Remote sensing in plants, botany, application in vegetation classification and conservation, basic mechanism of remote sensing,how it works, satellite mapping techniques and aerial mapping

1. REMOTE SENSING
PREPARED BY
BASIM ANEES T

2.  Remote sensing is the science of obtaining
information about objects or areas from a distance,
without coming direct contact with the object

3.  It can be done with devices on the ground or on
ships, planes and even satellites.
 This helps us to give a broad perspective on
vegetation, climatic change, environmental issues
etc.

4.  Remote sensors collect data by detecting the
energy that is reflected
 Remote sensors can be:
 Passive sensors respond to external stimuli
 They record natural energy that is reflected or
emitted
Passive sensors
Active sensors

5.  Active sensors use internal stimuli to collect data
 For example:
A laser beam remote sensing system projects a
laser beam onto the surface of earth and measures
the time it takes for laser to reflect back to its
sensors

6. APPLICATIONS
 Remote sensing is used in numerous fields like:
 Geography
 Earth science (Hydrology, ecology,
oceanography, glaciology, geology)
 Military Intelligence
 Commercial, economic planning and
humanitarian applications
 Vegetation and environment

7. ELEMENTS IN REMOTE SENSING
 Energy source
 Radiation and atmosphere
 Interaction with the target
 Recording of energy by sensors
 Transmission, reception and processing
 Interpretation and analysis

8. DATA ACQUISITION
 Data acquisition can be done using:
 Radars
 Satellites
 Ultrasound
 Lidar (light detection and ranging)
 Photometers and Radiometers
 Aerial photographs
 Seismographs
 Geodetic

9.  Electromagnetic energy may be detected either
photographically or electronically
 And image produced can be analog or digital
 Aerial photographs are examples of analog images,
while satellite images are of digital images

10. SATELLITE SENSORS
 They revolve around the earth
 The path followed by a satellite is referred to as its
orbit
 They are of two types:
Geostationary
Near polar

12. APPLICATION IN VEGETATION CLASSIFICATION
 The reflectance quality of a vegetation detected
using remote sensors enables its classification
 Green vegetation will reflect more energy than dry
vegetation
 Tree leaves and crop canopies reflect more in
shorter radar wavelengths,
 While tree trunks and limbs reflect more in longer
wavelengths

14.  The density of the tree or plant canopy will affect
the scattering of wavelengths
 Thus by analyzing reflectance, we can determine
characteristics of a vegetation.
 Moreover, Aerial photographs, color infrared
photographs, black and white infra red photographs
helps to identify species.
 They also give the details of branching
characteristics, crown shapes, spatial distribution
and patterns of species.

16.  This information along with the topographic
variables obtained through field work is a valuable
tool in vegetation classification
 Different types of images will display diverse
characteristics of vegetation
 Band 1 of AVHRR (advance very high resolution
radiometer) will allow chlorophyll to absorbed in red
wavelength.
 And a low value indicate high concentration of
chlorophyll

17.  Similarly, Band 2 of AVHRR include infrared
wavelengths and record the cell structure of the
leaves
 High values indicate more growth, indicated by dark
green signatures
 While low value are indicated by orange signatures

19.  Some satellites that successfully identify vegetation
types include:
 Landsat MSS
 Landsat TM
 SPOT HRV
 RADARSAT

20. LIMITATIONS
 Difficulty in distinguishing fine, ecological divisions
between certain vegetation classes.
 If vegetation share common heterogeneous traits
and similar spectral responses, difficulties are
created in classifying vegetations

21. REMOTE SENSING IN ECOSYSTEM MANAGEMENT AND ENVIRONMENTAL
ISSUES
 Remote sensing helps in :
 Habitat suitability mapping
 Monitor habitat loss and fragmentation
 Wetland mapping and monitoring
 Identifying and monitoring threats
 Predicting biodiversity richness
 Predicting species presence or absence

23.  Provide data on vegetation land cover and
pattern of distribution of plant communities
 Mapping and characterizing species habitats
 Identifying biodiversity Hotspots at broad spatial
scale
 In measuring biological productivity
 Forest fire monitoring

25.  For establishing base – lines and ongoing
monitoring for deforestation, pollutant emissions,
spread of invasive species, climate change impacts
etc.
 Assisting in stratified random sampling strategies
for field inventories.
 In carbon sequestration monitoring (
aforestation/deforestation)
 In coral reef monitoring
 Oil spill verification

26.  To monitor marine protected areas
 Monitor desertification process
 To raise public awareness, e.g. Toms data on
ozone hole, receding glaciers and climate change
 It can bring people together across boundaries to
address common problems
 Powerful tool for international cooperation
 To detect changes in water and to test water quality

28.  In Air quality – remote sensing of particulate
aerosols in the atmosphere helps in this
 Conservation of endangered species
 To identify flood plains
 To update highly dynamic, rapidly changing coastal
environment
 In distinguishing landscape categories etc.

30. THANK YOU