Colour Index: The Colour Index algorithm was developed to differentiate soils in the field. Low valued CIs have been shown to be correlated with the presence of a high concentration of carbonates or sulfates and higher values to be correlated with crusted soils and sands in arid regions (Escadfal 1989). In most cases the CI gives complementary information with the BI and the NDVI. Used for diachronic analyses they help for a better understanding of the evolution of soil surfaces. The CI results from the following equation: CI = (red_factor * red - green_factor * green) / (red_factor * red + green_factor * green)

Brightness Index: This index is representing the average of the brightness of a satellite image. The Brightness Index algorithm is representing the average of the brightness of a satellite image. The result looks like a panchromatic image with the same resolution of the original image.This index is therefore sensitive to the brightness of soils which is highly correlated with the humidity and the presence of salts in surface (Escadafal 1989). The BI results from the following equation: BI = sqrt( ( (red_factor * red * red_factor * red) + (green_factor * green * green_factor * green) ) / 2 )

Chlorophyll content in the leaf: corresponds to the content of chlorophyll a chlorophyll b and carotenoids per unit of leaf area.

Canopy water content (CWC) the amount of water stored in the vegetation canopy is typically determined by multiplying the leaf water content by the canopy leaf area index (LAI). This calculation incorporates information about the leaf water condition and the canopy structure [1]. CWC is a critical parameter for assessing vegetation growth and monitoring drought stress. It is influenced by soil water supply and atmospheric demand.

The Transformed Soil Adjusted Vegetation Index (TSAVI) method is a vegetation index that minimizes soil brightness influences by assuming the soil line has an arbitrary slope and intercept. TSAVI = (s *(NIR - s * Red - a)) / (a * NIR + Red - a * s + X * (1 + s2))

The Transformed Normalized Difference Vegetation Index algorithm indicates a relation between the amount of green biomass that is found in a pixel. (Senseman et.al. 1996). Transformed Normalised Difference Vegetation index (TNDVI) is the square root of the NDVI. It has higher coefficient of determination for the same variable and this is the difference between TNDVI and NDVI. The formula of TNDVI has always positive values and the variances of the ratio are proportional to mean values. The TNDVI results from the following equation: TNDVI = sqrt( (IR_factor * near_IR - red_factor * red) / (IR_factor * near_IR + red_factor * red) + 0.5)

The Pigment Specific Simple Ratio (chlorophyll index) algorithm was developed by Blackburn (1998). It investigates the potential of a range of spectral approaches for quantifying pigments at the scale of the whole plant canopy. When applying existing narrow-band pigment indices the PSSR algorithms have the strongest and most linear relationships with canopy concentration per unit area of Chl a (Chlorophyll a) Chl b (Chlorophyll b) and Cars (carotenoids). The PSSRa results from the following equation: PSSRa = (IR_factor * near_IR) / (red_factor * red)

The Pigment Specific Simple Ratio (chlorophyll index) algorithm was developed by Blackburn (1998). It investigates the potential of a range of spectral approaches for quantifying pigments at the scale of the whole plant canopy. When applying existing narrow-band pigment indices the PSSR algorithms have the strongest and most linear relationships with canopy concentration per unit area of Chl a (Chlorophyll a) Chl b (Chlorophyll b) and Cars (carotenoids). The PSSRa results from the following equation: PSSRa = (IR_factor * near_IR) / (red_factor * red)

The Weighted Difference Vegetation Index algorithm was introduced by Clevers (1988). This has a relationship to PVI similar to the relationship IPVI has to NDVI. WDVI is a mathematically simpler version of PVI but it has an unrestricted range.Like PVI WDVI is very sensitive to atmospheric variations (Qi et al. 1994). The WDVI results from the following equation: WDVI = (IR_factor * near_IR - g * red_factor * red) where: g is the slope of the soil line.

The Redness Index algorithm was developed to identify soil colour variations - Pouget et al.(1990). The RI results from the following equation: RI = (red_factor * red * red_factor * red) / (green_factor * green * green_factor * green * green_factor * green)