Main Indexs For Remote Sensing
Geospatial
indexs
| Code | name | formula | details |
|---|---|---|---|
| NDVI | The Normalized Difference Vegetation Index | NDVI = (NIR - Red) / (NIR + Red) | It measures the greenness of the vegetation a remote sensing tool used to assess vegetation health and density by analyzing the reflectance of light in the near-infrared and red wavelengths. Values close to 1: indicate healthy, dense vegetation. Values close to 0: indicate bare soil, rocks, or sparse vegetation. Negative values: typically indicate water or clouds. |
| NDRE | Normalized Difference Red Edge Index | NDRE = (NIR - RedEdge) / (NIR + RedEdge) | a vegetation index used in remote sensing to assess plant health and chlorophyll content. Sensitive to changes in plant chlorophyll content |
| NIRv | near-infrared reflectance of vegetation | NIRv=(NDVI−NDVImin)×NIR NIRv=NDVI×NIR | is a remote sensing index that enhances the measurement of vegetation productivity and greenness by isolating the vegetation signal from the background. It builds upon the Normalized Difference Vegetation Index (NDVI) but tries to correct for the mixed pixel problem (i.e., where pixels contain both vegetation and non-vegetation elements like soil or shadow). |
| NDMI | Normalized Difference Moisture Index | NDMI=(NIR+SWIR) / (NIR−SWIR) | measures the difference in reflectance between the Near-Infrared (NIR) and Short-Wave Infrared (SWIR) bands. Healthy, water-rich vegetation reflects more NIR and less SWIR, while stressed or dry vegetation reflects less NIR and more SWIR. High NDMI (close to +1): High vegetation moisture, healthy vegetation. Low NDMI (close to -1): Low moisture, vegetation stress, possible drought. NDMI ≈ 0: Sparse or dry vegetation, or non-vegetated surfaces like soil or built-up areas. |
| NBR | Normalized Burn Ratio | NBR=(NIR+SWIR) / (NIR−SWIR) | Detects burn areas and post-fire damage is a remote sensing index specifically designed to identify burned areas, assess fire severity, and monitor vegetation recovery after wildfires. Healthy vegetation strongly reflects near-infrared (NIR) and weakly reflects short-wave infrared (SWIR). Burned areas show reduced NIR reflectance and increased SWIR reflectance due to the charring and loss of biomass and moisture. |
| MSI | The moisture stress index | MSI=(Band 11 or SWIR 1 / Band 8 or NIR) | MSI is used to evaluate changes in the water content in vegetation via canopy stress analysis. It is also used to indicate water concentration in soil. Indicates Vegetation Moisture Stress |
| NDWI | Normalized Difference Water Index | NDWI=(Green+NIR) / (Green−NIR) NDWIGao=(NIR+SWIR) / (NIR−SWIR) MNDWI = (Green - SWIR) / (Green + SWIR) | Identifies water bodies using green and NIR reflectance to detect open water bodies and surface water extent. Detect water bodies (McFeeters) or vegetation moisture (Gao). Contrast between vegetation/water and background NDWI (McFeeters, 1996) — for water body detection. bands B3 (Green) and B8 (NIR) NDWI (Gao, 1996) — also called NDMI, for vegetation water content. “The Modified Normalized Difference Water Index (MNDWI) uses green and SWIR bands for the enhancement of open water features. It also diminishes built-up area features that are often correlated with open water in other indices. Positive NDWI (>0): Water Negative NDWI (<0): Soil, vegetation, or built-up areas -1 to +1 (positive values usually indicate water or moisture) |
| NDTI | Normalized Difference Tillage Index | NDTI=(Red+SWIR1) / (Red−SWIR1) | used primarily to distinguish between tilled and untilled agricultural soil surfaces. It helps monitor soil disturbance, especially in agricultural areas, where identifying recent plowing or tillage is important for land management, erosion studies, and precision agriculture. Red: Reflectance in the red band (~660 nm) SWIR1: Reflectance in the shortwave infrared band 1 (~1650 nm) Differentiate bare tilled soil (which tends to reflect more in the red band) from undisturbed or vegetated soil (which tends to reflect more in the SWIR1 band). Support analysis of soil management practices. Assist in erosion risk assessment and soil conservation mapping. Higher NDTI values (positive): Likely indicate tilled or disturbed soil. Lower NDTI values (negative): Suggest untilled or covered soil, or areas with vegetation or moisture. |
| NDTI (for water) | (RED - GREEN) / (RED + GREEN) | Detects Turbidity Or Sediment In Water | |
| WRI | Water Ratio Index | WRI=(NIR+SWIR) / (Green+Red) or (Green+Red) / (NIR + SWIR) | is a simple and effective remote sensing index used to detect open surface water bodies in satellite imagery. It helps distinguish water from non-water features such as soil, vegetation, and built-up areas based on their reflectance characteristics. Total surface reflectance behavior (combined bands) WRI leverages the fact that water absorbs more in the near-infrared (NIR) and short-wave infrared (SWIR) bands, and reflects more in the green and red parts of the spectrum. In contrast, soil and vegetation behave differently, allowing for separation. WRI > 1 → Likely water bodies WRI < 1 → Likely non-water surfaces (vegetation, soil, urban) Typically >1 for water, <1 for non-water Note: Thresholds may vary slightly depending on atmospheric conditions and sensor characteristics, so it’s often calibrated for specific regions or imagery. Fast water detection (e.g., floods, rivers) |
| AWEI | Automated Water Extraction Index | 0.304 × (Green) + 0.474 × (SWIR1) + 0.050 (Blue) - 0.250 × (NIR) | Detects water bodies with multiple spectral bands. |
| NDSI | Normalized Difference Snow Index | (Green - SWIR)/ (Green + SWIR) | Detects snow by green and SWIR reflectance. Detects snow cover by differentiating snow from clouds and water. Ideal for snowpack monitoring and climate studies. |
| NDGI | the normalized difference glacier index | (Green - Red)/ (Green + Red) | is used to identify glacier coverage in a region mainly composed of snow, ice, and debris |
| LSWI | (NIR-SWIR)/(NIR + SWIR) | Sensitive to water content in vegetation and soil. Estimates soil properties like moisture and texture | |
| EVI | Enhanced Vegetation Index | G (NIR - Red)/ (NIR + C1 × Red - C2 × Blue + L) 2.5 * ((NIR - Red) / (NIR + 6 * Red - 7.5 * Blue + 1)) | Enhances sensitivity in dense vegetation areas. Corrects for atmospheric interference and soil noise in high biomass regions. |
| GNDVI | (NIR - Green) / (NIR + Green) | Assesses vegetation health using the green band | |
| DVI | NIR - Red | Calculates the difference between NIR and red bands | |
| SAVI | Soil Adjusted Vegetation Index | SAVI=(1+L)⋅(NIR−Red) / (NIR+Red+L) | Reduces soil effects in sparse vegetation areas is a remote sensing index designed to minimize the influence of soil brightness when measuring vegetation greenness, especially in areas where vegetation cover is sparse. NDVI can be inaccurate in regions with low vegetation because the soil reflectance affects both the red and NIR signals. SAVI corrects this by introducing a soil adjustment factor to reduce soil background effects. NIR = Reflectance in the Near-Infrared band (e.g., ~850 nm) Red = Reflectance in the Red band (e.g., ~660 nm) L = Soil adjustment factor (ranges from 0 to 1) L = 0 → SAVI becomes NDVI (used when vegetation is dense) L = 0.5 → Commonly used default (for intermediate vegetation) L = 1 → Used in very sparse vegetation Higher values indicate more green vegetation. Lower or negative values suggest bare soil, dry vegetation, or non-vegetated surfaces. |
| NDBI | Normalized Difference Built-Up Index | (SWIR-NIR)/(SWIR + NIR) | Differentiates urban areas from natural landscapes. Identifies built-up urban areas by contrasting man-made structures against natural surroundings |
| UI | (Red - SWIR)/ (Red + SWIR) | Measures urban development using red and SWIR | |
| VHI | VHI = a × NDVI + b × TCI | Vegetation & temperature data for health assessment | |
| CMRI | Combined Mangrove Recognition Index | w1 ⋅VCI+ w2⋅SDI+ w3⋅BI+ w4⋅WQI | VCI (Vegetation Cover Index): A measure of the extent of mangrove forest cover in a given area (usually derived from satellite data or remote sensing). SDI (Species Diversity Index): This index represents the diversity of species present in the mangrove area. It is calculated based on the richness and evenness of species. BI (Biomass Index): This index indicates the total biomass or the carbon storage capacity of the mangrove forest. WQI (Water Quality Index): This index reflects the health of the surrounding water, which can be influenced by salinity, turbidity, and pollution levels that affect the mangrove ecosystem. |
| SDI | BLUE/RED | Indicates Soil Or Surface Dryness | |
| VARI | (Green - Red)/ (Green + Red - Blue) | Reduces atmospheric effects on vegetation | |
| DPSI | (NIR - Blue) / (NIR + Blue) | Detects snow or ice coverage | |
| TVI | 0.5 × (1+ (NIR - Red) / (NIR + Red)) | Alleviates saturation effects in dense vegetation | |
| RVI | NIR / Red | Simple vegetation index for preliminary analyses | |
| CVI | CVI = (NIR/Green) - 1 | Estimates chlorophyll content in vegetation | |
| 5/4 Ratio | 5/4 Ratio = (NIR/Red) square root (NIR/R) | enhances the presence of vegetation. The brighter the tones, the denser the vegetation. Vegetation – NIR/R »> 1 Water – NIR/R < 1 Soil – NIR/R > 1 NIR/R–images can serve as a crude classifier of images, and indicate vegetated areas in particular. Adding the square root function makes the image slightly brighter and provides a sharper distinction between features compared to the NIR/RED ratio | |
| ARVI | Atmospherically Resistant Vegetation Index | (NIR - (2 * Red) + Blue) / (NIR + (2 * Red) + Blue) | Reduces atmospheric scattering to provide better vegetation monitoring |
| GCI | Green chlorophyll vegetation index | (Band 9 or Water vapor / Band 3 or Green) - 1 | the green chlorophyll vegetation index (GCI) is applied to remote sensing data to estimate chlorophyll concentration in vegetation and, consequently, determine the health of the vegetation |
| BSI | The bare soil index (BSI) | ((SWIR 1 + Red) - (NIR + Blue)) / ((SWIR 1 + Red) + (NIR + Blue)) | is used to retrieve information from vegetation in cases where its coverage is less than half of the assessed area. This index allows us to determine the vegetation health of the exposed soil area |
| IPI | The structure-insensitive pigment index | (NIR - Blue) / (NIR - RED) | was initially proposed to identify vegetation stress through the ratio between carotenoid and chlorophyll in vegetation. It is also useful for analyzing vegetation structures with different canopy configuration |
| SWM | The sentinel water mask (SWM) | (Blue + Green) / (NIR + SWIR 1) | is specifically used to analyze water data from the Sentinel-2 constellation |
| TI | Turbidity levels | Red / Green | A measure of water clarity. High TI = Sediments or disturbed water |
| FDI | Floating Debris Index | NIR - (Red + Blue) | floating debris detection |
| FAI | Floating Algae Index | NIR − (Red + (SWIR − Red) × (λNIR − λRed) / (λSWIR − λRed)) or (RED - SWIR)/ (RED + SWIR) | Useful to detect floating organic matter. Detects Floating Algae Or Aquatic Vegetation |
| SWCI | (Blue-NIR)/ (Blue + NIR) | Indicates Surface Water And Moisture Presence | |
| NDPI | (GREEN - SWIR) / (GREEN + SWIR) | Highlights Surface Water And Wet Areas. | |
| WI | GREEN-NIR | Simple Index For Identifying Water Features | |
| SRWI | GREEN/SWIR | Emphasizes Surface Water Reflectance | |
| DFII | (NIR-SWIR)/(NIR + SWIR) | Identifies Drought And Dryness Intensity | |
| SMI | (RED - SWIR)/ (RED + SWIR) | Assesses Soil Moisture Condition | |
| CTI | (RED - NIR) / (RED + NIR) | Separates Vegetation From Bare Surfaces | |
| UWI | (GREEN - SWIR) / (NIR + SWIR) | Detects Urban Water Features | |
| EWI | (GREEN - NIR-SWIR) / (GREEN + NIR + SWIR) | Enhances Open Water Extraction | |
| NWI | (BLUE-NIR) / (BLUE + NIR) | Normalized Indicator Of Water Bodies | |
| RSWI | (RED-SWIR)/ (RED + SWIR) | Identifies Surface And Soil Water Stress | |
| FSWI | (GREEN - NIR) / (GREEN + NIR) | Highlights Flood And Surface Water Extent |