NDBI
The normalized difference built-up index from shortwave-infrared and near-infrared reflectance, which highlights roofs, roads, and other built surfaces.
Experimental: not yet fully verified. How results are checked
NDBI is 0.0877.
Provenance
- Computed by
- raster.index.ndbi 1.0.0, core 0.1.0
- Model
- NDBI = (SWIR1 - NIR) / (SWIR1 + NIR) on surface reflectance (Zha, Gao, and Ni 2003)
- Accuracy
- Exact arithmetic on the reflectance given.
- Notes
- 1 shown with the answer
- Cites
- Zha, Y., Gao, J., and Ni, S., International Journal of Remote Sensing, Use of normalized difference built-up index in automatically mapping urban areas from TM imagery
Something look off?
How we got thisFormula, worked example, sources, and proof
Model: NDBI = (SWIR1 - NIR) / (SWIR1 + NIR) on surface reflectance (Zha, Gao, and Ni 2003)
Accuracy: Exact arithmetic on the reflectance given.
When to use this: Use this to separate built surfaces from vegetation: roofs, pavement, and bare construction reflect shortwave-infrared more than near-infrared, so they come out positive while vegetation is negative. It is usually read beside NDVI rather than alone.
Limitations: Bare soil and dry ground behave much like built-up surfaces here, which is the index's main weakness, and the original work paired it with NDVI to tell them apart. It is not a measure of impervious fraction, and the result depends on the sensor's shortwave band.
Worked example: NDBI. Source: Zha and others 2003: SWIR1 0.31 and NIR 0.26 give 0.0877. It is golden test vector v004, and every build checks the tool still gives its answer within its tolerance.
You enter
- Near-infrared reflectance
- 0.26
- Shortwave-infrared reflectance
- 0.31
You get
- NDBI
- 0.0877
Review: Not yet independently reviewed by a GIS professional.
Last verified: 2026-09-22, when a maintainer last confirmed this tool's sources at the issuer. See the sources ledger.
Status: version 1.0.0, core 0.1.0. See this tool in the verification report.
Checked against: 10 golden test vectors (download the test vectors, each with its source and tolerance). See how results are checked and every source.
Sources
- Use of normalized difference built-up index in automatically mapping urban areas from TM imagery, Zha, Y., Gao, J., and Ni, S., International Journal of Remote Sensing, Volume 24, issue 3, pages 583-594. NDBI = (SWIR1 - NIR) / (SWIR1 + NIR).
Terms
- NDBI: normalized difference built-up index
- The difference between shortwave-infrared and near-infrared reflectance over their sum, which highlights roofs, pavement, and bare construction. Source: Use of normalized difference built-up index in automatically mapping urban areas from TM imagery
Experimental means this tool has not yet met the stable bar: at least 20 golden vectors, differential tests, and an independent worked example.