Random Forest Supervised Classification Using Sentinel-2 Data

Introduction to Multi-spectral Imaging

Multispectral imaging (MSI) captures image data within specific wavelengths ranges across electromagnetic spectrum. MSI detects different images through instruments that are sensitive to different wavelengths of light thus allowing for distinction in land-type. MSI is a highly informative form of imaging technique as it can move beyond visible light range and can detect and extract data that the human eye fails to capture. Sentinel 2 is an Earth Observation mission from the Copernicus programme that acquires high resolutions of multispectral imagery by conducting frequent visits over a given area. Sentinel-2 is a polar-orbiting Earth Observation Mission from the Copernicus programme that conducts multispectral high-resolution imaging for land monitoring to provide, for example, imagery of vegetation, soil and water cover, inland waterways, and coastal areas. Sentinel-2 can also deliver information for emergency services. Sentinel-2A was launched on 23 June 2015 and Sentinel-2B followed on 7 March 2017. The Sentinel-2 has 13 bands of multispectral data in the visible, near infrared and short-wave infrared part of the spectrum. This tutorial applies images captured by the Sentinel 2A satellite, which provides similar functions to the ones mentioned above.