GISRS and PhotogrammetryUAV

Environmental indices

You have probably encountered the concept of remote sensing indices many times during your studies, in professional work, or in scientific and popular science articles. We decided to take a closer look at this topic, and starting today, we are launching a series of short articles where we will present not only the theoretical basics but also the practical applications of these indices as measures of environmental conditions.

To begin, a bit of theory as an introduction…

Remote sensing indices are special mathematical indicators created on the basis of data collected from satellites, drones, or aircraft. They combine information from different bands of the electromagnetic spectrum to make it easier to analyze phenomena occurring on the Earth’s surface. With their help, an ordinary image can be transformed into a map showing specific symbols in the form of raster data with environmental significance.

These indices are most often used to study vegetation, water, soil, snow, or urban areas. A well-known example is NDVI, which makes it possible to assess plant condition and distinguish between healthy and stressed vegetation. However, there are also many other indices that focus on soil moisture, water presence, fire damage, or the degree of urbanization.

Remote sensing indices are widely used in agriculture, forestry, environmental protection, spatial planning, and disaster response. They are applied both by scientists and practitioners who need quick and reliable information about the state of the environment.

Below we present a list of indices, divided according to land cover type.

Vegetation Indices

  • NDVI (Normalized Difference Vegetation Index) – the classic vegetation index.
  • EVI (Enhanced Vegetation Index) – performs better with dense vegetation.
  • SAVI (Soil Adjusted Vegetation Index) – accounts for soil influence.
  • MSAVI (Modified SAVI) – improved version of SAVI, better for areas with low vegetation.
  • GNDVI (Green NDVI) – uses the green band, sensitive to chlorophyll content.
  • NDRE (Normalized Difference Red Edge) – uses the red edge band, sensitive to plant stress.
  • VARI (Visible Atmospherically Resistant Index) – based on visible light, resistant to atmospheric effects.

Water Indices

  • NDWI (Normalized Difference Water Index, McFeeters) – water surface detection.
  • MNDWI (Modified NDWI, Xu) – improved NDWI, more effective in urban areas.
  • NDMI (Normalized Difference Moisture Index) – vegetation and soil moisture.
  • LSWI (Land Surface Water Index) – sensitive to water content in plants and soil.

Soil and Surface Indices

  • NDSI (Normalized Difference Snow Index) – snow cover detection.
  • NBR (Normalized Burn Ratio) – fire-affected area monitoring.
  • NBR2 (Normalized Burn Ratio v2.)  – analysis of soil moisture after fires.
  • BAI (Burned Area Index) – assessment of burned surfaces.
  • BSI (Bare Soil Index) – detection of bare soil.

Urban and Mixed Indices

  • UI (Urban Index) – urban area identification.
  • NDBI (Normalized Difference Built-up Index) – built-up area index.
  • IBI (Index-Based Built-up Index) – alternative urban index.

Follow our page – in the upcoming posts, we will describe each individual index in more detail.

“Icon made by Pixel perfect from www.flaticon.com“