Remote Sensing
Remote Sensing is a technology to gather information and analyzing an object or
phenomenon without making any physical contact. This technology is used in numerous
fields like geography, hydrology, ecology, oceanography, glaciology, geology.
A geographic information system is a tool that is used for mapping and analyzing feature
events on Earth. The remote sensing and gis technology combine major database operations
like statistical analysis and query, with maps. The GIS manages information on locations and
provides tools for analysis and display of different statistics that include population,
economic development, characteristics, and vegetation. It also allows linking databases to
make dynamic displays. These abilities make GIS different from other systems and make it a
wide range of private and public remote sensing applications for planning and predicting
outcomes from remote sensing satellites.
There are three essential elements for Remote Sensing:
A platform to hold the instrument
A target or object
An instrument or sensor (to observe the target)
Satellite:
Satellites equipped with sensors observing earth are known as the remote sensing satellites.
These satellites go round in a specified orbit and are called the “eyes of the sky”.
Optical and Infrared:
Optical sensors detect solar radiation reflected or scattered from the earth and thus develop
images of Earth. This is known as the Optical and Infrared Remote Sensing. The images
formed by these sensors resemble that of photographs taken by a camera.
Vegetation analysis by remote sensing
Analyzing vegetation using remotely sensed data requires knowledge about the structure and
function of vegetation and its reflectance properties. Knowing which region of the
electromagnetic spectrum to consider and understanding the factors that influence the spec-
tral response of the interest features are critical to correctly interpreting the interaction of
electromagnetic radiation with the surface. In general terms of vegetation analysis by remote
sensing, vegetation can be divided into the follow general categories
Plant Foliage
Canopies
Non-Photosynthetic Vegetation
Plant Foliage
This category comprises plant foliage, including leaves, needles, and other green materials
that vary widely in both shape and chemical composition. The most important leaf
components that affect their spectral properties are: pigments, water, carbon and nitrogen.
Canopies
Different ecosystems, such as forest, grassland, or agricultural field, have different
reflectance properties, even though the properties of individual leaves are usually quite
similar. Vegetation with mostly vertical foliage, such as grass, reflects light differently than
foliage with more horizontally-oriented foliage, seen frequently in trees and tropical forest
plants. The variation in reflectance caused by different canopy structures, much like
individual leaf reflectance, is highly variable with wavelength. The two most significant are
leaf area index (LAI) and leaf angle distribution (LAD).
Non-Photosynthetic Vegetation
NPV Ecosystems can also contain senescent or dead vegetation. This material is often called
non-photosynthetic vegetation because it could be truly dead or simply dormant. Included in
the NPV category are woody structures in many plants, such as tree trunks, stems, and
branches.
vegetation
The most important leaf components that affect their spectral properties are: Pigments,
Water, Carbon and Nitrogen
Calculation of vegetation indices
The following vegetation indices are used to calculate the vegetation indices.
1. Normalized Difference Vegetation Index (NDVI)
2. Enhanced Vegetation Index (EVI)
3. Difference Vegetation Index (DVI)
4. Perpendicular Vegetation Index (PVI)
5. Chlorophyll vegetation index (CVI)
6. Green Normalized Difference Vegetation Index (GNDVI)
7. Soil Adjusted Vegetation Index
8. Atmospherically Resistant Vegetation Index (ARVI)
9. Structure Insensitive Pigment Index (SIPI)
10. Green Chlorophyll Index (GCI)
11. Ratio Vegetation Index (RVI)
NDVI is a vegetation index that describes the difference between the near-infrared and red
ranges and can be used to estimate the density of greenery on land. The index ranges from -1
to 1, however, there is no clear limit for each type of land cover.
Low NDVI values indicate non-vegetated areas and higher values indicate a higher density of
green vegetation. NDVI can be used for drought monitoring and early prediction. It is
calculated by the following formula:
NDVI=NIR-RED/NIR+RED
EVI is an improved vegetation index that is most useful in high LAI (Leaf Area Index)
regions where NDVI can be oversaturated.
DVI is a vegetation difference index, which is relatively the simplest vegetation index
because it shows the difference between near infrared (NIR) and red (Red) ranges.
DVI=NIR-RED
PVI is a vertical vegetation index similar to DVI, but it is sensitive to atmospheric variations.
CVI is the vegetation chlorophyll index, which represents the values of chlorophyll content in
foliage.
GNDVI is the green normalized relative vegetation index, which is an indicator of the
photosynthetic activity of the vegetation cover, and is most often used to estimate the
moisture content and nitrogen concentration in plant leaves.
CAVI is an adjusted ground vegetation factor that minimizes the effect of ground brightness
using a ground brightness correction factor. This is often used in arid regions where
vegetation cover is low.
ARVI is an index of atmospherically resistant vegetation, which is most useful in regions
with high concentrations of atmospheric aerosols.
The SIPI index maximizes sensitivity to the ratio of carotenoids to chlorophyll while
minimizing the effects of variable canopy structure
GCI is a green chlorophyll index, which, unlike the previous Chlorophyll Index RedEdge
index, is calculated using the Green spectral range.
RVI is a ratio vegetation index that indicates the amount of vegetation and high values of the
index are characteristic of areas of high vegetation and low values of land and water areas.
