Rindcalc Documentation¶

About¶

Rindcalc is an open source python library built on NumPy and GDAL with the goal of providing seamless raster index calculations and composites of satellite imagery for remote sensing. It looks to fill the gap left by proprietary softwares and open source initiatives alike when it comes to the need to create and process spectral index raster files.

Satellites & Imagery¶

Landsat-8

Index raster creation

Composites

Cloud Masking

National Agricultural Imagery Program - NAIP

Index raster creation

Composites

Sentinel-2 - WIP

MODIS - WIP

Example of use:¶

Calculating the ARVI of a NAIP tile and saving as a raster.¶

import rindcalc as rc

# set inputs and outputs
input_naip = '/naip_folder/m_3008101_ne_17_1_20151017.tif'
output_arvi = '/naip_outputs/ARVI_3008101_ne_17.tif'

data = rc.NAIP(path)
data.ARVI(output_ndvi)

Output ARVI raster:

Using in conjunction with matplotlib¶

import rindcalc as rc
import matplotlib.pyplot as plt

ls = '/landsat_8/2019_11_28'
index = ls.AWEIsh('/landsat_8/2019_11_28')
plt.imshow(index, 'ocean')
plt.title('AWEIsh - Water Index')
plt.show()

Creating a false color composite of a Landsat-8 Scene.¶

from rindcalc import Landsat

ls = rc.Landsat('/landsat_8/LC08_L1TP_197031_20131212_20170428_01_T1')
ls.composite(['band_5', 'band_4', 'band_3'], '/landsat_8_outputs/FalseColor_Barcelona.tif')

Output false color composite:

Install¶

With pip from PyPI repository¶

PyPI repository

Dependencies

GDAL (v 3.0.0 or greater)
NumPy (v 1.0.0 or greater)

pip install rindcalc

With Conda from Anaconda Cloud¶

Conda Cloud

conda install -c rindcalc rindcalc

Latest development version¶

For latest version clone the Rindcalc GitHub Repository and add the module to path with sys.path.append.

Landsat-8¶

Rindcalc uses the standard naming convention of landsat bands, it only needs the folder in which Landsat-8 bands are contained as the input. This method allows for easy, quick, and consistent index calculations from Landsat-8 imagery.

The Landsat 8 satellite orbits the the Earth in a sun-synchronous, near-polar orbit, at an altitude of 705 km (438 mi), inclined at 98.2 degrees, and circles the Earth every 99 minutes. The satellite has a 16-day repeat cycle with an equatorial crossing time: 10:00 a.m. +/- 15 minutes.

Landsat 8 aquires about 740 scenes a day on the Worldwide Reference System-2 (WRS-2) path/row system, with a swath overlap (or sidelap) varying from 7 percent at the Equator to a maximum of approximately 85 percent at extreme latitudes. The scene size is 185 km x 180 km (114 mi x 112 mi) (USGS).

Landsat-8 scene composite created with rindcalc RGB composite function.

class rindcalc.Landsat(path)¶

ARVI(out_tif=None, mask_clouds=False)¶

Calculates ARVI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

AWEInsh(out_tif=None, mask_clouds=False)¶

Calculates AWEInsh index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

AWEIsh(out_tif=None, mask_clouds=False)¶

” Calculates AWEIsh index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

EBBI(out_tif=None, mask_clouds=False)¶

Calculates EBBI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

GNDVI(out_tif=None, mask_clouds=False)¶

Calculates GNDVI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

MNDWI(out_tif=None, mask_clouds=False)¶

Calculates MNDWI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

NBLI(out_tif=None, mask_clouds=False)¶

Calculates NBLI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

NBRI(out_tif=None, mask_clouds=False)¶

Calculates NBRI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

NDBI(out_tif=None, mask_clouds=False)¶

Calculates NDBI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

NDBaI(out_tif=None, mask_clouds=False)¶

Calculates NDBaI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

NDMI(out_tif=None, mask_clouds=False)¶

Calculates NDMI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

NDVI(out_tif=None, mask_clouds=False)¶

Calculates NDVI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

SAVI(out_tif=None, soil_brightness=0.5, mask_clouds=False)¶

Calculates SAVI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. soil_brightness (float) – Soil brightness factor to compute SAVI with. Defaults to 0.5 mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

UI(out_tif=None, mask_clouds=False)¶

Calculates UI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

VARI(out_tif=None, mask_clouds=False)¶

Calculates VARI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF. mask_clouds (bool, optional) – Whether or not to apply cloud masking to output index with the QA band.
Returns:	equation – Output array of the generated index.
Return type:	array

__init__(path)¶

Class to read and write Landsat-8 data from.

Parameters:	path (str) – Path to folder where Landsat-8 bands are contained.

path¶

Dictionary of the path for each Landsat-8 band.

Type:	dict

bands¶

Dictionary of arrays for the bands chosen to load.

Type:	dict, array

band_options¶

List of all options for band input names.

Type:	list

composite(which_bands, out_composite)¶

Creates a three band composite out of the specified bands.

Parameters:	which_bands (list) – A list of bands to save as a three band composite. Must be in order of how the bands are to saved within the output TIFF. e.g. which_bands=[‘band_1’, ‘band_2’, ‘band_3’] out_composite (str) – The output filename to save the composite,

load_bands(which_bands=None)¶

Opens and reads bands into Float 32 arrays. If no list is passed into which bands then all bands are opened and added to the dictionary self.bands.

Parameters:	which_bands (list, optional) – A list of band names to open as arrays. e.g. which_bands=[‘band_1’, ‘band_2’, ‘band_3’]
Returns:	self.bands – Updated self.bands dictionary
Return type:	dict

NAIP¶

The National Agriculture Imagery Program (NAIP) acquires aerial imagery during the agricultural growing seasons in the continental U.S. A primary goal of the NAIP program is to make digital ortho photography available to governmental agencies and the public within a year of acquisition.

The default spectral resolution is natural color (Red, Green and Blue, or RGB) but beginning in 2007, some states have been delivered with four bands of data: RGB and Near Infrared (USDA).

class rindcalc.NAIP(path)¶

ARVI(out_raster=None)¶

Calculates ARVI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

NDVI(out_raster=None)¶

Calculates NDVI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

RedRatio(out_raster=None)¶

Calculates ARVI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

SAVI(soil_brightness=0.5, out_raster=None)¶

Calculates SAVI index

Parameters:	soil_brightness (float) – Soil brightness factor to compute SAVI with. Defaults to 0.5 out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

VARI(out_raster=None)¶

Calculates VARI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

__init__(path)¶

Class to read and write NAIP data from.

Parameters:	path (str) – Path to folder where Sentinel-2 bands are contained.

path¶

Dictionary of the path for each Landsat-8 band.

Type:	dict

bands¶

Dictionary of arrays for the bands chosen to load.

Type:	dict, array

band_options¶

List of all options for band input names.

Type:	list

composite(which_bands, out_composite)¶

Creates a three band composite out of the specified bands.

Parameters:	which_bands (list) – A list of bands to save as a three band composite. Must be in order of how the bands are to saved within the output TIFF. e.g. which_bands=[‘band_1’, ‘band_2’, ‘band_3’] out_composite (str) – The output filename to save the composite,

load_bands(which_bands=None)¶

Opens and reads bands into Float 32 arrays. If no list is passed into which bands then all bands are opened and added to the dictionary self.bands.

Parameters:	which_bands (list, optional) – A list of band names to open as arrays. e.g. which_bands=[‘band_1’, ‘band_2’, ‘band_3’]
Returns:	self.bands – Updated self.bands dictionary
Return type:	dict

Sentinel-2¶

class rindcalc.Sentinel(path)¶

ARVI(out_raster=None)¶

Calculates ARVI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

AWEIsh(out_raster=None)¶

Calculates AWEIsh index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

GNDVI(out_raster=None)¶

Calculates GNDVI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

IRECI(out_raster=None)¶

Calculates IRECI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

MCARI(out_raster=None)¶

Calculates MCARI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

MTCI(out_raster=None)¶

Calculates MTCI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

NDI45(out_raster=None)¶

Calculates NDI45 index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

NDVI(out_raster=None)¶

Calculates NDVI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

PSSR(out_raster=None)¶

Calculates PSSR index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

S2REP(out_raster=None)¶

Calculates S2REP index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

SIPI(out_raster=None)¶

Calculates SIPI index

Parameters:	out_raster (str, optional) – Output filepath for calculated TIFF.
Returns:	equation – Output array of the generated index.
Return type:	array

__init__(path)¶

Class to read and write Sentinel-2 data from.

Parameters:	path (str) – Path to folder where Sentinel-2 bands are contained.

path¶

Dictionary of the path for each Sentinel-2 band.

Type:	dict

bands¶

Dictionary of arrays for the bands chosen to load.

Type:	dict, array

band_options¶

List of all options for band input names.

Type:	list

composite(which_bands, out_composite)¶

Creates a three band composite out of the specified bands.

Parameters:	which_bands (list) – A list of bands to save as a three band composite. Must be in order of how the bands are to saved within the output TIFF. e.g. which_bands=[‘band_1’, ‘band_2’, ‘band_3’] out_composite (str) – The output filename to save the composite,

load_bands(which_bands=None)¶

Opens and reads bands into Float 32 arrays. If no list is passed into which bands then all bands are opened and added to the dictionary self.bands.

Parameters:	which_bands (list, optional) – A list of band names to open as arrays. e.g. which_bands=[‘band_1’, ‘band_2’, ‘band_3’]
Returns:	self.bands – Updated self.bands dictionary
Return type:	dict

Band Utilities¶

rindcalc.utils.resample.resample(band, cell_size, out=None)¶

Utility function to resample a raster and output it as either an array or TIFF

Parameters:	band (str) – Path to raster file to resample cell_size (int) – New size of the cells out (str, optional) – Filename to save the output TIFF
Returns:	resampled array

rindcalc.utils.gen_stats.gen_stats(raster_path)¶

Prints minimum, maximum, mean, median, and standard deviation values for a raster.

Parameters:	raster_path (str, required) – input raster with which to generate statistical summary of.
Returns:	minimum maximum mean median standard deviation

Index Formula List¶

All index formulas are grouped by specific use here.

Water Indices¶

Indices designed for water detection

Automated Water Extraction Index | AWEIsh¶

For areas with increased shadow.
AWEIsh = ((Blue + 2.5 * Green - 1.5 * (NIR + SWIR1) - 0.25 * SWIR2)) /

(Blue + Green + NIR + SWIR1 + SWIR2))

Automated Water Extraction Index | AWEInsh¶

For areas with minimal shadow.
AWEInsh = ((4 * (Green - SWIR1) - (0.25 * NIR + 2.75 *

SWIR1)) / (Green + SWIR1 + NIR))

Normalized Difference Moisture Index | NDMI¶

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

Modified Normalized Difference Water Index | MNDWI¶

MNDWI = ((Green - SWIR1) / (Green + SWIR1))

Vegetation Indices¶

Indices designed for vegetation detection

Normalized Difference Vegetation Index | NDVI¶

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

Green Normalized Difference Vegetation Index | GNDVI¶

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

Atmospherically Resistant Vegetation Index | ARVI¶

ARVI = (NIR - (2 * Red) + Blue) / (NIR + (2 * Red) + Blue)

Visual Atmospherically Resistant Index | VARI¶

VARI = ((Green - Red) / (Green + Red - Blue))

Soil Adjusted Vegetation Index | SAVI¶

SAVI = ((NIR - Red) / (NIR + Red + L)) x (1 + L)
- L = Soil Brightness Factor

Structure Insensitive Pigment Index | SIPI¶

SIPI = (NIR – Blue) / (NIR – Red)

Urban / Landscape Indices¶

Indices designed for urban and landscape detection

Normalized Difference Built-up Index | NDBI¶

NDBI = (SWIR1 - NIR) / (SWIR1 + NIR)

Nomrmalized Difference Bareness Index | NDBaI¶

NDBaI = ((SWIR1 - TIR) / (SWIR1 + TIR))

Normalized Bare Land Index | NBLI¶

NBLI = ((Red - TIR) / (Red + TIR))

Enhanced Built-up and Barness Index | EBBI¶

EBBI = ((SWIR1 - NIR) / (10 * (np.sqrt(SWIR1 + tir))))

Urban Index | UI¶

UI = ((SWIR2 - NIR) / (SWIR2 + NIR))

Burn / Fire Indices¶

Indices designed for fire and burned area detection

Normalized Burn Ratio Index | NBRI¶

NBRI = ((NIR - SWIR2) / ( NIR + SWIR2))

Contact¶

Owen Smith

Project GitHub: rindcalc

Email: ocsmit7654@ung.edu

Authors:	Owen Smith, University of North Georgia IESA
Version:	2.0.5
License:	GPL v3.0