# Remote Sensing for Precision Agriculture: Sentinel-2 Improved Features and Applications
## 2 Remote Sensing for Agriculture
### Sentinel-2 Data Access, Secondary Products, and Support Tools  
Regarding some of the highest spatial and temporal resolution satellites, such as Planet, the access to imagery is private or at least restricted, and therefore inaccessible for many institutions with limited funding, especially in developing countries. Besides that, NASA satellites, namely MODIS and LANDSAT-8 for instance, are publicly accessible and completely free, as well as ESA's entire Sentinel program, including Sentinel-2, along with the other sun-synchronous orbiting satellites that form part \begin{table}
\begin{tabular}{c c c} \hline \hline
**VIs** & **Sentinel-2 Bands Used** & **Original Author** \\ \hline NGRDI & \(\left(\text{B3}-\text{B4}\right)/\left(\text{B3}+\text{B4}\right)\) [PERSON] (2005) \\ TGI & \(-0.5\times\left[190\times\left(\text{B4}-\text{B3}\right)-120\times\left( \text{B4}-\text{B2}\right)\right]\) [PERSON] (2012) \\ NDVI & \(\left(\text{B8}-\text{B4}\right)/\left(\text{B8}+\text{B4}\right)\) [PERSON] (1979) \\ TCARI/OSAVI & \(3\times\left[\left(\text{B5}-\text{B4}\right)-0.2\times\left(\text{B5}-\text{ B3}\right)\times\left(\text{B5}/\text{B4}\right)\right]/\left[\left(1+0.16\right) \times\left(\text{B7}-\text{B4}\right)\right.\) [PERSON] (2002) \\ MTCI & \(\left(\text{B6}-\text{B5}\right)/\left(\text{B5}-\text{B4}\right)\) [PERSON] Dash and Curran (2004) \\ CVI & \(\left(\text{B8}\right)/\left(\text{B3}/\text{B4}\right)\) [PERSON] (2008) \\ CI red-edge & \(\left(\text{B8}/\text{B5}\right)-1\) [PERSON] (2003) \\ IRECI & \(\left(\text{B7}-\text{B4}\right)/\left(\text{B5}/\text{B6}\right)\) & [PERSON] (2013) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: An example of some spectral vegetation index (VIs) calculations of interest for use with European Space Agency (ESA) Sentinel-2 satellite data, where B is the spectral reflectance value of the band number of the Sentinel-2 band as detailed in Table 1.  
of the greater ESA Copernicus Program. This makes the data more readily accessible and more openly free for a more globally coordinated remote sensing of agriculture in this case. The accessibility to this data is central. In this sense, there are several ways to freely and openly download Sentinel-2 imagery; one of them is the direct download of the imagery from ESA's website, through Copernicus ([[https://scihub.copernicus.eu/dhus/#home](https://scihub.copernicus.eu/dhus/#home)]([https://scihub.copernicus.eu/dhus/#home](https://scihub.copernicus.eu/dhus/#home))). Furthermore, third party tools for downloading the imagery are available. For instance, there is the United States Geological Survey (USGS) ([[https://earthexplorer.usgs.gov/](https://earthexplorer.usgs.gov/)]([https://earthexplorer.usgs.gov/](https://earthexplorer.usgs.gov/))) which allows comprehensive searching and downloading of full-resolution Sentinel-2 images. On the open-source software QGIS, there are various plug-ins that take advantage of the ESA's Application Programing Interface (APIs) at the Copernicus Open Access Hub ([[https://scihub.copernicus.eu/apihub/](https://scihub.copernicus.eu/apihub/)]([https://scihub.copernicus.eu/apihub/](https://scihub.copernicus.eu/apihub/))), such as the free and open source Semi-Automatic Classification Plugin (SCP), developed by [PERSON] [40], which provides tools to simply download Sentinel-2 imagery or even download and immediately calibrate and apply image analyses to the data. Furthermore, the API access portals allow for download only specific bands of select images, thus reducing the storage requirements of personal computers. Moreover, Google Earth Engine has daily updated copies of all the available Sentinel-2 data and provides both access to this data repository along with high processing capacity using their image processing servers. Many other similar tools and services exist on other software applications and web portals and are being developed continuously.