Optical Basics
=====================
.. sidebar:: Optical Basics

What is Optical Remote Sensing?
---------------------------------

In the most basic description, optical remote sensing uses visible (VIS), near infrared (NIR), and shortwave infrared (SWIR) bands to detect and measure the properties of the
environment. Usually, multispectral sensors are used, which separate the electromagnetic (EM) spectrum into discrete bands associated with a range of wavelengths.

Some of these wavelengths we can see with the human eye in the form of colors. Other wavelengths can be viewed by specific animals, cameras or special sensors.
Satellites house these sensors and capture the specific wavelengths via reflectance bands.

Example: Vegetation Indices
-----------------------------

Let's take plant health insights for example.
The graphic below illustrates which reflectance band on its own provides relevant insights to specific aspects of a plant depending on the wavelength.

.. figure:: ../resources/images/607c3874134b1e3bd4797cab_imageVi.png
    :alt: EM Spectrum

    Example of different reflectance bands available at varying wavelengths. Top row depicts the corresponding plant health insights.

Bands in the 1st zone are in the **visible wavelength spectrum** (RGB: red, green and blue) and provide information on leaf pigmentation, which is useful to determine the growing stage
of the crop, and a basic indicator of crop health. During photosynthesis, plants rely on the green pigment chlorophyll to convert energy from the sun for fuel.
The 2nd zone **near-infrared (NIR)** wavelengths are a great way to detect healthy growing plants through chlorophyll detection, representing plant productivity more directly.
Bands in **shortwave infrared** 3rd zone provide information on the water content with the plants as well as biochemical components in leaves.
The data returned from these observations are spectral reflectance, that is, a numeric value corresponding to the strength of the detected radiation in each spectral band.

Besides vegetation indices, optical remote sensing can be leveraged for land use classification, infurstructure monitoring, disaster monitoring and recovery, and so much more.

Sentinel-2 Optial imagery in SpaceSense's Library
---------------------------------

The SpaceSense library currently uses Sentinel-2 Level 2A data, which represents surface reflectance having already corrected for atmospheric effects. The following table
shows the details of the spectral bands used in the S2 data.

+------------+------------+---------------------+--------------------------------------+
| Band	     | Resolution | Central Wavelength  |Description                           |
+============+============+=====================+======================================+
| B01        | 60 m       | 443 nm              | Ultra Blue (Coastal and Aerosol)     |
+------------+------------+---------------------+--------------------------------------+
| B02        | 10 m       | 490 nm              | Blue                                 |
+------------+------------+---------------------+--------------------------------------+
| B03        | 10 m       | 560 nm              | Green                                |
+------------+------------+---------------------+--------------------------------------+
| B04        | 10 m       | 665 nm              | Red                                  |
+------------+------------+---------------------+--------------------------------------+
| B05        | 20 m       | 705 nm              | Visible and Near Infrared (VNIR)     |
+------------+------------+---------------------+--------------------------------------+
| B06        | 20 m       | 740 nm              | Visible and Near Infrared (VNIR)     |
+------------+------------+---------------------+--------------------------------------+
| B07        | 20 m       | 783 nm              | Visible and Near Infrared (VNIR)     |
+------------+------------+---------------------+--------------------------------------+
| B08        | 10 m       | 842 nm              | Visible and Near Infrared (VNIR)     |
+------------+------------+---------------------+--------------------------------------+
| B8a        | 20 m       | 865 nm              | Visible and Near Infrared (VNIR)     |
+------------+------------+---------------------+--------------------------------------+
| B09        | 60 m       | 940 nm              | Short Wave Infrared (SWIR)           |
+------------+------------+---------------------+--------------------------------------+
| B11        | 20 m       | 1610 nm             | Short Wave Infrared (SWIR)           |
+------------+------------+---------------------+--------------------------------------+
| B12        | 20 m       | 2190 nm             | Short Wave Infrared (SWIR)           |
+------------+------------+---------------------+--------------------------------------+

Please note, Band 10 is not available for level 2A Sentinel-2 data, as this band is used for atmospheric corrections only.

To learn more about Sentinel-2 bands, their details, and their uses, `this page <https://gisgeography.com/sentinel-2-bands-combinations/>`_ has many resources available.

Sentinel-2 also provides an SCL or Scene Classification Layer, which aims to classify pixels of clouds, cloud shadows,
vegetation, soils/deserts, water, and snow, as well as defective, saturated, no data, or unclassified values. For more information about Sentinel-2's SCL band, please visit
`this page describing the Sentinel-2 algorithm <https://sentinels.copernicus.eu/web/sentinel/technical-guides/sentinel-2-msi/level-2a/algorithm-overview>`_.