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rindcalc

Raster Index Calculator

rind calc is a python package created to allow complete raster index calculation using Landsat-8 using gdal and numpy. Landsat bands are pulled directly from file downloaded from USGS containing all bands os landsat scene. Since rindcalc only requires the file in which Landsat-8 bands are contained instead of each individual band to be specified, it allows for easy, quick, and seamless index calculations from Landsat-8 imagery.

Dependencies

  • GDAL (v 3.0.0 or greater)
  • numpy (v 1.0.0 or greater)

Installation

Windows

pip install rindcalc

For Windows installation gdal wheels must be installed first.

Modules

landsat_dir = Landsat-8 folder that contains all bands

*_out = out file raster will be saved as

i.e. Landsat-8 folder structure:

.
|--LC08_L1TP_091086_20191222_20191223_01_RT                     Landsat Folder ex. #1
|   |-- LC08_L1TP_091086_20191222_20191223_01_RT_B1.TIF
|   |-- LC08_L1TP_091086_20191222_20191223_01_RT_B2.TIF
|   |-- LC08_L1TP_091086_20191222_20191223_01_RT_B3.TIF
|   |-- ...
|-- 2019_12_22                                                  Landsat Folder ex. #2
|   |-- LC08_L1TP_091086_20191222_20191223_01_RT_B1.TIF
|   |-- LC08_L1TP_091086_20191222_20191223_01_RT_B2.TIF
|   |-- LC08_L1TP_091086_20191222_20191223_01_RT_B3.TIF
|   |-- ...
  • AWEIsh(landsat_dir, aweish_out)
  • NDMI(landsat_dir, ndmi_out)
  • MNDWI(landsat_dir, mndwi_out)
  • NDVI(landsat_dir, ndvi_out)
  • GNDVI(landsat_dir)
  • SAVI(landsat_dir, soil_brightness, savi_out)
  • NDBI(landsat_dir, ndbi_out)
  • NDBaI(landsat_dir, ndbai_out)
  • NBLI(landsat_dir, nbli_out)
  • EBBI(landsat_dir, ebbi_out)
  • NBRI(landsat_dir, nbri_out)

EX:

import rindcalc as rc
landsat_dir = 'C:/.../.../LC08_L1TP_091086_20191222_20191223_01_RT'
ndvi_out = 'C:/.../.../NDVI_1.tif'
rc.NDVI(landsat_dir, ndvi_out)

OR:

import rindcalc as rc
rc.NDVI(landsat_dir = 'C:/.../.../2019_12_22', ndvi_out = 'C:/.../.../NDVI_2.tif')

Indices

Water

  • AWEIsh = ((Blue + 2.5 * Green - 1.5 * (NIR + SWIR1) - 0.25 * SWIR2)) / (Blue + Green + NIR + SWIR1 + SWIR2)

  • NDWI = ((nir_band - swir1_band) / (nir_band + swir1_band))

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

Moisture

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

Vegetation

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

  • Green NDVI (GNDVI) = ((nir_band - green_band) / (nir_band + green_band))

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

    • L = Soil Brightness Factor

Landscape

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

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

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

  • EBBI = ((swir1_band - nir_band) / (10 * (np.sqrt(swir1_band + tir_band))))

Fire

  • NBRI = ((nir_band - swir2_band) / (nir_band + swir2_band))

Metadata

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