---
title: "Features"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Features}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---
  
```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  eval = FALSE
)
```

`rgeeExtra` serves as a wrapper for the Python package named `eeExtra`. The creation of `eeExtra` was driven by a need to consolidate various third-party GEE Javascript and Python packages and projects found on GitHub in the same programming language and style, avoiding dependencies. `rgeeExtra` ensures a seamless integration of `eeExtra` within the R ecosystem

Key features of `rgeeExtra` include:

1. **Automatic Scaling and Offsetting**: Simplifying the adaptation and visualization of images and datasets.

2. **Spectral Indices Computation**: Harnessing the capabilities of Awesome Spectral Indices, it allows for the calculation of a wide range of spectral indices from satellite imagery.

3. **Clouds and Shadows Masking**: An essential tool for processing satellite images, it identifies and masks areas impacted by clouds and their shadows.

4. **STAC-related Functions**: Streamlining interactions with the SpatioTemporal Asset Catalog (STAC), standardizing the description of spatiotemporal datasets.

5. **Operator Overloading**: Provides a more direct and simplified interaction with data, enhancing code clarity and efficiency.


```{r setup}
library(rgeeExtra)
library(rgee)

ee_Initialize()        # Initialize the Google Earth Engine API connection
extra_Initialize()     # Initialize the extended functionalities of rgeeExtra
```


## **1. Features for `ee$Feature` and `ee$FeatureCollection`**

### **Subsetting**

todo

### **length**

todo

### **names**

todo

## **2. Features for ee$Image**

### **Subsetting**

todo

### **length**

todo

### **names**

todo

### **getCitation**

todo

### **getCitation**

todo
    
### **getDOI**

todo

### **getOffsetParams**

todo

### **getScaleParams**

todo

### **getSTAC**

todo

### **getSTAC**

todo

### **spectralIndex**

todo

### **preprocess**

todo

### **panSharpen**

todo

### **maskClouds**

todo

### **matchHistogram**

todo

### **tasseledCap**

todo

### **scaleAndOffset**

todo

## **2. Features for ee$ImageCollection**

todo

### **Subsetting**

todo

### **length**

todo

### **names**

todo

### **closest**

todo

### **getCitation**

todo

### **getDOI**

todo

### **getOffsetParams**

todo

### **getScaleParams**

todo

### **getSTAC**

todo

### **spectralIndex**

todo

### **preprocess**

todo

### **scaleAndOffset**

todo

### **tasseledCap**

todo

### **panSharpen**

todo


## **3. Third-party repositories**


## **1. Automatic Scaling and Offsetting**

- [Image or ImageCollection]$getOffsetParams: Apply offset 
parameters for each bands.

- [Image or ImageCollection]$getScaleParams: Apply scale parameters for each bands.

```{r}
ee$ImageCollection("NASA/GPM_L3/IMERG_V06") %>%
  ee$ImageCollection$first() %>%
  ee$ImageCollection$getOffsetParams()

ee$ImageCollection("NASA/GPM_L3/IMERG_V06") %>%
  ee$ImageCollection$first() %>%
  ee$Image$getScaleParams()
```


## **2. Spectral Indices Computation**

Computes one or more spectral indices for an `ee$Image` or an `ee$ImageCollection` object.

```{r}
s2_indices <- ee$ImageCollection("COPERNICUS/S2_SR") %>%
  ee$ImageCollection$first() %>%
  ee$Image$preprocess()%>%
  ee$Image$spectralIndex(c("NDVI", "SAVI"))

names(s2_indices)
```


## **3. Clouds and Shadows Masking**

Masks clouds and shadows in an `ee$Image`. Valid just for Surface Reflectance products. This function may mask water as well as clouds for the Sentinel-3 Radiance product.

```{r}
img <- ee$ImageCollection("COPERNICUS/S2_SR") %>%
  ee$ImageCollection$first() %>%
  ee$Image$maskClouds(prob = 75,buffer = 300,cdi = -0.5)

names(img)
```

## **4. STAC-related Functions**


Streamlining interactions with the SpatioTemporal Asset Catalog (STAC), get metadata easier!

```{r}
# get metadata
ee$ImageCollection("NASA/GPM_L3/IMERG_V06") %>%
  ee$ImageCollection$first() %>%
  ee$Image$getSTAC() %>%
  ee$Image$getInfo()

# get citation
ee$ImageCollection("NASA/GPM_L3/IMERG_V06") %>%
  ee$ImageCollection$first() %>%
  ee$Image$getDOI()
```

## **5. Third-party repositories**


### **5.1 Apply pansharpening**

Apply panchromatic sharpening to an `ee$Image` or an `ee$ImageCollection`. Optionally, run quality assessments between the original and sharpened Image to measure spectral distortion and set results as properties of the sharpened Image.

```{r}
img <- ee$Image("LANDSAT/LC08/C01/T1_TOA/LC08_047027_20160819")
img_sharp <- ee$Image$panSharpen(img, method="HPFA", qa=c("MSE", "RMSE"), maxPixels=1e13)

Map$centerObject(img)
Map$addLayer(img_sharp, list(bands=c("B4", "B3", "B2"))) |
Map$addLayer(img, list(bands=c("B4", "B3", "B2")))
```

<center>
<img src=img02.png width=75%>
</center>