Jack Tivey — Geospatial analysis & spatial data production

Open to work

Portfolio

Jack Tivey Geospatial Portfolio

Spatial data production. BSc (Hons) Physical Geography, University of the West of England Bristol.

Discipline
Geospatial analysis
Tools
QGIS, ArcGIS Pro, Claude Code
Degree
BSc (Hons) Physical Geography
Institution
UWE Bristol

01 — Spatial data production

Commercial

Vestige Golf App — a national dataset of English golf course polygons

Base
Open mapping extract
Corrected in
QGIS, geojson.io
Features
1,773
Coverage
47 counties

There was no usable spatial dataset of English golf courses, so I built one. Coverage starts as a bulk extract from open mapping data, which gets you most of the country and almost none of the accuracy — boundaries drawn to no consistent rule, inconsistent tagging, courses missing, and entries that closed or relocated years ago. The dataset is the correction pass, not the extract.

County by county, every polygon is checked against satellite imagery and redrawn in QGIS and geojson.io where it is wrong, to a single rule — operational extent: playable ground plus clubhouse, car park and driving range where present. Not the legal freehold, which is not visible from imagery and would have meant guessing. Each county is then reconciled against independent listings to catch closures, relocations and duplicates. The result is 1,773 courses across 47 English counties. I built the React admin tool that runs the review.

Whilst Vestige is my brainchild, it is a shared project. Tom writes the code for the iOS app and I expand and maintain its dataset. In-app features and decisions are always split, and through this we have created something we are very proud of.

Visit vestige.golf →

Vestige is a commercial project operated through Pinehollow Studios Limited, co-founded with Tom Slater.

The Vestige admin review tool: a dark basemap of Tyne and Wear and County Durham covered with digitised golf course polygons colour-coded by review state, beside a panel showing the record for Linden Hall Golf and Country Club with its imported tags and keep, delete and merge actions.
Admin review workflow The React tool built to QA the dataset county by county. Each imported feature is reviewed against its source tags and resolved as keep, delete or merge, with progress tracked against the county total. Polygons are coloured by review state.

The same dataset at three scales, in the shipped app

The Vestige iOS home screen: a dark map of England divided into its 47 county boundaries, above a progress card reading 13 of 1,773 courses.
National All 47 English counties, the full extent of the dataset.
The Vestige county view for Surrey, showing every golf course boundary in the county as a separate polygon scattered across the county outline, with a panel reading 7 of 68 courses played.
County Surrey, 68 courses. The density every boundary has to be right at.
A single course in the Vestige app: the digitised boundary of Hankley Common Golf Club drawn as a bright outline over satellite imagery, following the played holes and excluding the surrounding heath.
Course Hankley Common at working zoom — one boundary drawn to operational extent.

02 — Land suitability modelling

Dissertation

National land suitability modelling for oilseed rape

Tool
ArcGIS Pro
Method
MCDA, AHP-weighted
Criteria
7 weighted, 1 constraint
Extent
UK-wide

Undergraduate dissertation, titled Assessing the UK's Agricultural Capability for Producing Sustainable Aviation Fuels (SAFs) from Oilseed Rape. Seven criteria drawn from the agronomic literature — precipitation, mean air temperature, soil pH, growing degree days, sunshine hours, drought severity and distance to processing — were reclassified onto a common 1 to 10 suitability scale, weighted by pairwise comparison using the Analytic Hierarchy Process, and combined into a single national surface. Precipitation carried the heaviest weight at 30.5%, temperature 25.3% and soil pH 19.7%. Slope was handled separately as a binary constraint, excluding anything above 15%. The result was then clipped to existing agricultural land, which cut the theoretically suitable area to roughly 6 million hectares — around half what full domestic demand would require.

The method generalises. Narrowing a whole country to the land meeting a defined set of conditions is the same problem whatever the conditions are.

Suitability map of the United Kingdom for oilseed rape from the combined AHP-weighted model, before constraints. Most of England and eastern Scotland scores highly, with low suitability in the Scottish Highlands and upland Wales.
Combined MCDM surface, unconstrained Seven weighted criteria summed to a single national suitability score.
The same UK suitability surface clipped to slopes under 15% and to existing agricultural land, leaving a much reduced and fragmented suitable area concentrated in eastern England.
Clipped to slope and agricultural land The same surface constrained to slopes under 15% and existing farmland — roughly 6 million hectares.
UK map showing mean annual precipitation reclassified to a 1 to 10 suitability scale for oilseed rape, with the driest eastern counties scoring highest.
One input criterion Mean annual precipitation, reclassified to the shared 1–10 suitability scale. Six further criteria were prepared the same way.
AHP criterion weights
Mean precipitation30.5%
Mean air temperature25.3%
Soil pH19.7%
Growing degree days10.7%
Sunshine hours7.6%
Drought severity index3.8%
Distance to production2.5%

Weights derived from pairwise comparison of all seven criteria. Consistency ratio 0.093, below Saaty's 0.10 threshold. Bars are scaled to the heaviest weight.

03 — Remote sensing

Three studies

Remote sensing and change detection

Studies
3
Methods
Change detection, NDVI, burn scar
Regions
Spain, Brazil, South Africa
Span
1984–2023

Monitoring studies built during my degree, each taking an environmental change and finding a way to measure it from satellite data: landcover change detection tracking four decades of greenhouse expansion in Almería, an NDVI Z-score time series measuring vegetation anomaly around Porto Velho in the Amazon, and burn-scar mapping across the uKhahlamba World Heritage site to assess whether managed firebreaks were holding.

Baseline monitoring in method if not in subject — establish the normal condition, then measure movement away from it.

Five maps of the Almería coast for 1984, 1990, 1995, 2000 and 2023, showing greenhouse cover expanding from scattered patches to a near-continuous band along the coastal plain.
Almería, 1984–2023 Landcover change detection across four decades of greenhouse expansion. Cyan marks new cover in each period, grey the cover already present. All five panels share a scale and orientation.
Six NDVI Z-score panels around Porto Velho for 2018 to 2023, shifting from predominantly green to predominantly yellow, with red fishbone patterns spreading along access roads.
Porto Velho, 2018–2023 NDVI Z-score time series measuring vegetation anomaly against the period baseline. Green is healthier, more established vegetation; red is low vegetation cover. All six panels share a scale and a north-up orientation.
Paired burn-scar maps of the uKhahlamba World Heritage site for the 2021 pre-fire and post-fire seasons. The pre-fire map shows thin burn lines along the park boundary; the post-fire map shows extensive burning inside the park and scattered burning outside it.
uKhahlamba, 2021 Burn-scar mapping either side of the fire season, testing whether managed firebreaks along the park boundary were holding. Both panels share a scale and orientation.

04 — Hazard mapping

Sunda Strait

Tsunami vulnerability and hazard response

Method
MCDA vulnerability
Criteria
5
Scenarios
2 wave heights
Priority area
Bandar Lampung

A hazard management plan for the Krakatoa region, combining elevation, population density, age structure, purchasing power and distance to hospitals into a multi-criteria vulnerability surface, then modelling inundation for two eruption scenarios against it. The analysis identified Bandar Lampung, 75km north-east and home to 1.16 million people, as the priority area, and the plan set out costed intervention options against it. The audience for a hazard plan is people making decisions under time pressure, so the work had to reduce to maps that could be read quickly and correctly.

Turning spatial analysis into something a non-specialist can act on is most of the job.

Multi-criteria vulnerability surface across the Sunda Strait. Red, the most vulnerable class, covers the coast around Bandar Lampung and the western tip of Java near Krakatoa; green, the least vulnerable, covers the eastern coast towards Cirebon.
Vulnerability surface Elevation, population density, age structure, purchasing power and distance to hospitals combined into a single score. Krakatoa marked at centre.
Inundation map of Bandar Lampung bay showing modelled flood extent for two tsunami wave heights, 13 metres in blue and 41 metres in pink, reaching well inland around the head of the bay.
Modelled inundation, two scenarios Wave heights of 13m and 41m, taken from the 2018 Sunda Strait event and the 1883 eruption respectively.
Map of Bandar Lampung showing current locations of hospitals, schools and shelters, with several schools and hospitals sited close to the coastline and shelters further inland.
Key infrastructure and land use planning Current siting of hospitals, schools and shelters against the modelled extent — the basis for the plan's relocation and setback proposals.