rasterFunctionUtils

Creates a raster function that calculates the absolute value of the pixels in a raster. See Abs function.

Creates a raster function that calculates the inverse cosine of the pixels in a raster. See ACos function.

Creates a raster function that calculates the inverse hyperbolic cosine of the pixels in a raster. See Acosh function.

Creates a raster function that calculates the inverse sine of the pixels in a raster. See ASin function.

Creates a raster function that calculates the inverse hyperbolic sine of the pixels in a raster. See Asinh function.

Creates a Aspect function to identify the downslope direction of the maximum rate of change in value from each cell to its neighbors. Aspect can be thought of as the slope direction. The values of the output raster are the compass direction of the aspect. See Aspect function.

Creates a raster function that calculates the inverse tangent of the pixels in a raster. See Atan function.

Creates a raster function that calculates the inverse tangent (based on x,y) of the pixels in a raster. See Atan2 function.

Creates a raster function that calculates the inverse hyperbolic tangent of the pixels in a raster. See Atanh function.

Creates a Band Arithmetic function to calculate BAI. The Burn Area Index (BAI) uses the reflectance values in the red and NIR portion of the spectrum to identify the areas of the terrain affected by fire. See BAI raster function.

Equation: BAI = 1/((0.1 -RED) * (0.1 -RED) + (0.06 - NIR) * (0.06 - NIR))

Creates a Band Arithmetic function to calculate CIg. Chlorophyll index - Green (CIG) method is a vegetation index for estimating the chlorophyll content in leaves using the ratio of reflectivity in the NIR and green bands. See CIg raster function.

Equation: CIg = (NIR / Green)-1

Creates a Band Arithmetic function to calculate CIre. The Chlorophyll Index - Red-Edge (CIre) method is a vegetation index for estimating the chlorophyll content in leaves using the ratio of reflectivity in the NIR and red-edge bands. See CIre raster function.

Equation: CIre = (NIR / RedEdge)-1

Creates a Band Arithmetic function to calculate ClayMinerals. The Clay Minerals (clayMinerals) ratio method is a geological index for identifying mineral features containing clay and alunite using two shortwave infrared (SWIR) bands. It is used in mineral composite mapping. See ClayMinerals raster function.

Equation: CM = SWIR1 / SWIR2

Creates a custom Band Arithmetic function. ser defined method. When using the user defined method to define your band arithmetic algorithm, you can enter a single-line algebraic formula to create a single-band output. The supported operators are -,+,/,*, and unary -. To identify the bands, add B or b to the beginning of the band number. See Band Arithmetic function.

equation: (b1 - b0) / (b1 + b0)

Creates a Band Arithmetic function to calculate EVI. The Enhanced Vegetation Index (EVI) method is an optimized vegetation index that accounts for atmospheric influences and vegetation background signal. It's similar to NDVI but is less sensitive to background and atmospheric noise, and it does not become as saturated as NDVI when viewing areas with very dense green vegetation. See EVI raster function.

Equation: EVI = 2.5 * (NIR - Red) / (NIR + 6 * Red - 7.5 * Blue + 1)

Creates a Band Arithmetic function to calculate FerrousMinerals. The Ferrous Minerals (ferrousMinerals) ratio method is a geological index for identifying rock features containing some quantity of iron-bearing minerals using the SWIR and NIR bands. It is used in mineral composite mapping. See FerrousMinerals raster function.

Equation: FM = SWIR / NIR

Creates a Band Arithmetic function to calculate GEMI. The Global Environmental Monitoring Index (GEMI) method is a nonlinear vegetation index for global environmental monitoring from satellite imagery. It's similar to NDVI, but it's less sensitive to atmospheric effects. It is affected by bare soil; therefore, it's not recommended for use in areas of sparse or moderately dense vegetation. See GEMI raster function.

Equation: GEMI = eta * (1 - 0.25 * eta)-((Red - 0.125)/(1 - Red)) eta = (2 * (NIR * NIR - Red * Red) + 1.5 * NIR + 0.5 * Red)/(NIR + Red + 0.5)

Creates a Band Arithmetic function to calculate GNDVI. The Green Normalized Difference Vegetation Index (GNDVI) method is a vegetation index for estimating photo synthetic activity and is a commonly used vegetation index to determine water and nitrogen uptake into the plant canopy. See GNDVI raster function.

Equation: GNDVI = (NIR-Green)/(NIR+Green)

Creates a Band Arithmetic function to calculate GVITM. The Green Vegetation Index (GVI) method was originally designed from Landsat MSS imagery and has been modified for Landsat TM imagery. It's also known as the Landsat TM Tasseled Cap green vegetation index. It can be used with imagery whose bands share the same spectral characteristics. See GVITM raster function.

Equation: GVI = -0.2848 * Band1 - 0.2435 * Band2 - 0.5436 * Band3 + 0.7243 * Band4 + 0.0840 * Band5 - 0.1800 * Band7

Creates a Band Arithmetic function to calculate IronOxide. The Iron Oxide (ironOxide) ratio method is a geological index for identifying rock features that have experienced oxidation of iron-bearing sulfides using the red and blue bands. It is useful in identifying iron oxide features below vegetation canopies and is used in mineral composite mapping. See IronOxide raster function.

Equation: IronOxide = Red / Blue

Creates a Band Arithmetic function to calculate MNDWI. 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.

Equation: MNDWI = (Green - SWIR) / (Green + SWIR)

Creates a Band Arithmetic function to calculate MSAVI. The Modified Soil Adjusted Vegetation Index (MSAVI) method minimizes the effect of bare soil on the SAVI. See MSAVI raster function.

Equation: MSAVI2 = 0.5 * ((2NIR+1)-sqrt((2NIR+1)(2NIR+1)-8(NIR-Red)))

Creates a Band Arithmetic function to calculate MTVI2. The Modified Triangular Vegetation Index (MTVI2) method is a vegetation index for detecting leaf chlorophyll content at the canopy scale while being relatively insensitive to leaf area index. It uses reflectance in the green, red, and NIR bands. See MTVI2 raster function.

Creates a Band Arithmetic function to calculate NBR. The Normalized Burn Ratio Index (NBRI) uses the NIR and SWIR bands to emphasize burned areas, while mitigating illumination and atmospheric effects. Your images should be corrected to reflectance values before using this index. See NBR raster function.

Equation: NBR = (NIR - SWIR) / (NIR+ SWIR)

Creates a Band Arithmetic function to calculate NDBI. 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. See NDBI raster function.

Equation: NDBI = (SWIR - NIR) / (SWIR + NIR)

Creates a Band Arithmetic function to calculate NDMI. The Normalized Difference Moisture Index (NDMI) is sensitive to the moisture levels in vegetation. It is used to monitor droughts and fuel levels in fire-prone areas. It uses NIR and SWIR bands to create a ratio designed to mitigate illumination and atmospheric effects. See NDMI raster function.

Equation: NDMI = (NIR - SWIR1)/(NIR + SWIR1)

Creates a Band Arithmetic function to calculate NDSI. The Normalized Difference Snow Index (NDSI) is designed to use MODIS (band 4 and band 6) and Landsat TM (band 2 and band 5) for identification of snow cover while ignoring cloud cover. Since it is ratio based, it also mitigates atmospheric effects. See NDSI raster function.

Equation: NDSI = (Green - SWIR) / (Green + SWIR)

Creates a NDVI function. The Normalized Difference Vegetation Index (NDVI) method is a standardized index allowing you to generate an image displaying greenness (relative biomass). This index takes advantage of the contrast of the characteristics of two bands from a multispectral raster dataset—the chlorophyll pigment absorptions in the red band and the high reflectivity of plant materials in the NIR band.

Equation: NDVI = ((NIR - Red)/(NIR + Red))

See NDVI function and NDVI.

Creates a Band Arithmetic function to calculate NDVIre. The Red-Edge NDVI (NDVIre) method is a vegetation index for estimating vegetation health using the red-edge band. It is especially useful for estimating crop health in the mid to late stages of growth, when the chlorophyll concentration is relatively higher. Also, NDVIre can be used to map the within-field variability of nitrogen foliage to understand the fertilizer requirements of crops. See NDVIre raster function.

Equation: NDVIre = (NIR - RedEdge)/(NIR + RedEdge)

Creates a Band Arithmetic function to calculate NDWI. The Normalized Difference Water Index (NDWI) method is an index for delineating and monitoring content changes in surface water. It is computed with the NIR and green bands. See NDWI raster function.

Equation: NDWI = (Green - NIR) / (Green + NIR)

CCreates a Band Arithmetic function to calculate PVI. 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. See PVI raster function.

Equation: PVI = (NIR - a * Red - b) / (sqrt(1 + a*a)) a = slope of the soil line b = gradient of the soil line

Creates a Band Arithmetic function to calculate RTVICore. The Red-Edge Triangulated Vegetation Index (RTVICore) method is a vegetation index for estimating leaf area index and biomass. This index uses reflectance in the NIR, red-edge, and green spectral bands. See RTVICore raster function.

Equation: RTVICore = 100 * (NIR - RedEdge) - 10 * (NIR - Green)

Creates a Band Arithmetic function to calculate SAVI. The Soil-Adjusted Vegetation Index (SAVI) method 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, and it outputs values between -1.0 and 1.0.

Equation: SAVI = ((NIR - Red) / (NIR + Red + L)) x (1 + L)

L = The amount of green vegetation cover

See SAVI raster function.

Creates a Band Arithmetic function to calculate SR. The Simple Ratio (SR) method is a common vegetation index for estimating the amount of vegetation. It is the ratio of light scattered in the NIR and absorbed in red bands, which reduces the effects of atmosphere and topography. See SR raster function.

Equation: SR = NIR / Red

Creates a Band Arithmetic function to calculate SRre. The Red-Edge Simple Ratio (SRre) method is a vegetation index for estimating the amount of healthy and stressed vegetation. It is the ratio of light scattered in the NIR and red-edge bands, which reduces the effects of atmosphere and topography. See SRre raster function.

Equation: SRre = NIR / RedEdge

Creates a Band Arithmetic function to calculate Sultan index. Creates a BandArithmetic function.The Sultan's process takes a six-band 8-bit image and uses the Sultan's Formula method to produce a three-band 8-bit image. The resulting image highlights rock formations called ophiolites on coastlines. This formula was designed based on the TM or ETM bands of a Landsat 5 or 7 scene.

See Sultan raster function.

Creates a Band Arithmetic function to calculate TSAVI. 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. See TSAVI raster function.

Equation: TSAVI = (s * (NIR - s * Red - a)) / (a * NIR + Red - a * s + X * (1 + s * s)) s = the soil line slope a = the soil line intercept X = an adjustment factor that is set to minimize soil noise

Creates a Band Arithmetic function to calculate VARI. The Visible Atmospherically Resistant Index (VARI) method is a vegetation index for estimating vegetation fraction quantitatively with only the visible range of the spectrum. See VARI raster function.

Equation: VARI = (Green - Red) / (Green + Red – Blue)

Creates a Band Arithmetic function to calculate WNDWI. The Weighted Normalized Difference Water Index (WNDWI) method is a water index developed to reduce errors typically encountered in other water indices, including water turbidity, small water bodies, or shadow in remote sensing scenes.

Equation: WNDWI = [Green – α * NIR – (1 – α) * SWIR ] / [Green + α * NIR + (1 – α) * SWIR]

where a is weighted coefficient ranging from 0 to 1.

Creates a raster function that performs a Bitwise And operation on the binary values of two input rasters. See Bitwise And function.

Creates a raster function that performs a Bitwise Left Shift operation on the binary values of two input rasters. See Bitwise Left Shift function.

Creates a raster function that performs a Bitwise Not (complement) operation on the binary value of an input raster. See Bitwise Not function.

Creates a raster function that performs a Bitwise Or operation on the binary values of two input rasters. See Bitwise Or function.

Creates a raster function that performs a Bitwise Right Shift operation on the binary values of two input rasters. See Bitwise Right Shift function.

Creates a raster function that performs a Bitwise Xor operation on the binary values of two input rasters. See Bitwise Xor function.

Creates a raster function that performs a Boolean And operation on the pixel values of two input rasters See Boolean And function.

Creates a raster function that performs a Boolean Not (complement) operation on the pixel values of the input raster. See Boolean Not function.

Creates a raster function that performs a Boolean Or operation on the pixel values of two input rasters See Boolean Or function.

Creates a raster function that performs a Boolean Xor operation on the pixel values of two input rasters See Boolean Xor function.

Creates a raster function that calculates a statistic from multiple rasters, on a pixel-by-pixel basis. The available statistics are majority, maximum, mean, median, minimum, minority, percentile, range, standard deviation, sum, and variety. See Cell Statistics function.

Extracts a portion of an image based on an extent or a polygon geometry. The clip output includes any pixels that intersect the clip geometry.

Creates a Colormap function to define a colormap for a raster by specifying a corresponding color for each pixel value. See Colormap function.

Creates a Composite Bands function to combine multiple inputs into one multiband raster. See Composite Bands function.

Creates a raster function that sets the truthy pixels (value is not 0) to the pixel value from a true raster, and falsy pixels (value is 0) to the pixel value of the false raster. See Con function.

Creates a Contrast And Brightness function that enhances the appearance of raster data by modifying the brightness and contrast within the image. See Contrast And Brightness function.

Creates a Convolution function that performs filtering using the given kernel to enhance the image, e.g. sharpening an image, blurring an image, and detecting edges et al. See Convolution function.

Creates a raster function that calculates the cosine of the pixels in a raster. See Cos function.

Creates a raster function that calculates the hyperbolic cosine of the pixels in a raster. See Cosh function.

Creates a Curvature function that calculates the shape or curvature of the slope. A part of a surface can be concave or convex; you can tell that by looking at the curvature value. The curvature is calculated by computing the second derivative of the surface. See Curvature function.

Creates a raster function that divides the values of two rasters on a pixel-by-pixel basis. See Divide function.

Creates a raster function that performs an equal-to operation on two rasters on a pixel-by-pixel basis. See Equal To function.

Creates a raster function that calculates the base e exponential of the pixels in a raster. See Exp function.

Creates a raster function that calculates the base 2 exponential of the pixels in a raster. See Exp2 function.

Creates a raster function that calculates the base 10 exponential of the pixels in a raster. See Exp10 function.

Creates an Extract Band function to extract one or more bands from a multiband raster. To use bandNames or bandWavelengths, the data source must have corresponding key properties information. See Extract Band function.

Creates a raster function that converts each pixel value of a raster into a floating-point representation. See Float function.

Converts a multiband image into a single-band grayscale image. Specified weights are applied to each of the input bands, and normalization is applied to the output image. The weights are often applied because some bands have variable importance depending on the application. For example, the blue band often contains more noise than other bands.

Creates a raster function that performs a relational greater-than operation on two rasters on a pixel-by-pixel basis. See Greater Than function.

Creates a raster function that performs a relational greater-than-or-equal-to operation on two rasters on a pixel-by-pixel basis. See Greater Than Equal function.

Creates a raster function that converts each pixel value of a raster to an integer by truncation. See Int function.

Creates a raster function that determines which values from the input raster are NoData on a pixel-by-pixel basis. See Is Null function.

Creates a raster function that performs a relational less-than operation on two rasters on a pixel-by-pixel basis. See Less Than function.

Creates a raster function that performs a relational less-than-or-equal-to operation on two rasters on a pixel-by-pixel basis. See Less Than Equal function.