seminar on application of remote sensing, GIS and GPS in agriculture

1. CREDIT SEMINAR
ON
APPLICATION OF REMOTE SENSING, GIS AND
GPS IN AGRICULTURE
SEMINAR INCHARGE
Dr. V. Nepalia
Professor & Head
Dept. of Agronomy
RCA, Udaipur
SPEAKER
Mohammed Mohsin
Ph.D. Scholar
Dept. of Agronomy
RCA, Udaipur
MAJOR ADVISOR
Dr. J. Choudhary
Assistant Professor
Dept. of Agronomy
RCA, Udaipur

2. Outlines
Introduction
Remote sensing
GIS
GPS
Application in agriculture
Conclusion

3.  In the late 1800s, camera were positioned above the earth surface in
balloon or kites to take oblique aerial photograph of the landscape.
 During world war I, aerial photography played an important role in
gathering information about the position and movement of enemy
troops.
 After the war, civilian use of aerial photography from airplanes began
with the systematic vertical imaging.
 In 1962 world first true operational GIS was developed in canada as a
name Canada Geographic Information System (CGIS).
 Tomlinson, who developed CGIS, is known as “Father of GIS”.
 GPS is a satellite based navigation system made up of a network of 24
satellite placed into orbit by the U. S. department of defense.
 GPS was originally intended for military applications, but in the 1980s,
the government made the system available for civilian use.
Introduction

4. What is Remote Sensing?
Remote sensing can be defined as the collection of data
about an object from a distance without coming in
contact with them.

5. Need of Remote Sensing?
 Systematic data collection
 Information about three dimensions of real objects
 Repeatability
 Global coverage
 The only solution sometimes for the otherwise inaccessible
areas
 Multipurpose information

6. Electromagnetic Spectrum

7. Satellite Orbits
Near Polar Orbits Geostationary Orbits

8. Remote Sensing Process

9. Spectral Signature
 Spectral signature is the variation of reflectance or emittance of
a material with respect to wavelengths .
 Different objects based on their structural, physical and
chemical properties reflect or emit different amount of energy in
different wave length range of the E.M.S
 The sensors measure the amount of energy reflected from that
object.

10. Spectral Reflectance Curve of Soil, Water and Vegetation

11. What is GIS?
 Geographic Information System
 System that captures, store, analyzes, manages and presents
data that are linked to location.
 Technically, a GIS is a system that include mapping software
and its application to remote sensing, land surveying, aerial
photography, mathematics and tools that can be implemented
with GIS software.

14.  GPS is a satellite based navigation system made up of a network of 24
satellite.
 The GPS system has three major segments
I. Space segment
II. Control segment
III. User segment

15.  GPS receiver compares the time a signal was transmitted by a satellite with
the time it was received.
 The time difference tells the information about distance between GPS
receiver and satellite.
 Now, with distance measurements from a few more satellite the receiver can
determine the user position.
 In GPS, signal of at least three satellites is required to calculate a 2D position
(latitude and longitude) and track movement.
 With signal from four or more satellites, the receiver can determine the 3D
position (latitude, longitude and altitude).

16. Triangulation
2- D
Positioning
3- D
Positioning

17. Application in Agriculture

19. Effect of Crop Health On Reflectance in Different Spectrum
Range

20.  NDVI was developed by a NASA scientist named Compton Tucker in a 1977.
 The Normalized Difference Vegetation Index (NDVI) is a quantitative index of
greenness ranging from 0 - 1 where 0 represents minimal or no greenness
and 1 represents maximum greenness.
 NDVI is often used for a quantitative proxy measure of vegetation health,
cover and phenology (life cycle stage) over large areas.

21. NDVI

22. Crop Identification
 Multitemporal and multispectral remote sensing imagery has been widely
used for crop identification
 The basis for separating one crop from another is the supposition that each
crop species has a specific spectral signature in a time series of
multispectral images

23. Spectral Behaviour

24. Agricultural Drought Assessment
 Since green vegetation had strong absorption of spectrum in red region and
high reflectance in infrared region, vegetation index was thus generally
formulated as various combinations of red and infrared bands.
 The monthly average temperature of the region is calculated and the values
are correlated with the monthly NDVI values in order to understand the
changes in vegetation growth with respect to the rainfall and temperature,
thereby indicating the intensity of agricultural drought.

25. The National Agricultural Draught Assessment and
Monitoring System (NADAMS)
Ground system Satellite system
Rainfall Aridity Index Historical VICrop calendar Land Use Current VI
Geographical Information System
Decision support System
VI Anomaly (Normal VI – Current VI) Drought Condition
Up to 10% - Normal
10-25% - Mild
25-50% - Moderate
> 50% - Severe
Drought bulletin and Map

26. Assessment of Agricultural Drought in Rajasthan Using Remote
Sensing Derived Vegetation Condition Index (VCI)
26
Dutta et al 2015

27. Crop Acerage and Crop Production Estimation
 Estimating of crop production in advance of the harvest is the great utility in
the farming such as implementing appropriate agriculture management and
pricing of export/import of agriculture commodities.
 Spectral reflectance data obtained from remote sensing is a manifestation of
integrated effect of weather, soil, cultural practices and crop characteristics
that can be used in identifying and monitoring crop growth and for
estimating crop yield.
 For large monocropped area with uniform crop distribution, coarser
resolution data such as IRS LISS I and LISS II with 72.5 and 36.25 meter
spatial resolutions respectively would be adequate.

28. Crop Acerage and Crop Production Estimation
 In multi-cropped region characterized by small field size and scatted crop
distribution, higher spatial resolution data such as from LISS III (23 m) would
be desirable.
 Vegetation Indices (VIs) derived from RS data acquired at maximum
vegetative growth stage are indicative of crop growth, vigour and potential
grain yield.

29. Wheat Acerage Estimation Using Remote Sensing Data
Hooda et al, HARSAC, Hisar

30. Wheat Production Estimation Using Remote Sensing Data
Hooda et al, HARSAC, Hisar

31.  Remote sensing in the middle-infrared and thermal infrared portion of the
EMR can provide information as to how much water is in the leaves and soil
.
 Water is a good absorber of middle-infrared energy. Therefore, leaves with
high moisture content will have low reflectance in the middle-infrared
portion.
 So high reflectance would signify low moisture content.
 Thermal Infrared used to compute the crop water stress indices (CWSI), a
measure of the crop water status .

32. Watershed Analysis For Water Resource Management Using Remote
Sensing and GIS Techniques
32Singh et al, 2014
Slope map of the Orr watershed, M.P., India

33. Land Suitability Map of Wheat Using Remote sensing and GIS
Mustafa et al, 2011, IARI New Delhi
9.6 %
23.06 %
35.44 %
15.92 %
15.95 %

34. Thakor et al, 2014

35. Identification of Disease and pest infestation
 Breakdown of foliar pigments
 Foliar physiological activity decreases.
 Less reflectance of infrared by disease affected plant and vice versa.
 Decrease in value of NDVI.

36. Some other application
 Monitoring and evaluation of watershed development project.
 Land use/cover & degradation mapping
 Identification of planting and harvesting dates
 Identification of problematic soils

37. Application of GPS and GIS in Precision Agriculture
 Location information is collected by GPS receivers for mapping field
boundaries, roads, irrigation systems, and problem areas in crops such as
weeds or disease.
 Today, farmers in developed countries use GPS mapping for more precise
application of pesticides, herbicides, and fertilizers; better control
and dispersion of these chemicals are possible through precision
agriculture.
Tractor guidance
Crop scouting
Variable rate applications

38. Precision Agriculture

39.  Remote sensing technology plays an important role in natural resources
management .
 GIS can be used in producing a soil fertility map of an area, which will help in
formulating site specific balanced fertilizer recommendation and to
understand the status of soil fertility.
 With the help of global positioning system (GPS), it is possible to record
field data (slope, aspect, nutrients, and yield) as geographically Latitude and
longitude data.
 Thus, it can be concluded that remote sensing, GIS and GPS are tools for
enhancing agricultural crop production through efficient utilization of land,
irrigation water management, crop acreage estimation, crop identification,
pest and disease management and drought assessment etc.