NDBI: Mapping the Built Environment From Space
Concrete and asphalt do something vegetation does not — they reflect more shortwave-infrared than near-infrared. NDBI turns that reversal into a first-order map of where the built environment is.
What it actually measures
Built-up and impervious surfaces push NDBI positive; vegetation and water go negative. It is the mirror image of NDVI's band logic, which is why the two are so often differenced together to isolate urban land from everything else.
The formula
where SWIR1 is shortwave-infrared 1 reflectance (~1.6 µm), NIR is near-infrared reflectance.
Reading the values
> 0 built-up / impervious · < 0 vegetation and water. Bare soil sits close to built-up values.
Which bands to use
| Sentinel-2 | SWIR1 B11 · NIR B8 |
| Landsat 8/9 | SWIR1 B6 · NIR B5 |
In practice
Use it for rapid urban-extent mapping, impervious-surface estimation, and monitoring city expansion across dates.
Where it struggles
NDBI's blind spot is bare soil, which behaves almost identically in SWIR/NIR and gets over-mapped as built-up. In any scene with fallow fields or drylands, combine it with NDVI and a water mask — or use IBI, which does exactly that.
Compute NDBI on your own study area
Skip the code. Draw or upload a boundary and Spatial Research Suite runs NDBI on live Sentinel-2 or Landsat imagery — with cloud masking, exports and citations built in.
Run this analysis in GISforus →Frequently asked
Why does NDBI confuse bare soil with buildings?
Dry bare soil has a SWIR/NIR response close to impervious surfaces, so both score positive; combining NDBI with NDVI/MNDWI (as IBI does) resolves it.
What NDBI value means built-up?
Positive values typically indicate built-up or impervious surfaces, but validate the threshold locally.