Remote sensing

1. Basic concept, components and
applications of Remote Sensing
Lec. 1-2
Dr. Sanjani S. Salunkhe,
Assistant Professor,
Dept. of Soil and Water Cons. Engg.,
Dr. D.Y.Patil CAET, Talsande

2. • Remote sensing is the science and art of obtaining
information about an object, area or phenomenon
through an analysis of the data acquired by a device
which is not in contact with the object, area or
phenomenon under investigation.
• Remote sensing data basically consists of wavelength
intensity information acquired by collecting the
electromagnetic radiation leaving the object at
specific wavelength and measuring its intensity.
WHAT IS REMOTE SENSING ?

3. Fig. Sensor on-board satellite scans along line AB

4. Components of Remote Sensing
1. Energy Source:
i. Passive System: Sun, irradiance from earth’s materials.
ii. Active System: Irradiance from artificially generated
energy sources such as radar.
2. Platforms: These are vehicles to carry the sensor e.g. truck,
aircraft, space shuttle, satellite, etc.

5. 2. Sensors: Device to detect electro-magnetic radiation e.g.
camera, scanner, etc.
3. Detectors: Handling signal data e.g. photographic, digital, etc.
4. Processing: Handling signal data e.g. photographic, digital etc.
5. Institutionalization: These are organizations for execution of
all stages of remote sensing technology e.g. International and
national organizations, research centres, universities, etc.

6. Elements Involved in Remote Sensing:
1. Energy Source or Illumination (A)
2. Radiation and the Atmosphere (B)
3. Interaction with the Object (C)
4. Recording of Energy by the Sensor (D)
5. Transmission, Reception and Processing (E)
6. Interpretation and Analysis (F)
7. Application (G)

7. • Types of sensing systems to record the information
about any target:
1. Active sensing system and
2. passive sensing system
Classification of Remote Sensing

9. Advantages of remotely sensed data
• Collection of data from both accessible and
inaccessible areas on a repetitive bais
• Quality, reliability and timeliness
• Remote sensors collected data, it can be used and
analysed multiple times for different applications.
• Remote sensing technology like LiDAR collects point
cloud data
• Large area coverage

10. • Remote sensing allows repetitive coverage which comes in
handy when collecting data on dynamic themes such as water,
agricultural fields and so on.
• A single image captured through remote sensing can be
analysed and interpreted for use in various applications and
purposes. There is no limitation on the extent of information
that can be gathered from a single remotely sensed image.
• Remote sensing is un-obstructive especially if the sensor is
passively recording the electromagnetic energy reflected from
or emitted by the phenomena of interest (passive remote
sensing does not disturb the object or the area of interest).

11. • Remote sensing allows for map revision at a small to medium
scale which makes it a bit cheaper and faster.
• Colour composite can be obtained or produced from three
separate band images which ensure the details of the area are
far much more defined than when only a single band image or
aerial photograph is being reproduced.
• It is easier to locate floods or forest fire that has spread over a
large region which makes it easier to plan a rescue mission
easily and fast.
• Remote sensing is a relatively cheap and constructive method
reconstructing a base map in the absence of detailed land
survey methods.

12. Disadvantages of remotely sensed data
• Remote sensing requires a special kind of training to analyse
the images.
• It is expensive to analyse repetitive photographs if there is
need to analyse different aspects of the photography features.
• The instruments used in remote sensing may sometimes be
un-calibrated which may lead to un-calibrated remote sensing
data.
• Sometimes different phenomena being analysed may look the
same during measurement which may lead to classification
error.

13. Uses of RS techniques in assessment and
monitoring of land and water resources
• Assessment of water availability in reservoirs for optimal
management of water to meet irrigation demand.
• Identifying, inventoryingand assessment ofirrigated crops.
• Determination of irrigation water demands over space and
time.
• Estimation of crop yields.
• Water logging and salinity problems in irrigatedlands.

14. • Evapotranspiration studies.
• Irrigation system performance evaluation.
• Satellite remote sensing derived indicators such as
chlorophyll, can monitor that algal bloom thus monitoring
water quality in a spatio-temporal fashion.
• Surface Water Quantity: One of the key argument is the
lack of the ground data, which plays an important role in
evaluating the status of water resource and taking useful
measures to respond the threat of water scarcity. In this
regard, earth observation can offers standardized and
long-term observations to address such challenges.

15. • The RS has capability of multi-temporal imaging and satellite
imagery based indices (i.e., Normalized Difference Water
Index (NDWI)), can efficiently identify, map and calculate the
total surface area of the water bodies in different seasons
(i.e., dry, wet) and by integrating satellite altimetry
measurements which quantify and monitor the water storage
change over time.
• Ground water Quantity: For planning and management of
water resource, need to know, globally how much fresh
water available. Gravity Recovery and Climate Experiment
(GRACE), continuously measuring the changes in earth’s mass
hence gravity that are mainly due to water moving on and
under the surface.

16. WATER RESOURCES MANAGEMENT
• Runoff and Hydrological Modelling: Remote Sensing
techniques, they can be used in research areas like
- determining watershed geometry, drainage network
and other map-type information for distributed
hydrologic models and for determining empirical flood
peak, annual runoff or low flow equations and
- providing input data like soil moisture or delineated
land use classes, which are used for determining runoff
co-efficient.

17. • Remotely sensed data, particularly Landsat, Thematic Mapper
(TM), SPOT), and Indian Remote Sensing Satellite (IRS) data
has been used for calculation of drainage basin area and
stream network density.
• Hydrologic Engineering Center (HEC-1) model was used to
demonstrate the efficacy of using Remote Sensing for re-
computation of hydrologic variables. HEC-1 model was used in
integrating detailed land use data from Landsat TM.

18. • Flood Management:
• Information acquired through Remote Sensing covers wide
area, periodicity and spectral characteristics and is especially
useful in comparing data before and after the flood.
• The utility of satellite Remote Sensing has been demonstrated
operationally for mapping flood inundated areas.
• Partially cloud free data acquired, analysed and interpreted in
near real time by IRS series satellites.
• IRS-1C, IRS-1D, IRS-P6, Cartosat-1, Cartosat-2, Radarsat and
Earth Resource Satellite (ERS) are used for flood inundation
mapping, estimation of flood damage and infrastructure loss.

19. • Watershed Management:
• Space borne multi spectral data has been used to generate
baseline information on various natural resources like soil,
forest cover, surface water, groundwater and land use/land
cover.
• Subsequent integration of such information with slope and
socio-economic data in a GIS has resulted in generation of
location specific management plan for sustainable
development of land and water resources within a watershed.

20. • Drought Management:
• Timely and reliable information about the onset of drought,
its extent, intensity, duration and impact can limit drought
related loss of life, minimize human suffering and reduce
damage to the economy and environment.
• Remote Sensing data from geostationary and polar orbiting
weather satellites like Indian National Satellite (INSAT),
National Oceanic and Atmospheric Administration (NOAA)
and other global data are used as major inputs in rainfall
predictions ranging from long-term seasonal predictions
through medium range predictions to short-term predictions.

21. • Irrigation Command Area Management:
• Remote Sensing techniques can be immensely helpful in
inventory of irrigated land, identification of crop types, crop
extent, crop condition and estimation of crop yield, as
demonstrated in various investigations in India and in other
countries.
• Periodic satellite monitoring of Irrigation Command Areas has
helped in evaluating increase in irrigation utilization and
improvement in agricultural productivity over a period of time.

22. • Remote Sensing methods have been successfully applied in
delineating saline and alkaline soils and detecting areas having
ineffective water management practices leading to decrease in
crop yield.
• Remote Sensing techniques are now increasingly applied in
land use planning and in identifying areas suitable for sustained
irrigated cropping with the help of “irrigability maps” prepared
from satellite data.
• Vegetation Indices and demand-supply analysis is used in many
Irrigation Command Areas in India to evaluate irrigation
potential.

23. Thank You