01-intro.Rmd

# Introduction  {#intro}

This guide is intended to introduce the basics of running VICA and  how to implement the libraries in any GEE Script. It describes the VICAL conceptual framework, the vegetation indices (VIs) considered and the images collections used to calculate it, how to run it, what the outputs are, and how they are formatted.

VICAL was developed within the GEE platform <https://earthengine.google.com/> and was coded in JavaScript from the Earth Engine Code Editor <https://code.earthengine.google.com/>.


## Scopes
The design principles for **VICAL** were that it should provide for any area (defined by the user) where there is a Landsat or Sentinel-2 image, the estimation of different VIs applied in agriculture. In addition, to graph the VI time series for that area in the date range established by the user. **All without the user writing a single line of code within the GEE platform or performing image pre-processing.**

The VICAL tool has three main functions::

**1.-** calculation of 23 VIs with images (cloud-free) from Landsat (4, 5, 7, 8 and 9) and Sentinel-2 data from any user-defined area. 

**2.-** VI time series plot for each polygon drawn by the user with Landsat and Sentinel-2 or both satellites. 

**3.-** Regression maps (linear, quadratic, potential or exponential function) or weighting factor using VIs values. 

In this tool, you can configure some VI coefficients such as EVI, SAVI, among others.

We believe that the **VICAL** tool saves time and avoids the trivial repetitive procedure associated with “manual” VI calculations (image download, processing, etc.), which requires different types of software, which can lead to human error.

VICAL can be used to quickly extract VIs values for calibration in agricultural biophysical variables.