TPI: Is This Pixel on a Ridge, a Slope, or in a Valley?
The Topographic Position Index answers a deceptively useful question at every point on the map: are you higher or lower than your surroundings? That single comparison is enough to classify a whole landscape into landforms.
The physical basis
TPI subtracts a cell's elevation from the mean elevation of a surrounding neighbourhood. Positive values sit above their surroundings (ridges, peaks); negative values sit below (valleys, pits); near-zero means flat or mid-slope. Changing the neighbourhood radius changes which scale of landform you see.
How it is calculated
What the numbers mean
≈ 0 flat or mid-slope · strongly positive = ridge / peak · strongly negative = valley / pit.
The data it needs
| Derived from | Digital Elevation Model (SRTM / Copernicus, 30 m) — not an optical band index. |
Where it is used
It is used for automated landform classification, habitat and soil mapping, and stratifying terrain for ecological or archaeological survey.
Limitations to know
TPI is entirely scale-dependent — a small window finds gullies, a large one finds mountain ranges. Report the radius you used, and consider combining two scales to capture nested landforms.
Compute TPI on your own study area
Skip the code. Draw or upload a boundary and Spatial Research Suite runs TPI on live data — with cloud masking, exports and citations built in.
Run this analysis in GISforus →Frequently asked
What does a positive TPI mean?
The cell is higher than its surroundings — a ridge, crest or peak; negative TPI marks valleys and depressions, and near-zero flat or mid-slope ground.
Why does the neighbourhood size matter for TPI?
TPI describes position relative to its window: a small radius detects fine features like gullies, a large radius detects broad landforms.