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The Normalized Difference Built‑up Index (NDBI) is a remote‑sensing metric that highlights urban and built‑up surfaces by exploiting the spectral contrast between short‑wave infrared (SWIR) and near‑infrared (NIR) wavelengths.

Built‑up areas typically reflect more SWIR radiation while absorbing NIR, producing a positive NDBI value. Conversely, vegetated or water‑covered regions yield negative or near‑zero values, making the index valuable for urban expansion monitoring and land‑cover classification.

By calculating NDBI for each pixel, analysts can generate maps that differentiate built environments from natural landscapes, supporting city planning, disaster response, and environmental impact assessments.

\frac{\text{SWIR} – \text{NIR}}{\text{SWIR} + \text{NIR}}
NDBI = Normalized Difference Built‑up Index
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Frequently Asked Questions
What is the purpose of the NDBI in remote sensing?
The NDBI highlights urban and built-up surfaces by distinguishing between short-wave infrared (SWIR) and near-infrared (NIR) radiation.
How does NDBI differentiate between built-up areas and natural land cover?
Built-up areas reflect more SWIR radiation while absorbing NIR, resulting in a positive NDBI value. Vegetated or water-covered regions typically yield negative or near-zero values.
What are some applications of the NDBI index?
The NDBI is valuable for urban expansion monitoring and land-cover classification using remote sensing data.
Can NDBI be used to detect changes in urban areas over time?
Yes, by comparing NDBI values from different time periods, researchers can monitor changes in urban development and expansion.
What wavelengths are used in the NDBI calculation?
The NDBI uses short-wave infrared (SWIR) and near-infrared (NIR) wavelengths to calculate the index.

Results are for informational purposes only and do not constitute professional advice.