Git Product home page Git Product logo

awesome-spectral-indices's Introduction

Awesome Spectral Indices

A ready-to-use curated list of Spectral Indices for Remote Sensing applications.

Awesome Awesome Spectral Indices Tests Documentation DOI GitHub Sponsors Buy me a coffee Ko-fi Twitter Black


GitHub: https://github.com/davemlz/awesome-ee-spectral-indices

Documentation: https://awesome-ee-spectral-indices.readthedocs.io/


Spectral Indices

The ready-to-use curated list of spectral indices (check the list here) for remote sensing applications is presented here. The list is available in two formats (CSV, JSON) so it can be easily used in any programming language.

Attributes

Each item of the list has the following attributes:

  • short_name: Short name of the index (e.g. "NDWI").
  • long_name: Long name of the index (e.g. "Normalized Difference Water Index").
  • formula: Expression/formula of the index (e.g. "(G - N)/(G + N)").
  • bands: List of required bands/parameters for the index computation (e.g. ["N","G"]).
  • reference: Link to the index reference/paper/doi (e.g. "https://doi.org/10.1080/01431169608948714").
  • type: Type/application of the index (e.g. "water").
  • date_of_addition: Date of addition to the list (e.g. "2021-04-07").
  • contributor: GitHub user link of the contributor (e.g. "https://github.com/davemlz").

Expressions

The formula of the index is presented as a string/expression (e.g. "(N - R)/(N + R)") that can be easily evaluated. The parameters used in the expression for each index follow this standard:

Description Standard Sentinel-2 Landsat-8 Landsat-457 MODIS
Aerosols A B1 B1
Blue B B2 B2 B1 B3
Green G B3 B3 B2 B4
Red R B4 B4 B3 B1
Red Edge 1 RE1 B5
Red Edge 2 RE2 B6
Red Edge 3 RE3 B7
Red Edge 4 RE4 B8A
NIR N B8 B5 B4 B2
SWIR 1 S1 B11 B6 B5 B6
SWIR 2 S2 B12 B7 B7 B7
Thermal 1 T1 B10 B6
Thermal 2 T2 B11

Additional index parameters also follow a standard:

  • g: Gain factor (e.g. Used for EVI).
  • L: Canopy background adjustment (e.g. Used for SAVI and EVI).
  • C1: Coefficient 1 for the aerosol resistance term (e.g. Used for EVI).
  • C2: Coefficient 2 for the aerosol resistance term (e.g. Used for EVI).
  • cexp: Exponent used for OCVI.
  • nexp: Exponent used for GDVI.
  • alpha: Weighting coefficient used for WDRVI.
  • sla: Soil line slope.
  • slb: Soil line intercept.

The kernel indices are constructed using a special type of parameters:

  • kAB: Kernel of bands/parameters A and B (e.g. kNR means k(N,R), where k is the kernel function).
  • p: Kernel degree (used for the polynomial kernel).
  • c: Free parameter that trades off the influence of higher-order versus lower-order terms (used for the polynomial kernel).

Used by

JavaScript

  • spectral: Awesome Spectral Indices for the Google Earth Engine JavaScript API (Code Editor).

Python

  • eemont: A python package that extends Google Earth Engine.
  • eeExtra: A ninja Python package behind rgee, rgeeExtra and eemont.
  • spyndex: Awesome Spectral Indices in Python.

R

  • rgeeExtra: High-level functions to process spatial and simple Earth Engine objects. Popular Third-party GEE algorithms are re-coded from Javascript and Python to R.

Spectral Indices by Type

Vegetation 🌱

A

  • ARVI: Atmospherically Resistant Vegetation Index.
  • ATSAVI: Adjusted Transformed Soil-Adjusted Vegetation Index.

B

  • BNDVI: Blue Normalized Difference Vegetation Index.

C

  • CIG: Chlorophyll Index Green.
  • CIRE: Chlorophyll Index Red Edge.
  • CVI: Chlorophyll Vegetation Index.

D

  • DVI: Difference Vegetation Index.

E

  • EVI: Enhanced Vegetation Index.
  • EVI2: Two-Band Enhanced Vegetation Index.
  • ExG: Excess Green Index.

G

  • GARI: Green Atmospherically Resistant Vegetation Index.
  • GBNDVI: Green-Blue Normalized Difference Vegetation Index.
  • GDVI: Generalized Difference Vegetation Index.
  • GEMI: Global Environment Monitoring Index.
  • GLI: Green Leaf Index.
  • GNDVI: Green Normalized Difference Vegetation Index.
  • GRNDVI: Green-Red Normalized Difference Vegetation Index.
  • GVMI: Global Vegetation Moisture Index.

M

  • MCARI: Modified Chlorophyll Absorption in Reflectance Index.
  • MCARI1: Modified Chlorophyll Absorption in Reflectance Index 1.
  • MCARI2: Modified Chlorophyll Absorption in Reflectance Index 2.
  • MGRVI: Modified Green Red Vegetation Index.
  • MNDVI: Modified Normalized Difference Vegetation Index.
  • MNLI: Modified Non-Linear Vegetation Index.
  • MSAVI: Modified Soil-Adjusted Vegetation Index.
  • MSR: Modified Simple Ratio.
  • MTCI: MERIS Terrestrial Chlorophyll Index.
  • MTVI1: Modified Triangular Vegetation Index 1.
  • MTVI2: Modified Triangular Vegetation Index 2.

N

  • NDREI: Normalized Difference Red Edge Index.
  • NDVI: Normalized Difference Vegetation Index.
  • NGRDI: Normalized Green Red Difference Index.
  • NLI: Non-Linear Vegetation Index.

O

  • OCVI: Optimized Chlorophyll Vegetation Index.
  • OSAVI: Optimized Soil-Adjusted Vegetation Index.

R

  • RDVI: Renormalized Difference Vegetation Index.
  • RVI: Ratio Vegetation Index.

S

  • SARVI: Soil Adjusted and Atmospherically Resistant Vegetation Index.
  • SAVI: Soil-Adjusted Vegetation Index.
  • SAVI2: Soil-Adjusted Vegetation Index 2.
  • SeLI: Sentinel-2 LAI Green Index.

T

  • TCARI: Transformed Chlorophyll Absorption in Reflectance Index.
  • TCI: Triangular Chlorophyll Index.
  • TGI: Triangular Greenness Index.
  • TSAVI: Transformed Soil-Adjusted Vegetation Index.
  • TVI: Triangular Vegetation Index.

V

  • VARI: Visible Atmospherically Resistant Index.

W

  • WDRVI: Wide Dynamic Range Vegetation Index.
  • WDVI: Weighted Difference Vegetation Index.

Burn πŸ”₯

B

  • BAI: Burned Area Index.
  • BAIS2: Burned Area Index for Sentinel 2.

C

  • CSIT: Char Soil Index Thermal.

N

  • NBR: Normalized Burn Ratio.
  • NBRT: Normalized Burn Ratio Thermal.
  • NDVIT: Normalized Difference Vegetation Index Thermal.

S

  • SAVIT: Soil-Adjusted Vegetation Index Thermal.

Water 🌊

  • MNDWI: Modified Normalized Difference Water Index.
  • NDWI: Normalized Difference Water Index.

Snow β›„

  • NDSI: Normalized Difference Snow Index.

Drought 🏜️

  • NDDI: Normalized Difference Drought Index.
  • NMDI: Normalized Multi‐band Drought Index.

Urban πŸ™οΈ

  • NDBI: Normalized Difference Built-Up Index.

Kernel 🎯

  • kEVI: Kernel Enhanced Vegetation Index.
  • kNDVI: Kernel Normalized Difference Vegetation Index.
  • kRVI: Kernel Ratio Vegetation Index.
  • kVARI: Kernel Visible Atmospherically Resistant Index.

List

Check the full list of spectral indices with their formulas here.

Download Raw Files

You can download or clone the repository:

git clone https://github.com/davemlz/awesome-ee-spectral-indices.git

Or you can download the single files here (right-click > Save link as...):

Credits

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    πŸ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. πŸ“ŠπŸ“ˆπŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❀️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.