SpectralIndices.jl

| Documentation | Build Status | Julia | Testing | |:-----------------:|:----------------:|:---------:|:-----------:| | | | | |

Overview 📖

SpectralIndices.jl is a Julia package for working with spectral indices commonly used in remote sensing and earth observation applications. It provides a convenient way to compute various spectral indices using Julia's high-performance capabilities.

Features 🚀

• Computation for a wide range of spectral indices
• Computation support for Float64, Float32 and Float16 at index formula level to support fast computation for ML applications
• Support for various data types, including but not limited to (see this issue for an updated list and WIP)
  • [x] Arrays
  • [x] DataFrames
  • [x] YAXArrays
• Flexible parameter input options
• Compatibility with multiple remote sensing platforms and sensors

Installation 💻

SpectralIndices.jl is registered in the general registry, please install it using the following: julia_repl julia> ] pkg> add SpectralIndices or julia using Pkg Pkg.add("SpectralIndices")

Usage 🛠️

```julia using SpectralIndices using DataFrames

Compute NDVI with direct parameter input

result = compute_index("NDVI", N = 0.643, R = 0.175)

Compute NDVI with direct parameter input and direct NDVI call

result = compute_index(NDVI, N = 0.643, R = 0.175)

Compute multiple indices with array inputs

multiresult = computeindex(["NDVI", "SAVI"], N = fill(0.643, 5), R = fill(0.175, 5), L = fill(0.5, 5))

use Dataframes

df = DataFrame(N = [0.643, 0.560], R = [0.175, 0.225]) resultdfsingle = compute_index("NDVI", df)

Multiple inputs in a dataframe

df = DataFrame(N = [0.643, 0.560], R = [0.175, 0.225], L = [0.5, 0.5]) resultdfmultiple = compute_index(["NDVI", "SAVI"], df) ```

To compute at custom Float precision input the bands at the chosen precision and specify the Float type to the compute_index function ```julia

Compute NDVI with direct parameter input

result = compute_index(Float32, "NDVI", N = Float32(0.643), R = Float32(0.175)) ```

Code Structure

Contributing 🤝

Contributions to SpectralIndices.jl are welcome! If you would like to contribute, please see our Contribution Guidelines for more information.

License 📜

SpectralIndices.jl is licensed under the MIT License. See LICENSE for more information.

Acknowledgments ✨

This package is inspired by the Spyndex Python library for spectral indices. The logo is AI-generated by dalle3 through ChatGPT and modified by the talented David Montero.

Support 🆘

If you have any questions, issues, or feature requests, please open an issue or contact us via email.

Citation 🔗

If you use SpectralIndices.jl in your research, please consider citing it using the following DOI:

bibtex @article{martinuzzi2024spectral, title = {SpectralIndices.jl: Streamlining spectral indices access and computation for Earth system research}, volume = {XLVIII-4/W12-2024}, ISSN = {2194-9034}, url = {http://dx.doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-89-2024}, DOI = {10.5194/isprs-archives-xlviii-4-w12-2024-89-2024}, journal = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, publisher = {Copernicus GmbH}, author = {Martinuzzi, Francesco and Mahecha, Miguel D. and Montero, David and Alonso, Lazaro and Mora, Karin}, year = {2024}, month = jun, pages = {89–95} } Also consider citing the paper introducing the Awesome Spectral Indices collection:

bibtex @article{montero2023standardized, title={A standardized catalogue of spectral indices to advance the use of remote sensing in Earth system research}, author={Montero, David and Aybar, C{\'e}sar and Mahecha, Miguel D and Martinuzzi, Francesco and S{\"o}chting, Maximilian and Wieneke, Sebastian}, journal={Scientific Data}, volume={10}, number={1}, pages={197}, year={2023}, publisher={Nature Publishing Group UK London} }