Remote sensing and agriculture

1. Application of Remote sensing, GIS and GPS in
Agriculture
Submitted by
Vajinder Pal Kalra
Ph.d Student

2. What is remote sensing?
 “Remote” means away
 Remote sensing means sensing
things from a distance. Of our five
senses we use 3 as a remote sensors.
a) Watch a football game from a
distance (sense of sight)
b) Smell fleshy baked bread from the
oven (sense of smell)
c) Hear a telephone ring (sense of
hearing)
Aggarwal (2003)

3. Remote sensing is science of
 acquiring,
 processing, and
 interpreting
images and related data that are obtained from ground based, air-
or space-borne instruments that record the interaction between
matter (target) and electromagnetic radiation.
 Remote Sensing using the electromagnetic spectrum to image
the land, ocean, and atmosphere.
Campbell (1987)

4. Remote sensing platforms
Ground-based Airplane-based Satellite-based

5. Satellite Characteristics: Orbits and
Swaths
The path followed by a satellite
is referred to as its orbit.
As a satellite revolves around
the Earth, the sensor "sees" a
certain portion of the Earth's
surface.
The area imaged on the surface,
is referred to as the swath.
Swath
Orbit

6. Satellite based
1. Sun-synchronous polar orbits
 Most earth imaging satellites is
polar-orbiting, meaning that they
circle the planet in a roughly north-
south ellipse while the earth
revolves beneath them.
 They cover each area of the
world at a constant local time of
day called local sun time.
 Typical altitude 500-1,500 km

7. 2. Non-Sun-synchronous
orbits
 Tropics, mid-latitudes, or
high latitude coverage,
varying sampling
 typical altitude 200-2,000
km
 example: TRMM

8. 3. Geostationary orbits
Satellites at very high altitudes,
at approximately 36,000
kilometres ,which view the same
portion of the earth's surface at
all times.
Revolve at speeds which match
the rotation of the earth so they
seem stationary
 Weather and communications
satellites

9. Types of remote sensing
 Passive remote sensing
systems which measure energy
that is naturally available. For
example : Sun
 This can only take place during
the time when the sun is
illuminating the Earth.

10.  Active: provide their own energy
source for illumination.
 The sensor emits radiation which is
directed toward the target to be
investigated.
 The radiation reflected from that
target is detected and measured by the
sensor.
 They obtain measurements anytime,
regardless of the time of day or
season.
 LASER, RADAR

11. Process of Remote Sensing
(A) Energy source or illumination
(B) Radiation and the atmosphere
(C) Interaction with the target
(D) Recording of energy by the
sensor
(E) Transmission, reception, and
processing
(F) Interpretation and analysis
(G) Application

12. Radiation - Target Interactions
There are three (3) forms of
interaction that can take place
when energy strikes, or is
incident (I) upon the surface.
1. Absorption (A)
2. Transmission (T)
3. Reflection (R)
 Specular reflection
 Diffuse reflection

13. Specular reflection

14. Diffuse Reflection

15. Four types of resolution
Resolution
Radiometric
Spectral
Temporal
Spatial

16. Spatial resolution
It refers to the size of the smallest
possible feature that can be detected.
It depends upon the Instantaneous
field-of-view (IFOV) which is the
angular cone of visibility of the
sensor.
Images are composed of a matrix of
picture elements, or pixels, which are
the smallest units of an image.

17. Spectral resolution
 Spectral resolution describes the
ability of a sensor to define fine
wavelength intervals.
 The finer the spectral resolution,
the narrower the wavelength range
for a particular channel or band.

18. Radiometric resolution
Sensor’s sensitivity to the magnitude
of the electromagnetic energy.
Sensor’s ability to discriminate very
slight differences in (reflected or
emitted) energy in form of bits.
The finer the radiometric resolution
of a sensor, the more sensitive it is to
detecting small differences in energy.

19. Basics of Bit
Computer store everything in 0 or 1. Each bit records an exponent of
power 2.
For example: 8 bits bits Max num
2 n
1 2
2 4
3 8
6 64
8 256
11 2048
12 4096
Coverage: 0 -4095Resolution: 12 bits

20. Temporal resolution
 It is the revisit period, and is the
length of time for a satellite to
complete one entire orbit cycle,
i.e. start and back to the exact
same area at the same viewing
angle.
 For example, Landsat needs 16
days, MODIS needs one day,
NEXRAD needs 6 minutes.

21. Image Interpretation
Image is a pictorial representation of an object or a scene.
Image can be
 Analog image
 Digital image
Lillesand and Keifer (1994)

22. Analog image
 Produced by photographic
sensors on paper based media or
transparent media
 Variations in scene characteristics
are represented as variations in
brightness ( gray shades)
 Objects reflecting more energy
appear brighter on the image and
objects reflecting less energy
appear darker.

23. Digital image
 A digital image is made up of square
or rectangular areas called pixels.
 Each pixel has an associated pixel
value known as Digital Number (DN)
or Brightness value (BV) or gray level
which depends on the amount
reflected energy from the ground.
 An object reflecting more energy
records a higher digital number for
itself on the digital image and vice
versa.
DN value

24. Analysis of remote sensing imagery involves the identification of
various targets in an image.
 Those targets may be environmental or artificial features, which
consist of points, lines, or areas.
Targets may be defined in terms of the way they reflect or emit
radiation.
This radiation is measured and recorded by a sensor, and
ultimately is depicted as an image product such as an air photo or
a satellite image by comparing different targets based on any, or
all, of the visual elements of tone, shape, size, pattern, texture,
shadow, and association.

25. Tone
 Tone refers to the relative
brightness or colour of
objects in an image.

26. Shape
 Shape refers to the general form, structure,
or outline of individual objects.
 Shape can be a very distinctive clue for
interpretation.
 Straight edge shapes typically represent
urban or agricultural (field) targets, while
natural features, such as forest edges, are
generally more irregular in shape.
 Farm or crop land irrigated by rotating
sprinkler systems would appear as circular
shapes

27. Size
 Size of objects in an image is a
function of scale.
If an interpreter had to distinguish
zones of land use, and had
identified an area with a number of
buildings in it.
 Large buildings such as factories
or warehouses would suggest
commercial property, whereas
small buildings would indicate
residential use.

28. Pattern
Pattern refers to an orderly
repetition of similar tones and
textures will produce a
distinctive and ultimately
recognizable pattern.
Orchards with evenly spaced
trees, and urban streets with
regularly spaced houses are
good examples of pattern.

29. Texture
Texture refers to the arrangement
and frequency of tonal variation in
particular areas of an image.
Smooth textures are most often the
result of uniform, even surfaces,
such as fields, asphalt, or
grasslands.
 Rough textured represent
irregular structure, such as a forest
canopy.

30. Shadow
Shadow may provide relative
height of a target.
 Shadows can also reduce or
eliminate interpretation in
their area of influence, since
targets within shadows are
much less (or not at all)
discernible from their
surroundings.

31. Association
Association takes into account the
relationship between other
recognizable objects or features in
proximity to the target of interest.
Commercial properties may be
associated with proximity to
major transportation routes.
 Residential areas would be
associated with schools,
playgrounds, and sports fields.

32. What is spectral reflectance curve?
 A graph of the spectral reflectance of an object as a function of
wavelength.
 It is very useful for choosing the wavelength regions for remotely
sensed data acquisition for a certain application.

33. Spectral signatures
A signature is that which gives an information about an object
to its identity.
Identity is whatever makes an entity recognizable.

34. Spectral signature for vegetation
A general characteristic of vegetation is its green colour
caused by the pigment chlorophyll.
 Chlorophyll reflects green energy more than red and blue
energy, which gives plants green colour.

36. The major difference in leaf reflectance between species, are
dependent upon leaf thickness.
Thick leaf Thin leaf

37. Needle-leaf trees canopies reflect significantly less near-
infrared radiation compared to broad-leaf vegetation.
Coniferous forest Deciduous forest

38. Immature leaves contain less chlorophyll than older leaves,
they reflect more visible light and less infrared radiation.
Mature plant Immature plant

39.  Reflectance is also affected by health of vegetation.

40. Vegetation indices
Normalized Difference Vegetation Index (NDVI)
This index is the ratio of the difference of the near-infrared and
red reflectance, over the sum of those.
[NDVI = (NIR - Red) / (NIR + Red)]
It receives values from -1 (no vegetation) to +1 (abundant
vegetation).

41. Normalised Difference Water Index
 It employs the near-infrared band and a band in the short-
wave infrared (SWIR)
Instead of using the red band, a short-wave infrared band
in the region between 1500 and 1750 nm is used where
water has high absorption.
[ NDWI = (NIR - SWIR) / (NIR + SWIR) ]

42. Spectral Signature for Soil
 The five characteristics of a soil that determine its
reflectance properties are, in order of importance:
 Moisture content
 Organic content
 Structure
 Iron oxide content
 Texture

43. Soil moisture content
A wet soil generally appears darker.
 Increasing soil moisture content lowers reflectance.
Dry soil Wet soil

44. Soil organic matter
 A soil with 5% or more organic
matter usually appears black in color.
 Less decomposed organic materials
have higher reflectance and vice
versa.
A B C

45. Soil iron content
The presence of iron
especially as iron oxide
affects the spectral
reflectance.
 Reflectance in the green
region decreases with
increased iron content, but
increases in the red region.
(a) High organic content, moderately fine
texture
(b) Low organic, Low iron content
(c) Low organic, medium iron content
(d) High organic content, moderately coarse
texture
(e) High iron content, fine texture
b c d
e a

46. Soil structure
 A clay soil tends to have a strong
structure, which leads to a rough
surface on ploughing.
 Clay soils also tend to have high
moisture content and as a result
have a fairly low diffuse reflectance.
 Sandy soils also tend to have a low
moisture content and a result have
fairly high and often specular
reflectance properties.

47. Spectral signature for water
Reflection of Light – Wavelengths
 Water Depths – Shallow , Deep
Suspended material
Chlorophyll Content
Surface Roughness

48.  The majority of radiant flux incident
upon water is either not reflected but
is either absorbed or transmitted.
 In visible wavelengths of EMR,
little light is absorbed, a small
amount, usually below 5% is
reflected and the rest is transmitted.
 Water absorbs NIR and MIR
strongly leaving little radiation to be
either reflected or transmitted. This
results in sharp contrast between
any water and land boundaries.

49. Spectral Reflectance of Snow
 Factors governing are
 Snow pack thickness:
Reflectance of snow decreases as
it ages.
 Liquid water content: Even
slightly melting snow reduces
reflectance .
 Contaminant present:
Contaminations (soot, particles,
etc.) reduce snow reflectance.

50. Remote sensing applications in
agriculture
 Agricultural products from crops form a large part of every person´s diet.
Producing food of sufficient quantity and quality is essential for the well-being
of the people anywhere in the world.
 Plants require water and nutrients in order to grow and are sensitive to extreme
weather phenomena, diseases and pests.
 Remote sensing can provide data that help identify and monitor crops.
 When these data are organized in a Geographical Information System along
with other types of data, they become an important tool that helps in making
decisions about crops and agricultural strategies.
Jones and Vaughan (2010)

51. National governments can use remote sensing data, in order to make
important decisions about the policies they will adopt, or how to
tackle national issues regarding agriculture.
 Individual farmers can also receive useful information from remote
sensing images, when dealing with their individual crops, about their
health status and how to deal with any problems.
India has its own satellites like Indian Remote Sensing Satellite
(IRS) series - Resourcesat, Cartosat, Oceansat etc which provide
required data for carrying out various projects.
Jones and Vaughan (2010)

52. Monitoring of crop status
The normal growth process of a plant can be disrupted when it goes
through a stress period.
When in stress, the plant is not functioning properly because of one
or more causes.
When a plant is stressed, it usually expresses certain visible
symptoms, but also some that are not visible to the human eye.
Stress symptoms may appear in all of the plants of the field or in
some portions of the field, depending on the cause.
Premalatha and Nageshwara (1994)

53. Chlorosis Development of a fungus
Insect attack

54. Water content of field crops
Water content of crop fields with thermal imaging.
Isdo et al (1977)

55. Combating disease and pests
Identifying the most probable areas where insects might attack.
Fitzgerald et al (1999)

56. Estimate the loss of leaf area to study the damage caused by
caterpiller on leaf
Rouse et al (2000)

57. Crop yield estimation
May 2005
Shanahan et al (2001)
August 2005

58. Crop yield forecasting
 In order to make estimates on future crop yield with remote sensing data alone, we need to
know the relationship between vegetation indices at a particular growth stage of the crop
and the final crop yield.
 Historical data of previous growth seasons, serve this purpose, and the accuracy of the
crop yield prediction increases as the amount of historical data increase.
 However, no two growth seasons are the same. In order to make more accurate
predictions, it is essential to consider the factors that affect crop growth and yield in the
current year.
 Information such as meteorological and climatic data, soil properties and farming
practices are combined with the up-to-date remotely sensed data, in order to model the
crop growth and make estimates on the final crop yield.
Parihar and Nageswara (1997)

59. Crop identification
 It is very important for a national government to know what crops
the country is going to produce in the current growing season.
This knowledge has financial benefits for the country, as it allows the
budget planning for importing and exporting of food products.
 One method is for someone to travel around the country and see
what crop is grown in each field. But this takes too much time and
costs a lot of money.
Bauer (1985)

60.  By using multi-date data (data from different dates) from one
growing period, it is possible to identify the different crop
types, because the vegetation cover of each crop changes at
different rates.
 In addition, the planting and harvesting dates are also different.
 By combining this information with remote sensing data, we
can discriminate between different crops and also identify them.
Bauer (1985)

61. Image classification showing the various crop types.
Source: U.S. Geological Survey

62. GPS is short for Global Positioning System
which is "a network of satellites that
continuously transmit coded information,
which makes it possible to precisely identify
locations on earth by measuring distance from
the satellites".
GIS is short for Geographic Information
System(s). "In the strictest sense, a GIS is a
computer system capable of assembling, storing,
manipulating, and displaying geographically
referenced information , i.e. data identified
according to their locations. Practitioners also
regard the total GIS as including operating
personnel and the data that go into the system“.
GPS and GIS

63. Examples of GPS and GIS:
Global Positioning System (GPS):
An agricultural producer may use a handheld
GPS receiver to determine the latitude and
longitude coordinates of a water source next to
a field or vineyard.
Global Information System (GIS): Following
a chemical spill, maps obtained from a GIS
system can reveal environmentally-sensitive
areas that should be protected during response
and recovery phases.
Source: Purdue University

64. GPS data gathering
Depending on the make and model of
the unit, the number of satellites
available, and the quality of
(unobstructed) signals, GPS receivers
can collect information such as
 Latitude and longitude coordinates
(time-in-place or point location)
 “Real Time” position
(calculated while farm equipment is
moving)
 Elevation (if 4 or more satellites are
used)

65. YOUR CURRENT POSITION
COORDINATES (Latitude & Longitude, Utm, Mgrs etc.)
ELEVATION (Approximate)
DIRECTION TO SPECIFIED WAYPOINTS (“Markers”)
(or Between Waypoints)
DISTANCE TO SPECIFIED WAYPOINTS
(or Between Waypoints)
YOUR SPEED OF TRAVEL
YOUR DIRECTION OF TRAVEL
BASIC INFORMATION PROVIDED BY GPS
RECEIVERS . . .

66. With GIS software, information from a GPS
unit may be combined with data such as
• USGS topographical maps
• Digital elevation models
• Critical infrastructure maps
• Aerial photography
• Cropland use
• Census maps
The Result:
“Layered” maps can be generated by
the GIS software.

67. Example of Map “Layers”
A GIS database creates “layers” with
many pieces of information visualized
for the same area.
Yield data – collected using GPS
Topsoil Depth - collected using GPS
Aerial photo of the area
Source: University of Missouri

68. GPS – How it works
1. Constellation of more than 24 satellites
Known positions (at any time)
Each continuously transmits time and position data between
two frequencies (L1-1575.42MHz and L2-1227.6MHz)
Each orbits twice per day
2. Ground receiver (Your GPS receiver)
 Calculates Position and Time
 Times signal and calculates distance to each satellite
received
 Triangulates Latitude and Longitude
 Calculates time
 Must see a minimum of 4 satellites68 of 10

69. GPS & GIS Communication and Control

70. Different GPS Types
1. Hand Held
2. Backpack
3. Vehicle Mounted

71. GPS Antenna
attached on the
combine
GPS Mounted Over Combine Harvester

72. Commercially Available GPS
Garmin Trimble

73. GPS/GIS Applications in Agriculture
Guidance
 Point Guidance
 Swath Guidance
Control
 Variable rate application
 Variable depth tillage
 Variable irrigation
 Mapping
Soil properties
Chemical application
Chemical prescriptions
Tillage Maps
Yield Mapping
Pest Mapping
Topographic Maps
Planting Maps

74. Field Mapping
Position data (georeference data) recorded at predetermined
intervals.
Other data recorded manually or automatically by monitor,
computer, or data logger.
Data displayed by geographic information system (GIS) in
thematic map format.

75. Soil Sampling
Georeferenced soil samples can be collected
Sampling Methods
Grid sampling: intensive sampling of entire
field
Directed sampling: intensive sampling of
particular target areas

76. Semi-Automatic Soil Sampler

77. Yield Maps
Record of spatial yield
variability within a field or
farm.
GPS data coupled with yield
data to produce map.
Mechanically harvested
Hand harvested
Useful tool for decision
making.

78. Field Scouting
 Fields can be scouted for a variety of pests
 Pest populations recorded on maps
 Decision tools can be applied on a site specific basis

79. Variable Rate Control
 Application rates designed for needs of small sections of a field
 GPS determines position of equipment in the field
 Computer controls use GPS data and prescription files to adjust rate

80. Precision Agriculture
 It is a collection of agricultural
practices that focus on specific areas
of the field at a particular moment in
time.
 This is opposed to more traditional
practices where the various crop
treatments, such as irrigation,
application of fertilizers, pesticides
and herbicides were evenly applied to
the entire field, ignoring any
variability within the field.
Agricultural tractor used in precision
agriculture.
Source: Agricultural Research Service,
USDA

81. Advances in remote sensing technology and the reduced cost of
sensors is now allowing for the more widespread use of such
equipment in farming.
With the use of these sensors it is possible to identify which
particular areas of the field are in need of which treatment, and
focus the application of chemicals to these particular locations
alone.
 Reducing the amount of chemicals used, and thus the cost of
the application, as well as protecting the environment.

82. Soil test of phosphorus, potassium and pH for a central Missouri (USA)
farm. (Blue to red is low to high for the concentrations)
Davis et al (1998)

83. Adjustment of ultra-low volume herbicide applicators. With this method the use
of chemicals in agriculture is greatly reduced.
Source: Keith Weller, USDAAgricultural Research Service

84.  By using remote sensing and
GPS, it is possible to identify
the exact location where the
application of fertilizers or
pesticides is required.
The Variable Rate Treatment
(VRT) is a system that
regulates the rate of pesticides
or fertilisers, releasing only the
required amount over the areas
or the field that are in need of
the chemicals.
Sensors (top) and variable-rate applicators
(bottom) on a combine.
Variable rate treatment
Source: Oklahoma State University

86. Experimental Setup for Paddy field Preparation
using nine tyne Cultivator
Trial parameters Without
Navigator
With Navigator
Area to be cultivated 55x36.4m=0.20ha 55x36.4m=0.20ha
Location of research
plot
Latitude :
30.9084640
Longitude:
75.8173750
Latitude :
30.9084890
Longitude: 75.8175660
Total width of machine
(m)
2.6 2.6
Position of GPS
antenna from cultivator
1.7m Front 1.7m Front
Visibility of navigator
screen to operator
Not visible Visible

87. Missed area During Operation of Cultivator
Without Navigator
(0.001+0.002+0.004+0.005+0.004
+0.009+0.012+0.001+0.001+0.001+ 0.007=0.047ha)
With Navigator
(0.001+0.001+0.003+0.001+
0.002+0.001+0.001+0.004+
0.001+0.001+0.001=0.017ha)

88. Overlapped Area During Operation of
Cultivator
Without Navigator
(0.004+0.004+0.005+0.001+0.006 +
0.003+0.003+0.002+0.006+0.008
=0.042)
With Navigator
(0.001+0.001+0.002+0.001+ 0.001=0.006)

89. Summarized Data During Operation of Cultivator
Simplified
parameters
Without Navigator With Navigator
Area to be cultivated 55x36.4m=0.20ha 55x36.4m=0.20ha
Location of research
plot
-Latitude : 30.9084640
-Longitude: 75.8173750
-Latitude : 30.9084890
-Longitude: 75.8175660
Calculated area 0.11 ha 0.19ha
Perimeter - 175m
Productivity 0.35 ha/h 0.55ha/h
Total area cultivated 0.29ha 0.20ha
Uncovered/missing
area of the field
0.001+0.002+0.004+0.005
+0.004
+0.009+0.012+0.001+
0.001+0.001
0.001+0.001+0.003+0.001+
0.002+0.001+ 0.001+0.004+
0.001+0.001+0.001
= 0.017

90. Summarized Data During Operation of Cultivator
Simplified
parameters
Without Navigator With Navigator
Total overlapped
area
0.004+0.004+0.005+0.001
+0.006 +
0.003+0.003+0.002+0.006
+0.008
=0.042
0.001+0.001+0.002+0.001+ 0.001
=0.006
Out of Boundary
area
cultivated/covered
0.001+0.001+0.001+0.001+
0.001
+0.001=0.006
0.002+0.001+0.001+0.001+
0.002+0.001+0.001=0.009
Total un-useful
cultivated area
(overlapped +
unnecessary area
cultivated)
0.048ha 0.015ha
Effective area 0.111ha 0.185ha

91. Fertilizer spreader
GPS
Antenna
Electrical
connections from
12V dc battery
Setting
chart for
spreader
Spreader
setting
machine
Experimental Setup for Urea Spreading using
Fertilizer Spreader

92. Missed/Uncovered Area During Urea
Fertilization
Without Navigator
(0.003+0.001+0.002+0.141=0.147ha)
With Navigator
(0.001+0.004+0.002+0.010+0.003
+ 0.008+0.012= 0.067ha )

93. Satellite Navigator
GPS Antenna fitted
on hood
Zero till drill
settingTractor attached
with zero till drill
Experimental
Setup During
Zero Till Drill
Operation

94. Overlapping During Zero Till Drilling with
Navigator

95. Zero Till Drilling Without Navigator

96. Real Time Kinematic Positioning System

97. RTK —How does it work?
1.Base station transmits corrections via radio to the mobile
receivers in the field
2.RTK base stations transmit data once per second
3.Data in format called CMR (Compact Measurement
Record)
4.Dual frequency data format transmits data in a more
compact and robust way than other formats

98. Conclusion
 Remote sensing technology can be used to assess various abiotic and biotic
stresses in different crop.
 The remote sensing plays an important role in detecting and management of
various crop issues even at a small land holding with high resolution.
 The discrimination can be made between different crops based on the
reflectance characteristics for different policy making decisions
 Crop yield forecast is also an important factor in decision making and
therefore can accomplished by ground and satellite based remote sensing.
 By using the microwave remote sensing, studies related with the nutrient and
moisture assessment can be under taken on temporal and spatial scales.