Remote sensing uses satellite or aircraft sensors to monitor the environment without direct contact. It can monitor soil, water, and air pollution over large areas in a timely manner. Satellite imagery is used to monitor air quality by detecting pollutants and aerosols. Water quality is monitored by measuring changes in the spectral signature of surface water caused by substances like sediments, algae, and thermal releases. Remote sensing provides synoptic views of large areas but has limitations like spectral interference and inability to distinguish low concentrations of pollutants. It is a useful tool for environmental monitoring when used in conjunction with field data.

1. REMOTE SENSING APPLICATION IN MONITORING AND
MANAGEMENT OF
SOIL, WATER AND AIR POLLUTION
Soil 509: Soil, Water and Air pollution
Submittedto:-
Dr. Dileep Kumar
Assistant Research Scientist
AICRP on Micronutrient
Submittedby:-
Jayvirsinh P. Solanki
Ph. D (First Sem.)
Agricultural Microbiology
Reg. no. 1010113084

2. REMOTE SENSING
• The acquisition of information about an object or phenomenon without making physical
contact with the object and thus in contrast to on-site observation, especially the Earth.
• In current usage, the term "remote sensing" generally refers to the use of satellite or
aircraft-based sensor technologies to detect and classify objects on Earth, including on
the surface and in the atmosphere and oceans, based on propagated signals (e.g.
electromagnetic radiation).
• It may be split into "active" remote sensing (i.e., when a signal is emitted by a
satellite or aircraft and its reflection is detected by the sensor) and "passive" remote
sensing (i.e., when the reflection of sunlight is detected by the sensor).

3. MONITORING
Environmental monitoring can be defined as the systematic sampling of air, water, soil
and biota in order to observe and study the environment, as well as to derive knowledge from this
process.
Gaining information about the present levels of harmful / potentially harmful pollutants in
discharges to the environment
Objectives:
• Carried out to assess pollution effects
• To evaluate pollution interactions and patterns
• To assess the need for legislative controls
• To ensure compliance with emission standards

4. TYPES OF MONITORING
1. Source monitoring
2. Ambient environment monitoring
• Air pollution monitoring
• Water pollution monitoring
• Sediment, soil and biological monitoring
• Noise level monitoring

5. SATELLITE BASED ENVIRONMENT MONITORING AREAS
• Atmosphere monitoring
• Air quality monitoring
• Climate change studies
• Resource management
• Landuse / Landcover
• Hazard monitoring
• Marine & Phytoplankton studies
• Dust storm

6. SATELLITE IMAGERY IN MONITORING AIR QUALITY
• Provides complete and synoptic views of large areas in one image on a systematic basis due
to the good temporal resolution
• Monitor many pollutants simultaneously
• Capability to monitor in near real-time and provides continuously rapid monitoring
Sensors used in mapping air pollution are:
• 1. Landsat TM/ETM+
• 2. MODIS AOT
• 3. ASTER data

7. TYPES OF MONITORING TECHNIQUES USED TO MAP AIR
POLLUTANTS
 Aerosol
 Aerosol thickness is
monitored by four different
methods
• Ocean method
• Brightness method
• Contrast-reduction
method
• Dark vegetation method

8. REMOTE SENSING FOR WATER RESOURCES AND POLLUTION
• Snow and Glacier mapping and
monitoring
• Irrigation water management
• Flood disaster monitoring, forecasting
and management
• Water quality monitoring
• Watershed management
• Groundwater prospecting
• Environmental Impact assessment

9.  Substances [Suspended sediments, algae, dissolved organic matter
(DOM), oils, aquatic vascular plants, and thermal releases] in surface water
can significantly change the backscattering characteristics of surface water.
 Remote sensing techniques depend on the ability to measure these
changes in the spectral signature backscattered from water and relate
these measured changes by empirical or analytical models to a water
quality parameter.

10. ADVANTAGES OF REMOTE SENSING
• Provides complete and synoptic views of large areas in one image on a systematic basis
• Can monitor many pollutants simultaneously
• Reduces the labour work and time in mapping large areas
• reduced fieldwork to a considerable extent
• Soil boundaries are more precisely delineated than in conventional methods.
• While mapping the soil using RS, the stereo data is highly useful in identification of different landforms, which have got
close relationship with soils associated with them.
• The assessment of the levels of heavy metal pollution of soils by collation of multi-spectral imagery and geochemical
data.
• As a result, direct and reversible correlation links were revealed between absolute total contents of heavy metals (Pb,
Cr, Ti, Cu, Zn,Mn) and spectral values of soils on the satellite and spectrophotometric images, which can serve as a
background for qualitative assessment of heavy metal contents in soils and creation of a remote monitoring system.

11. LIMITATIONS OF REMOTE SENSING
• Spectral confusions (i.e., impure pixels) from simultaneous detection of reflectance signals
at the sensors, (One of the major limitations is spectral interference caused by other
atmospheric inhabitances that are not pollution)
• Difficulty in distinguishing plant species,
• Scaling issues, Any pollutant with a low concentration will not be detected
• Low accuracy due to soil and water heterogeneity (e.g., spectral complexities of incomplete
plant cover)
• Absence of long-term satellite data (e.g., Landsat satellite data were available from only
1972 and MODIS from 2000).
• Models may be too simplistic or incomplete (e.g., omit soil depth variability or assume one
type of soil everywhere), because the model design and functionality depend on the
professional background of the model developer. Requires highly qualified staff, and the
process is very expensive

12. • The misuse of Predotransfer Functions (PTFs) in deriving soil physicochemical properties (e.g.,
bulk density, texture, soil moisture content, available water capacity, SOC, etc.) may generate
erroneous results.
• Soil characteristics (e.g., bulk density and texture) which are crucial for assessing soil quality are
difficult to assess using only remote sensing data.
• Some workers report a high correlation between SOC concentration and spectral reflectance
under controlled laboratory conditions, however, from aerial- or space- based platforms the lower
SNR attributed to atmospheric scattering, bi-directional reflectance, adjacency effects,
topographic variation, and geometric and radiometric errors may lower this accuracy.
• Variability in composition or concentration of heterogeneous mixtures of soil or water (i.e., SOC,
FeO3), soil moisture, mineralogy, and chlorophyll) may significantly influence the characteristics of
the reflectance signal detected by the sensor. Deciphering information from remote sensors is
difficult within heterogeneous landscapes.