is not verified
Source dataset verified
Where the data comes from

Department of Business Development — Uses the legal-entity register and new/dissolution events; CityMETER is a curated, geocoded subset.

What period the data covers

CityMETER snapshot: Apr 2024–Apr 2025; verify each resource title rather than inferring event type from package ID alone.

Before making a decision

Legal registration status is not actual opening or closure, and registered capital is not investment, revenue or employment.

This badge confirms same-dataset lineage through an official owner channel. It does not mean every file was downloaded directly from the central GD Catalog.

locationVerifiedMonthly

Business Dynamics: Headquarters, Branches & New Activity

Tell the 50,000-branch network story through headquarters, sectors, and newly registered branches

HQ–branch networkNew registered branchesTSIC sectors
What you can do with this data
What this data helps you answer

Map VAT-registered branches by business type to shortlist areas for deeper business-base and competitor research.

Coverage
A Thailand summary view is visible; source coverage is not stated
Spatial unit
A province comparison map and HQ–branch records are evidenced
Source dataset verified
Where the data comes from

Revenue Department — Records were reconciled by legal-entity number, branch code, name and address against the VAT operator register.

What period the data covers

Monthly source; CityMETER is a transformed snapshot.

Before making a decision

CityMETER uses an enriched, geocoded 50,000-branch subset. Registered address is not proof of operation at that point and does not cover every business.

This badge confirms same-dataset lineage through an official owner channel. It does not mean every file was downloaded directly from the central GD Catalog.

locationCandidate source

Factories, Workers & Investment

Combine factory, worker, capital, and machinery metrics into one industrial-base story

RegistryWorkforceRegistered capital
What you can do with this data
What this data helps you answer

Compare factories, workers, capital and machinery capacity to understand the industrial base and choose areas for follow-up.

Coverage
A Thailand summary view is visible; source coverage is not stated
Spatial unit
The factory is the evidenced record unit; point detail and the smallest map geography are not verified
Related source identified
Where the data comes from

Industrial factory register (high-confidence candidate) — The field fingerprint matches the factory register, but factory-ID reconciliation or an ETL source manifest is still missing.

Before making a decision

Use the factory, worker, capital and machinery measures exploratorily until definitions, units and registry coverage are confirmed.

locationExploratory

Office Buildings & Rent

Use building supply, area, age, floors, and asking rent to frame Bangkok's office market

Office marketAsking rentHeight & floors
What you can do with this data
What this data helps you answer

Compare Bangkok office inventory and asking rents to see where supply concentrates and how price ranges differ.

Coverage
Bangkok
Spatial unit
The office building is the evidenced record unit; building-level map detail is not verified
Exploratory data view
Where the data comes from

Commercial inventory — public lineage not yet verified — The office-building and asking-rent inventory did not match the official building packages reviewed.

Before making a decision

The evidenced scope is Bangkok. Prices are asking rents, not contracted rent or occupancy.

locationExploratory

Restaurants: Density, Ratings & Price

Use density, reviews, and price bands to explain the local food-competition context

RestaurantsDensityRatings & reviews
What you can do with this data
What this data helps you answer

Compare restaurant density, price bands and ratings to explore competitive context and areas with more or fewer dining options.

Coverage
A Thailand summary view is visible; source coverage is not stated
Spatial unit
The restaurant is the evidenced record unit; point detail and the smallest map geography are not verified
Exploratory data view
Where the data comes from

Private place/review source — public lineage not yet verified — Ratings, price bands and density did not align with the government restaurant registers reviewed.

Before making a decision

Use as competitive context, not demand, customer count or independently verified quality; collection date and coverage are required for comparison.

locationExploratory

Shopping Centers: Supply, GLA & Market Segment

Compare retail structure through supply, leasable area, tenant scale, and market segment

Retail supplyGLATenant scale
What you can do with this data
What this data helps you answer

Compare shopping-centre size, type, market segment and tenant counts to understand retail structure and local competitors.

Coverage
A Thailand summary view is visible; source coverage is not stated
Spatial unit
A province comparison map and shopping-centre records are evidenced
Exploratory data view
Where the data comes from

Commercial inventory — no matching government package verified — GLA, GFA, tenant count and market segment did not match the government datasets reviewed.

Before making a decision

Use to compare retail structure in the sample; unequal field coverage means it should not be presented as market totals.

locationCandidate source

Hotel Supply, Rates & Seasonality

Use hotel supply, rooms, ADR, and the seasonal curve to frame the market and an initial comparison set

Hotel supplyADRSeasonality
What you can do with this data
What this data helps you answer

Explore the displayed accommodation, room, asking-rate and seasonality measures to choose areas for further hotel-market checks.

Coverage
Geographic coverage is not stated on the public page
Spatial unit
Hotel and room records are evidenced; hotel-level map detail is not verified
Related source identified
Where the data comes from

Tourism Authority of Thailand — Accommodation (candidate) — The field signature closely resembles TAT Accommodation, but hotel and room totals have not been reconciled to the same snapshot.

Before making a decision

Use supply, asking-rate and seasonality as an initial comparison—not as occupancy, bookings or hotel revenue.

locationVerifiedMonthly · by province

Tourism Demand: Visitors & Spending

Use visitors, spending, spend per visitor, change, and province ranking to tell the demand story

Tourism demandVisitorsSpending
What you can do with this data
What this data helps you answer

Compare visitor volume, spending, seasonality, activities and attractions to choose provinces or periods for further service planning.

Coverage
A Thailand summary and province ranking are visible; source coverage is not stated
Spatial unit
Province is the smallest comparison geography evidenced on the inspected page
Source dataset verified
Where the data comes from

Ministry of Tourism and Sports / Tourism Authority of Thailand — Demand reconciles to the official MOTS workbook after unit conversion; activities and attractions use official TAT channels.

What period the data covers

Year–month–province grain; exact values reconcile to the official workbook, not every byte of the frozen GD JSON.

Before making a decision

Compare visitors, receipts, seasonality, activities and attractions. Visitor counts are not unique people and figures may be revised.

This badge confirms same-dataset lineage through an official owner channel. It does not mean every file was downloaded directly from the central GD Catalog.

locationExploratory

Fuel Stations: Count, Density & Fuel Types

Use station counts, density, and fuel mix to explain automotive-service availability

StationsDensityFuel mix
What you can do with this data
What this data helps you answer

Explore the displayed mix of EV, LPG, NGV and conventional-fuel services to choose areas for checking actual stations and availability.

Coverage
A Thailand summary view is visible; source coverage is not stated
Spatial unit
The station is the evidenced record unit; point detail and the smallest map geography are not verified
Exploratory data view
Where the data comes from

No official package yet matches the displayed fuel mix — The DOEB package reviewed did not contain the same EV, LPG, NGV and fuel-availability mix shown by CityMETER.

Before making a decision

Use as provisional automotive-service context until station definition, effective date and multi-fuel counting are verified.

locationVerifiedJan 2020 – Feb 2026

Registered Cars

Pair the province map with brand, model, category, and period to explain the registered-vehicle base

Vehicle registryBrand & modelTime period
What you can do with this data
What this data helps you answer

Track first registrations by vehicle type, make and model to see how registration patterns change month by month.

Coverage
A Thailand summary view is visible; source coverage is not stated
Spatial unit
Province comparison is evidenced; individual-vehicle detail is not supported
Source dataset verified
Where the data comes from

Department of Land Transport — February 2026 values were reconciled at year, month, vehicle type, make, model and count level.

What period the data covers

Monthly national statistics; CityMETER shows Jan 2020–Feb 2026.

Before making a decision

This is first-registration statistics, not the active fleet, travel behaviour or where vehicles operate.

This badge confirms same-dataset lineage through an official owner channel. It does not mean every file was downloaded directly from the central GD Catalog.

locationDerived

Road Network Archetypes

Explore Pathum Wan road-network archetypes with dead-end ratio, intersection density and Road DNA

Derived modelNetwork archetypesDead-end ratio
What you can do with this data
What this data helps you answer

Compare street patterns, dead ends and intersection density to understand network structure and frame questions for field checks.

Coverage
Start with the Pathum Wan road-pattern example and check the source before comparing other places.
Spatial unit
View the analysis areas and Road DNA metrics, then review how the analytical unit was built before making a decision.
Calculated and summarised by CityMETER
Where the data comes from

CityMETER derived model — This is a derived road-network model rather than an atomic GD Catalog dataset.

Before making a decision

Dead-end and intersection measures are diagnostic signals—not location quality, accessibility, traffic or a good/bad verdict.

locationExploratory

Traffic: Congestion & Speed

Use speed, congestion, and the seven-day trend when the feed status is available

MonitoringCongestionSpeed
What you can do with this data
What this data helps you answer

Read displayed traffic speed and trends to identify routes or time periods that need closer travel-condition checks.

Coverage
Bangkok data route
Spatial unit
The smallest supported geography is not yet verified from the public page
Exploratory data view
Where the data comes from

Current/7-day traffic feed — public source contract not yet verified — The current and seven-day feed did not match the static OTP studies reviewed, and no public SLA was found.

Before making a decision

Use only with timestamp and feed status visible; delayed or unavailable data does not mean free-flow traffic.

locationDerived

Locale Insights

Frame what should be validated in the field rather than presenting behaviour as fact

Contextual priorLocaleTime period
What you can do with this data
What this data helps you answer

Read a concise place profile and suggested questions to prioritise areas and prepare field validation.

Coverage
The default page is scoped to Bangkok; the full locale coverage is not published
Spatial unit
Locale is the smallest selectable unit; geometry and service-boundary crosswalks are not verified
Calculated and summarised by CityMETER
Where the data comes from

CityMETER derived / LLM-assisted contextual layer — This is a contextual synthesis across several signals, not one exact GD Catalog dataset.

Before making a decision

Use it to frame questions, prioritise places and plan field validation; do not treat behavioural descriptions as facts without evidence and a boundary crosswalk.

livingVerified2013 – Jul 2026

Population by Age & Sex

Use age-sex structure and density as baseline context for market reading and service planning

DemographicsAge & sexDensity
What you can do with this data
What this data helps you answer

Compare registered population by age, sex and area to plan services for children, working-age groups and older people.

Coverage
A Thailand summary view is visible; source coverage is not stated
Spatial unit
A province comparison map is visible; the smallest supported administrative geography is not verified
Source dataset verified
Where the data comes from

Bureau of Registration Administration, Department of Provincial Administration — Monthly age, sex and area dimensions align with DOPA statistics for people listed in house registration.

What period the data covers

The official download covers 2013–Jul 2026 and can reach village level; always show the reference month.

Before making a decision

Use for age-structure planning, but call it registered population—not daytime, resident or live population.

This badge confirms same-dataset lineage through an official owner channel. It does not mean every file was downloaded directly from the central GD Catalog.

livingCandidate source

Schools, Students & Teachers

Use school, student, teacher, and ratio metrics to explain education-service context

SchoolsStudents & teachersDistribution
What you can do with this data
What this data helps you answer

Compare schools, students, teachers and ratios to identify areas where education-service capacity needs closer review.

Coverage
A Thailand summary view is visible; source coverage is not stated
Spatial unit
The school is the evidenced record unit; point detail and the smallest map geography are not verified
Related source identified
Where the data comes from

Ministry of Education (candidate) — Owner, grain and schema align with the school dataset, but school-code/name/year records have not been reconciled.

Before making a decision

School, student, teacher and ratio measures describe service context—not quality, access or spare capacity.

livingVerified2017 – 2024

Municipal Revenue

Use revenue per person, per area, and revenue mix to compare local-finance context

Local financePer person & areaDistribution
What you can do with this data
What this data helps you answer

Compare local own-source revenue, state allocations, grants and total revenue to understand each local authority's funding structure.

Coverage
A Thailand summary view is visible; source coverage is not stated
Spatial unit
The local authority is the evidenced record unit; boundary geometry is not verified
Source dataset verified
Where the data comes from

Department of Local Administration — The backend owner confirmed DLA localincome; fields and local-authority grain align. No exact central GD Catalog package was found.

What period the data covers

Verified CityMETER lineage covers 2017–2024; a 2025 resource was added later to the catalogue.

Before making a decision

Compare own-source, allocated, grant and total revenue. Per-capita/area metrics are CityMETER calculations and are not service quality.

This badge confirms same-dataset lineage through an official owner channel. It does not mean every file was downloaded directly from the central GD Catalog.

livingExploratory

Government Agencies & Workforce

Use agency, workforce, density, and contact metrics to explain structural service context

Government agenciesWorkforceDensity
What you can do with this data
What this data helps you answer

Review the agencies, contact points and workforce categories shown by CityMETER to plan service access or follow-up coordination.

Coverage
A Thailand summary view is visible; source coverage is not stated
Spatial unit
Agency and workforce records are evidenced; point detail and the smallest geography are not verified
Exploratory data view
Where the data comes from

Composite layer — no single matching package verified — CityMETER combines agency and workforce categories, but no public manifest separates the owner and release of each component.

Before making a decision

Counts, contacts and workforce describe service structure—not availability, quality or eligibility.

livingCandidate source14-year history

Flood: Recurrent

See annual flood extent and recurrence in Phak Hai with a 14-year comparison chart

HistoricalRecurrenceWorst year
What you can do with this data
What this data helps you answer

See where flooding recurred, which years had greater impact and which subdistricts need closer site or preparedness review.

Coverage
Start with the Phak Hai example, then check source coverage before comparing other places.
Spatial unit
View district extent, flooded areas and subdistrict summaries, then check source resolution before using a smaller area.
Related source identified
Where the data comes from

GISTDA disaster layers (candidate) — CityMETER uses annual observed extents for 2011–2024, while the located recurrence/risk package covers 2011–2023 and produces a different output.

Before making a decision

Use for recurrent history—not current conditions, a forecast or a statutory risk determination.

livingCandidate source

Flood: Latest Observed

Make the observation date more prominent than the word ‘latest’ when showing detected flood areas

ObservationExposure contextTime period
What you can do with this data
What this data helps you answer

View the areas shown as flooded on the stated date and possible exposed locations to choose places for current-condition checks.

Coverage
A Thailand summary view is visible; source coverage is not stated
Spatial unit
The smallest supported geography is not yet verified from the public page
Related source identified
Where the data comes from

GISTDA flood boundary (candidate) — Geometry may come from GISTDA, but endpoint, resource, vintage and exposure-overlay transformation remain unverified.

Before making a decision

Read the observation date before the word ‘latest’; uncoloured areas are not automatically safe and a snapshot is not live conditions.

livingExploratoryForecast

Flood: Forecast Depth by DWR

Use flooded area, maximum and average depth, and run time to prioritise follow-up

ForecastWater depthExposure context
What you can do with this data
What this data helps you answer

Review forecast area and depth by model run to choose places for monitoring and current checks with responsible agencies.

Coverage
A Thailand summary and province ranking are visible; model coverage is not stated
Spatial unit
Province comparison is evidenced; model-surface resolution is not published
Exploratory data view
Where the data comes from

Department of Water Resources forecast layer; exact public package not yet verified — Forecast runs and depth output did not match the historical-risk packages reviewed in GD Catalog.

Before making a decision

Show run time, method, model and limits. A forecast is not an observation, guarantee or emergency instruction.

livingSpecialist source24-hour forecast

Flood: Flash Flood: 24-hour Risk by Google

See 24-hour risk levels across Thailand with province ranking and forecast run time

Forecast24-hour risk signalRanking
What you can do with this data
What this data helps you answer

See provinces with a 24-hour flash-flood signal and its run time to prioritise areas for official-alert monitoring.

Coverage
Compare the Thailand overview and province ranking, then check model coverage before use.
Spatial unit
Compare provinces, then check watershed or model-surface resolution before using a smaller area.
Uses a specialist data source
Where the data comes from

Google Flood Forecasting — CityMETER identifies the Google provider/model, so this is not GD Catalog lineage.

Before making a decision

Use as a 24-hour monitoring signal with experimental status and run time—not confirmation of an event or travel advice.

livingSpecialist source

Earthquake Sensor Network

Use station locations, MMI, acceleration, and update time to explain the sensing network

Sensor networkMMIAcceleration
What you can do with this data
What this data helps you answer

Read station locations, update times, shaking measures and related events to identify areas needing closer earthquake monitoring.

Coverage
Geographic coverage is not stated on the public page
Spatial unit
The sensor station is the smallest evidenced unit; map geometry is not verified
Uses a specialist data source
Where the data comes from

TMD event feed with RUGON / USGS — Located GD records are station inventories or annual aggregates at a different grain from CityMETER's event/sensor view, so lineage is not counted.

Before making a decision

Read station location, MMI, acceleration and update time together; freshness must always remain visible.

livingSpecialist source

Fire Monitoring

Use the time-window control as the visual and clearly mark the data object as awaiting confirmation

Fire monitoringTime windowsMonitoring
What you can do with this data
What this data helps you answer

View the distribution of signals used for fire monitoring to choose areas for checking reports and current conditions.

Coverage
Geographic coverage is not stated on the public page
Spatial unit
The smallest supported geography is not yet verified from the public page
Uses a specialist data source
Where the data comes from

NASA VIIRS / FIRMS — The field fingerprint points to NASA VIIRS/FIRMS rather than a GD Catalog dataset.

Before making a decision

CityMETER's unit still needs confirmation as hotspot, burned area or incident, so counts should not be turned into risk conclusions.

livingVerifiedAnnual 2014 – 2024

Disaster: Historical Impacts

Use hazard type, year, and impacts on people, households, businesses, and assets to tell the historical story

Multi-hazardHistoricalPeople & asset impacts
What you can do with this data
What this data helps you answer

Compare disaster types, frequency and reported impacts across places to prioritise preparedness and follow-up checks.

Coverage
A Thailand summary view is visible; source coverage is not stated
Spatial unit
The smallest supported geography is not yet verified from the public page
Source dataset verified
Where the data comes from

Department of Disaster Prevention and Mitigation — Event–area/village grain, 2014–2024 period and impact fields match the official village disaster-event statistics.

What period the data covers

Annual CSVs for 2014–2024; latest verified data year is 2024.

Before making a decision

Use for historical impact comparison and follow-up; one event may span several rows and the data is neither forecast nor current conditions.

This badge confirms same-dataset lineage through an official owner channel. It does not mean every file was downloaded directly from the central GD Catalog.

livingSpecialist sourceEvent 24–27 Nov 2025

Hat Yai Flood Reports — 24–27 Nov 2025

Pair the 24–27 November timeline with people and building context in the event area

Event archiveDated reportsExposure context
What you can do with this data
What this data helps you answer

Review the sequence and reported locations of the 24–27 Nov 2025 Hat Yai flood to discuss response lessons.

Coverage
Hat Yai flood event, 24–27 November 2025
Spatial unit
Dated reports are evidenced; the smallest event geography is not verified
Uses a specialist data source
Where the data comes from

Thai PBS / ThaiHelp case reports — Core case reports come from event-reporting sources rather than a GD Catalog dataset.

Before making a decision

Use as a 24–27 Nov 2025 event archive for sequence and context—not as a reusable flood layer or complete impact assessment.

livingExploratoryArchived

QuakeSafe: Building Inspection Status

Use inspection-status charts and comments to explain post-event follow-up

Event archiveBuilding inspectionStatus
What you can do with this data
What this data helps you answer

See the post-earthquake building-inspection workflow and statuses to understand follow-up steps and responsible contacts.

Coverage
Bangkok building-inspection archive
Spatial unit
The building-inspection record is evidenced; building-level map detail is not verified
Exploratory data view
Where the data comes from

BMA Building Inspection Dashboard — exact record lineage not yet verified — Attribution points to the BMA dashboard, but no repeatable package or record reconciliation was found.

Before making a decision

Use to understand post-event follow-up workflow—not as structural certification, a sensor network or a current inventory of every building.

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