This Remote sensing is fast becoming one of the
most successful techniques in studying and classifying land-cover
classes. Satellite remote sensing technology has provided
environmental managers with a relatively cheap and accessible
technique to accurately classify earth’s features into common
groups based on the similarities in behavior of their component
structures. As the sun’s electromagnetic light energy reaches
earth surface, they are either absorbed and/or re-radiated into
the atmosphere, depending on the component and structure of
the receiving surface. The extent of absorption or radiation also
depends on these components. Space satellite sensors are able to
determine the wavelengths of light energy absorbed and reflected
by the earth’s surface. This paper assesses how three dominant
land cover types (vegetation, water bodies and built-up areas
which include buildings, pavements and tarmacs) usurp
electromagnetic radiation, how satellite sensors are able to
measure the radiation wavelengths and how RS technology uses
data obtained by remote sensors which measure wavelengths of
absorbed and reflected energy. The paper also presents the
spectral response of these land cover types and their
corresponding mathematical indices; Normalized Difference
Vegetation Index, Normalized Difference Water Index and
Normalized Difference Built-up Index (NDVI, NDWI and NDBI).
The paper shows that vegetation absorbs most of the visible light
in the electromagnetic spectrum (red and blue) but has a high
reflectance in the near-infrared (NIR) band of the
electromagnetic spectrum. This is because infrared light inhibits
photosynthesis causes desiccation. Deep water bodies, on the
other hand, quickly absorb NIR and red wavelengths, and
reflects blue wavelength back into the atmosphere. These indices
can be used to compute and determine specific land cover types
from a constellation of several land cover categories on satellite
imageries. LandSat-8 imagery of Nantucket Island, state of
Massachusetts, USA was used for the computation
