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Geospatial Computational Research

We measure what the ground is actually doing.

RegenX.eco builds terrain and satellite models for coastlines, cities, farmland and the glaciers above them. We build on the public Earth-observation record, we show the arithmetic behind every number, and we publish the tests our own models fail.

Islamabad · Gulf & South Asia Sentinel-1 & 2 · Copernicus GLO-30 · ERA5 Reproducible, auditable method
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site models built, from a 1.6 ha orchard to a 1,965 ha command area

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countries — United Arab Emirates, Pakistan, Nepal, China (TAR)

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Sentinel-2 acquisitions analysed across the portfolio

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of reanalysis climate record behind each site baseline

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scale span across which the same engine has been run

What we do

One engine, three questions.

Most geospatial work answers what is there. The decisions our clients face need two more answers: what is changing, and how much of that change is real. The same model produces all three.

LAYER 01 — TERRAIN

Where water goes, and how fast

Hydrological routing on 30 m Copernicus elevation: catchment delineation, channel confinement, impoundment volume, arrival time to the first settlement. Flow routing, not proximity — the difference changes conclusions.

LAYER 02 — OBSERVATION

What the surface has been doing

Multi-year Sentinel-2 and Sentinel-1 time series, cloud-masked per pixel and radiometrically corrected, for vegetation, water, snow, built form and surface moisture — alongside ERA5 and NASA POWER climate records.

LAYER 03 — VALIDATION

Whether any of it survives testing

Robust trend statistics, back-tests against documented events, and leave-one-out hindcasts. A finding that fails is reported as a failure, with the test that killed it.

Layer 03

Validation you can check.

A satellite index will always produce a number. Whether that number means anything is a separate question, and it is the one we spend most of our time on.

Every RegenX engagement ends with the tests we ran against our own conclusions. Where a finding survives, the client gets the statistic that proves it. Where it does not, the finding is withdrawn in writing — before anyone builds a decision on it.

Worked example — hazard modelling

The model that lost, and the one that replaced it

A recurrent neural network trained on weather forcing scored an in-sample ROC-AUC of 0.674 at one glacier. Under honest leave-one-year-out retraining it fell to 0.120 out of sample, below the best single-feature baseline at 0.584, and warned 0 of 15 documented events.

We published that result and rebuilt the system around a physically grounded lake-area precursor instead. It now warns 7 of 11.

Worked example — a claim we withdrew

Four findings that did not survive

At Al Marjan Island, ordinary least-squares trends produced four publishable headlines. Robustness testing killed all four: one was a water-dominated artefact, one rested on a single leveraged year, one collapsed once serial correlation was accounted for, and one was pure seasonal sampling.

The finding that replaced them is stronger than any of the four, because it survived the same tests.

Where the model is used

Six decisions we are built for.

01

Coastal & resort development

Land growth, shoreline stability, canopy performance against a comparable benchmark, and the heat and rainfall record the asset will actually operate in.

02

Urban planning baselines

A single district frame carrying terrain, drainage and inundation history, land cover, built form, population and canopy — the substrate a digital twin needs before it can be trusted.

03

Blue carbon & restoration

Mangrove and wetland extent, condition and trend; screening-grade carbon estimates with their uncertainty stated; restoration-ready area identified and sized.

04

Glacial & flood hazard

Lake-fill precursors, ice-dam state, velocity surges, routed arrival times and downstream exposure — with the observation gaps stated as plainly as the alerts.

05

Agricultural verification

Per-parcel determinations at portfolio scale for lenders, insurers and programme managers — what is planted, what is irrigated, what is performing, delivered as a ranked exception list.

06

Site & land assessment

Pre-investment screening for farmland, mineral concessions and building platforms: climate envelope, water balance, slope stability, chill hours, frost risk and species fit.

Start here

Tell us about the site.

Send a boundary — a KML, a shapefile, or four corner coordinates — and the question you need answered. The first response tells you what the open record can and cannot resolve for that location, before any engagement.