INDICES

Normalized Difference Vegetation Index:-

NDVI (Normalized Difference Vegetation Index) is a numerical indicator used in remote sensing and geographic information systems (GIS) to assess the health and density of vegetation cover in a given area. It is calculated from the reflectance of visible and near-infrared light captured by satellite or aerial imagery. 

Here's a brief description of NDVI:

Calculation: NDVI is calculated using the following formula:

                            NDVI = float(NIR-RED) / float(NIR+RED)

                                           where NIR represents near-infrared reflectance and Red represents red light reflectance.

Values: NDVI values typically range from -1 to 1. 

The interpretation of NDVI values is as follows:

• Values close to -1: These indicate non-vegetated surfaces, such as water bodies or barren land.
• Values around 0: These usually represent built-up areas or areas with no live vegetation.
• Values between 0 and 1: These indicate the presence of vegetation, with higher values signifying healthier and denser vegetation.

Applications: NDVI is a fundamental tool in various fields, including agriculture, forestry, ecology, and land management. It is used to monitor changes in land cover, detect vegetation stress, assess crop health, estimate biomass, and track environmental changes over time.

Enhanced Vegetation Index (EVI):-

 It was developed as an alternative vegetation index to address some of the limitations of the NDVI.

The EVI was specifically developed to:

    1.Be more sensitive to changes in areas having high biomass (a serious shortcoming of NDVI), 

    2.Reduce the influence of atmospheric conditions on vegetation index values, and 

    3.Correct for canopy background signals.

Formula:  EVI  =  2.5 * ((NIR-R) / (NIR + C1 * R - C2 * B + L))

    In Landsat 4-7, EVI  = 2.5 * ((Band 4 - Band 3) / (Band 4 + 6 *  Band 3 - 7.5 *  Band 1 + 1)).

    In Landsat 8, EVI = 2.5 * ((Band 5 - Band 4) / (Band 5 + 6 * Band 4 - 7.5 * Band 2 + 1)).

    Range: 1 to 1

where NIR, RED, and BLUE are atmospherically-corrected (or partially atmospherically-corrected) surface reflectances, and C1, C2, and L are coefficients to correct for atmospheric condition (i.e., aerosol resistance). For the standard MODIS EVI product, L-1, C1-6, and C2-7.5.

Limitations

One of the biggest current limitations to implementing EVI is that it needs a blue band in order to be calculated. Not only does this limit the sensors that EVI can be applied to (e.g., ASTER has no blue band), but the blue band typically has a low signal-to-noise ratio.Research is ongoing to develop a two-band EVI that can be calculated from just red and near infrared bands (see Jiang et al. 2008).

Soil Adjusted Vegetation Index:-

• Soil Adjusted Vegetation Index (SAVI) lis used to correct Normalized Difference Vegetation Index (NDVI) for the influence of soil brightness in areas where vegetative cover is low.
• SAVI is used to correct Normalized Difference Vegetation Index (NDVI) for the influence of soil brightness in areas where vegetative cover is low.
• The Soil-Adjusted Vegetation Index (SAVI) is a vegetation index that attempts to minimize soil brightness influences using a soil-brightness correction factor. This is often used in arid regions where vegetative cover is low.
• Landsat Surface Reflectance-derived SAVI is calculated as a ratio between the R and NIR values with a soil brightness correction factor (L) defined as 0.5 to accommodate most land cover types.

                        L = amount of green vegetation cover

                The L value varies depending on the amount of green vegetative cover.

Generally,

In areas with no green vegetation cover, L=1;

In areas of moderate green vegetative cover, L=0.5; and

In areas with very high vegetation cover, L=0 (which is equivalent to the NDVI method).

        This index outputs values between -1.0 and 1.0

Formula for Soil Adjusted Vegetation Index (SAVI):-

                                ((NIR-R)/(NIR+R+L)) * (1 + L), 

                                                        where L = amount of green vegetation cover

In Landsat 4-7, SAVI = ((Band 4-Band 3)/(Band 4+ Band 3+0.5)) * (1.5).

In Landsat 8-9, SAVI = ((Band 5-Band 4)/(Band 5+ Band 4+0.5)) * (1.5).

Normalized Difference Built-up Index (NDBI)

What is NDBI index?

The Normalized Difference Built-up Index (NDBI) uses the NIR and SWIR bands to emphasize manufactured built-up areas. It is ratio based to mitigate the effects of terrain illumination differences as well as atmospheric effects.

The Normalize Difference Build-up Index value lies between -1 to +1. Negative value of NDBI represent water bodies where as higher value represent build-up areas. NDBI value for vegetation is low.

        Formula for NDBI,

                        NDBI = (SWIR – NIR)/(SWIR+NIR)

In Landsat 9,

NDBI = (Band 6 - Band 5) / (Band 6 + Band 5).

In Landsat 8,

NDBI = (Band 6 - Band 5) / (Band 6 + Band 5).

In Landsat 7,

NDBI = (Band 5-Band 4) / (Band 5+ Band 4).

Topographic Position Index (TPI)

The Topographic Position Index (TPI) is a GIS (Geographic Information System) tool used in terrain analysis to characterize the topographic position of a location within a landscape. It measures the relative elevation of a point compared to its surroundings and provides insights into the local terrain morphology. TPI is widely used in environmental modeling, landscape ecology, and terrain classification.

The Topographic Position Index quantifies the topographic position of a point by comparing its elevation to the average elevation of its surrounding landscape. It helps identify whether a location is situated in a valley, on a ridge, or in a flat area.

Interpretation:

• Positive TPI values indicate that the point is higher than its surroundings, suggesting a ridge or elevated position.
• Negative TPI values suggest lower elevation relative to the surroundings, indicating a valley or depression.
• TPI values around zero suggest relatively flat terrain.

Applications:

• Landform Classification: Use TPI to classify landforms, such as identifying ridges, valleys, and plains within a landscape.
• Hydrological Analysis: Understand how the topography influences surface water flow and drainage patterns.
• Ecological Studies: Assess how the topographic position influences vegetation distribution, habitat suitability, or wildlife movement.