Remote sensing can be used to study soils by analyzing parameters like surface color, temperature, moisture, vegetation indices, mineralogy, organic carbon, iron content, and salinity. High resolution DEM and imagery from sensors like LIDAR and SAR can be used to map landforms and classify soils. Traditional soil mapping is done at scales of 1:1 million to 1:50,000. Remote sensing allows soil mapping across large areas by analyzing the spectral response patterns influenced by soil properties.
2. SOIL : BASIS OF LIFE
Soil is of major importance to mankind
because if supports the plants & animals that
provide us with food ,shelter & clothing.
Different concepts of soils have been
developed by agriculturists and engineers.
3. SOIL : Agriculturist perspective
• Soil is a complex entity of minerals , water & air and
influenced by living things.
• To them , most of the soil profile is significant for plant
growth;
• the surface (A horizon) because it is the seat of
biological activity & principal source of nutrients.
• B horizon (subsoil) affects drainage, soil moisture
retension, aeration & root development of plants
• C horizon; because it may contain weatherable
minerals yielding nutrients & its texture may affect
permeability.
• D horizon;the deeper part of soil is generally of less
importance to plant growth.
4. SOIL:ENGINEER
PERSPECTIVE
• In engineer’s view ,soil merely in terms of
unconsolidated sediments & deposits of solid
particles derived from the disintegration of
rock.
• Soil comprised of 3 phased system in some
state of dynamic equilibrium, i.e,
Solid (particulate organic and inorganic
material)
Liquid (consisting of soil solution containing
various salts)
Gas (soil air)
5. Conventional Mapping of Soil
• Russian scientist ,Dokuchaiev, first explained the
relationship between soil profile & the
environment.
• Soil Series: A group of soils of similar profiles
derived from a particular parent material
• Soil phases: On the basis of any characteristic or
combination of characteristics potentially
significant to our use or management of soil
• Attributes : Slope ,degree of erosion, depth of
soil, stoniness ,salinity, physiographic position
6. Spatial Stratification of Landscape
• A common way of spatially segmenting the
landscape is to divide it into internally more or
less homogeneous & mutually contrasting land
form units
• For classical soil mapping,such as the SOTER
(Soil & Terrain) methodology,the classical maps
can be used to draw soil boundaries.
7. Landform Mapping
Traditionally,landform mapping is done by
visually interpreting aerial photographs.
It can be done by using digital sources like
DEMs(digital elevation models) acquired by
remote sensing.
Typically,the surface is parameterized by
attributes such as elevation,slope,profile
curavture and flow accumulation to obtain
surface topography units.
8. • 3 types of relief units are distinguished based
on decreasing complexity.
i. Firstly elementary forms (smallest and
simplest geometric units)
ii. Secondly, composite of elementary forms
iii. Thirdly, association of landforms
9. Land form mapping based on
combined data sources
• The combination of DEM with spectral data
can improve landform classification in
complex landscapes.
• Different landform models have been
developed for using spectral data in
combination with data from SRTM (Shuttle
Radar Topography Mission) and Landsat
Thematic Mapper.
10. Digital Elevation Model
• The most widely used sources of DEM data
are LIDAR (Light Detection Ranging) and SAR
(Synthetic Aperture Radar).
• Dependent on the sensor flight altitude ,
LIDAR allows highly accurate and very densely
sampled elevation points.
11. Soil Parameters Using for Remote
Sensing
• Surface colour
• Surface roughness
• Soil temperature
• Soil moisture
• Vegetation pattern & indices
• Mineralogy
• Soil Organic Carbon
• Iron content
• Soil salinity
• Lichens
• Non photosynthetic vegetation
12. SURFACE COLOUR
In remote sensing ,the surface colour affect
the percentage of isolation received at the
surface which is reflected back to space.
Dry Sandy Soil, Albedo=37%
Moist Black Soil, Albedo=8%
13. SURFACE ROUGHNESS
• Created by cultivation or inherent soil
structure
• Observation through scattering of incident
radiation
14. SOIL TEMPERTURE
• It can be detected by thermal sensors.
• Major factor affecting the temperature relation of
the soil is its Specific heat/Thermal capacity.
• Specific heat of soil: The amount of heat
required to raise the temperature of a given
substance from 15°C to 16°C compared with that
required for the same rise in temperature of an
equal weight of water.
• In field condition , the soil moisture content
determines its thermal capacity.
15. SOIL MOISTURE
• Obtained from Microwave RADAR
• Related with dielectric properties of water
• Dielectric constant of soil depends on the water
content of the soil
• 2 methods are used to measure the soil water
content.
1. Gravimetric method:- in terms of % of dry weight of
the solids forming soil
2. Volumetric method:- in terms of % of volume of the
soil
• Recent RS study on soil properties is based
upon the “available” water in the soil.
16. Vegetation Patterns and Indices
Spatial & temporal variation indices have been found
to be linked to prevailing climate,ecosystem,terrain and
physical soil properties.
The Normalized Difference Vegetation Index (NDVI) is
one of the most common indicators of crop growth
characteristics of specific site qualities.
E.g, root zone soil moisture,soil colour,soil
texture,water holding capacity,soil carbon and nitrogen
content
17. Mineralogy
• The analysis of mineralogy with spectral
proximal sensing has made great progress
over the last years.
• With remote sensing , mineralogy can be
determined from the spectral signature of
rock outcrops or from the mineral
composition of bare in-situ soils.
18. SOIL ORGANIC CARBON
• Most research on the determination of soil organic
carbon with remote sensing has been perform at plot
scale(<1 km²).
• When mapping SOC on a large scale without extensive
calibration,a solution could be to use indices based on
reflectance for quantifying soil organic carbon.
• The amount of SOC is then detected with reflectance
spectroscopy based on the constituents of SOC:
cellulose,starch,lignin.
• Good relations have been found for indices on the
visible part of spectrum.
19. IRON CONTENT
• Soil iron can be seen as an indicator of soil
fertility and the age of sediments.
• RS imagery has been used for determining the
presence of iron over areas upto 500km².
• Both soil color and absorption features have been
used to derive iron content.
• Iron oxides and Iron hydroxides have specific
absorption features that are located in the VNIR
(visible & near-infra red) & can be measured from
multispectral spectrometer images.
20. SOIL SALINITY
• In arid and semi-arid climates ,precipitaion is
insufficient to maintain a regular percolation
of rain water through the soil,so soluble salts
accumulate.
• Both RADAR and optical remote sensing
data have been used for mapping soil salinity.
• It is based on the dielectric properties of soil
as salinity is a key element of the electric
conductivity.
21. NON PHOTOSYNTHETIC
VEGETATION
• Non-photosynthetic vegetation(NPV) such as crop
residues,woody stems and forest litter influences
the spectral response of bare soil and thus the
accuracy of determined soil properties.
• In RS studies, The imaging spectrometer Cellulose
Absorption Index (CAI) and multispectral Lignin-
Cellulose Absorption (LCA) index are used to
estimate Crop residue cover.
22. LICHENS
• Exposed bedrock is often partly covered with
lichens varying in color ,from blackish brown to
orange.
• Lichens might prevent the transmission of light to
the underlying rock substrate and effectively
mask the mineral substrate.
• They may either influence or not influence the
spectral reflectance of a rock surface , depending
on the spectral contrast between the lichen and
the bare rock.
23. SOIL PROXIES
• The efficiency of using remote sensing to map soil
properties in densely vegetated areas depends on
indirect relations between vegetation and soil
attributes.
• To retrieve soil properties ,more detailed information
on the vegetation cover is needed.
• Two useful proxy indicators have been used to retreive
soil properties from RS data: Plant Functional Types
(PFT) & Ellenberg indicator values.
• PFT may be derived from high resolution imaging
spectrometer data on a plot level.
24. Applications
For survey of :
soil erosion
vegetation
agriculture
irrigation
forestry
drainage
Soil classification
25. Development of satellite remote
sensing on soil studies
• Before the launch of Landsat 1, aerial
photographs were being used for soil
mapping.
• In mid 80’s , high resolution Landsat TM & IRS
LISS 2 data enabled soil scientist to map soils
at 1:50,000 scale (district level).
26. Spectral behaviour of soil
• Spectral response pattern is generally
governed by numbers of factors ,i.e, different
soil properties.
• Chemical composition of soil influences
spectral signature of soils through the
absorption process.
27. Need & Scale of Soil Mapping
• Small scale maps of 1:1million = macro level
planning i.e, national level
• 1:250,000 scale = regional or state level for
several agricultural uses
• 1:50,000 scale= district level for planning
resource conservation & optimum land use
• 1:8000 /1:4000 scale = for specific purposes
(jhum lands, water logged areas)
28. Example
• In one of the major projects in Department of
space,Government of India – “integrated
Mission for Sustainable Development “ ,the
soil mapping has been taken up at 1:50,000
scale for about 175 districts in the country.
29. Soil Mapping Methods
• Aerial photographs provide info about
physiographic variations
• Methodology involves :
a. Visual interpretation based on size ,shape etc
comprises of 3 tier approach i.e,
interpretation of remote sensing
imagery/aerial photograph,field survey &
cartography
b. Computer aided approach