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International Journal of Advanced Engineering Research and Science (IJAERS) [Vol-5, Issue-4, Apr- 2018]
https://dx.doi.org/10.22161/ijaers.5.4.10 ISSN: 2349-6495(P) | 2456-1908(O)
www.ijaers.com Page | 63
Application of Remote Sensing & GIS in
Agriculture
Acharya S.M1
, Pawar S.S2
, Wable N.B3
1
Assistant professor, Department of Soil Science & Agril. Chemistry, College of Agriculture Business Management,
Narayangaon, Pune. India
Email:smacharya.baif@gmail.com
2
Assistant professor, Department of Agriculture Marketing, College of Agriculture Business Management, Narayangaon,
Pune. India
Email:pawarsiddhesh22@gmail.com
3
Assistant professor, Department of Agriculture Marketing, College of Agriculture Business Management, Narayangaon,
Pune. India
Email:nitinwable5@gmail.com
Abstract—This article provides an overview of some of
the recent research in agriculture involving remote
sensing and GIS. Attention focuses on application of
remote sensing and GIS specially in agriculture including
geography, land surveying, most Earth Science
disciplines, parent child relationship, unique
identification, attributes, technical parameters, 2D/3D
view and any other requirement customized. These
advances have been made over recent years and
foundations for future research established and can be
efficiently used in Agriculture for better results.
Keywords— Agriculture, GIS, Information, Remote
sensing, Satellite.
I. INTRODUCTION
Agriculture is the backbone of Indian economy and the
pivotal sector for ensuring food security. Timely
availability of information on agriculture is vital for
taking informed decisions on food security issues. India is
one of the few countries in the world that uses space
technology and land-based observations for generating
regular updates on crop production statistics and
providing inputs to achieve sustainable agriculture.
Satellite-based optical and radar imagery are used widely
in monitoring agriculture. Radar imagery are especially
used during monsoon season. Integrated use of geospatial
tools with crop models and in-situ observation network
enables timely crop production forecasts and drought
assess-ment & monitoring.
In India, Agriculture plays a vital role in the Indian
economy. Over 50 per cent of the rural households
depend on agriculture. Agriculture is an important sector
of Indian economy as it contributes about 17% to the
total GDP and provides employment to over 60% of the
population. Government recently launched some major
schemes like crop insurance, per drop more crop,
Rashtriya Krishi Vikas Yojna to enhance the productivity
of the crops. Initiatives like organic farming and increase
in the production of pulses are also been taken.
II. REMOTE SENSING
Remote sensing is the acquisition of information about
an object or phenomenon without making physical
contact with the object and thus in contrast to on-site
observation. Remote sensing is used in numerous fields,
including geography, land surveying and most Earth
Science disciplines (for example, hydrology, ecology,
oceanography, glaciology, geology); it also has military,
intelligence, commercial, economic, planning, and
humanitarian applications.
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 by the object is detected by the sensor) and
"passive" remote sensing (i.e., when the reflection of
sunlight is detected by the sensor).
Who needs remote sensing for agriculture?
Govt. authorities or local agencies can use remote sensing
data, in order to make important decisions about the
policies they will adopt or measures 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.
International Journal of Advanced Engineering Research and Science (IJAERS) [Vol-5, Issue-4, Apr- 2018]
https://dx.doi.org/10.22161/ijaers.5.4.10 ISSN: 2349-6495(P) | 2456-1908(O)
www.ijaers.com Page | 64
III. GEOGRAPHICAL INFORMATION SYSTEM
(GIS)
Geographical Information System (GIS) combines
location data with both quantitative and qualitative
information about the location, allowing you to visualize,
analyze, and report information through maps and charts.
Using the technology, you can answer questions, conduct
what-if scenarios, and visualize results. GIS is identified
as a system used to manage infrastructure assets, natural
resources and any objects as per requirement. It is easier
to analyze and manage facility and asset data stored in
GIS, making design, construction, and maintenance more
efficient and profitable.
GIS is a software based system which facilitates end to
end information of assets or any type of objects as
required by end user on maps having desired accuracy in
raster and vector forms. GIS aids geographical location,
parent child relationship, unique identification, attributes,
technical parameters, 2D/3D view and any other
requirement customized. GIS information/data is most
adoptable, accurate and user-friendly to meet general
requirements of operations and other software
applications. Using main GIS application, other GIS
based applications can be easily developed to meet
specific requirements of users. Such systems are essential
in Utility (Water, Electric, Gas), Local Government
Authorities, Defense Services, Aviation, Roads,
Transportation Services, Space, Mining and any multi-
location business operations requirements. These utilities
are managed under various GIS based domains
like Utility GIS, Municipal GIS.
In ancient India apparently had a clear concept of remote
sensing. For instance epic ‘Maha Bharata’ Sanjaya had
been endowed, presumably with some equipment which
enabled him to report (in real time) all the events at the
distant “Kurukshetra” battle field, whether they were
open or camouflaged and occurred in day or by night.
In recent times, Frenchman Mr. Tournachen took
photographs for the first time from a balloon which
floated over Paris in 1858. The term “Remote sensing”
was first used in 1961 when U.S. Naval project on the
study of Aerial photographs was renamed as “remote
sensing”.The application of remote sensing technology to
agriculture and forestry was presented in couple of papers
in 1968 at the occasion of U.N. conference on peaceful
uses of on the space uses and the first satellite in remote
sensing technology was launched in July 1972 in U.S.A.
In India the remote sensing activities
Agricultural plants, as living organisms require water and
nutrients in order to grow and are sensitive to extreme
weather phenomena, diseases and pests. Remote
sensing can provide data that helps identify and monitor
crops. When these data is organised in a Geographical
Information System (GIS) along with other parameters,
they become an important tool that helps in making
decisions about crops and agricultural strategies.
IV. IMPORTANCE OF REMOTE SENSING AND
GIS
To identify the potential land for any particular crop, GIS
is the best technique as it brings all the data on a single
platform for the analysis. Different vegetation indices like
NDVI, FPAR and TVI. are widely used to monitor crop
health which is also directly proportional to yield. In case
of crop insurance, actual damage can be assessed. Claims
and compensations can be given on fair basis.
To monitor crop health, its growth and production various
factors come into play such as temperature, irrigation
facilities and the most important soil health condition. For
this purpose government has launched a nation-wide
scheme called soil health card.
Under this scheme mapping of soil is done along with
its nutrient and sub-nutrient information like pH
content, nitrogen, phosphorus, soil moisture etc.
Mapping of soil has been done by Ceinsys in
Jharkhand, state of India. The project was successfully
implemented in 06 districts of Jharkhand state
covering 13000 Sq. Km. area.
V. CONCLUSION
In order to implement these programs effectively it is
vital to use the latest technologies like remote sensing
and GIS. The decision makers can visualize all the
farmlands with their allied information and current
situation on one click. The tasks like yield estimation
& crop damage assessment done by traditional means
take month or two and a whole lot of manpower to
complete the work. By using these technologies the
same task can be completed within half or even in
lesser time frame with minimum number of resources
and high accuracy. Balancing the inputs and outputs
on a crop farm is essential to its success and cost-
effectiveness. The ability of GIS to study and envisage
agricultural environments and workflows has proved
to be favourable to those involved in the farming
industry. While natural inputs in farming cannot be
International Journal of Advanced Engineering Research and Science (IJAERS) [Vol-5, Issue-4, Apr- 2018]
https://dx.doi.org/10.22161/ijaers.5.4.10 ISSN: 2349-6495(P) | 2456-1908(O)
www.ijaers.com Page | 65
measured but, can be better understood and managed
with GIS applications such as crop yield estimates,
soil amendment analysis, erosion identification and
remediation.
REFERENCES
[1] A blog from Ceinysys Tech Ltd 20 Mar-17
Remote Sensing & Agriculture GIS
[2] Anji Reddy, M., 2000, Remote Sensing and
Geographic Information Systems, The Book
Syndicate, Hyderabad, pp. 22-24
[3] Asner G P 1998. Biophysical and biochemical
sources of variability in canopy reflectance.
Remote Sens Environ 64: 234-53.
[4] Atzberger C 2013. Advances in remote sensing of
agriculture: context description, existing
operational monitoring systems and major
information needs. Remote Sens 5: 949 – 81.
[5] Agarwal, C.S., and Garg, P.K., 2000, Remote
Sensing in Natural Resources Monitoring and
Management, Wheeler publishing, A Division of
A.H. Wheeler & Co.Ltd, New Delhi, pp. 19-25
[6] Barnes E M, Sudduth K A, Hummel J W, Lesch S
M, Corwin D L, Yang C, Daughtry C S T and
Bausch W C 2003. Remote- and ground-based
sensor techniques to map soil properties,
Photogrammetric Engineering & Remote Sensing
69(6): 619– 30.
[7] Basso B, Cammarano D and De Vita P 2004.
Remotely sensed vegetation indices: theory and
applications for crop management. Rivista Italiana
di Agrometeorologia (1): 36-53.
[8] Batra N, Islam S, Venturini V, Bisht G and Jiang L
2006. Estimation and comparison of
evapotranspiration from MODIS and AVHRR
sensors for clear sky days over the Southern Great
Plains. Remote Sens Environ 103: 1-15.
[9] Bernardes T, Meriera M A, Adami M, Giarolle A
and Rudor B F T 2012. Monitoring biennial
bearing e ect on co ee yield using MODIS
remote sensing imagery. Remote Sens 4: 2492 –
2509.
[10]Brackenridge R, Anderson E and Nghiem S V
2006. Satellite microwave detection and
measurement of river floods. NASA Spring Annual
General Conference 2006.www.nasa.gov/
vision/earth/lookingatearth/springagu_2006.html
(Accessed 4 October 2006).
[11]Burrows J P, Dehn A, Deters B, Himmelmann S,
Richter A, Voigt S and Orphal J 1998.
Atmospheric remote-sensing reference data from
GOME: part 1. Temperature-dependent absorption
cross- sections of NO2 in the 231—794 nm range.
J Quant Spectrosc Radiat Transf 60 (6): 1025-31.
[12]Chapman L and Thornes J E 2003. The use of
geographical information system in climatology
and meteorology. Climate and Atmospheric
Research Group, School of Geography and
Environmental Science, University of
Birmingham, Birmingham B15 2TT, UK.
[13]Desmond Ball, 1989, Geographic Information
System: Defense Applications, Pergamon Press
(Australia) P.Ltd, Australia, pp. 42-60.
[14]Estes, E John., and Senger, W Leslie., 1974,
Remote Sensing Techniques for Environmental
Analysis, Hamilton publishing company,
California, pp. 189-214.
[15]Eckert S, Ratsimba H R, Rakotondrasoa L O,
Rajoelison L G and Ehrensperger A 2011.
Deforestation and forest degradation monitoring
and assessment of biomass and carbon stock of
lowland rainforest in the Analanjirofo region,
Madagascar. Forest Ecology and Management
262: 1996–2007.
[16]Mather, P.M., 1987, Computer processing of
Remotely sensed image: An introduction, John
Wiley & Sons, p357
[17]Magurie, D. J David., 1989, Computer in
Geography , Longman Group (FE) Ltd, Hongkong,
pp. 63-67
[18]Mohan Sundran Rajan., 1995, Space Today,
National book trust, New Delhi, pp. 165168.
[19]Patel Surendra Singh, A.N., 1992, Remote
Sensing: Principles and Applications, Scientific
publishers, Jodhpur, pp. 1-40
[20]Pisharoty, P.R., 1984, Introduction to Remote
Sensing, Indian Academy of Science, Bangalore,
pp. 45-47
[21]Rao, U.R., 1996, Space Technology for
Sustainable Development, Tata McGraw-Hill
Publishing company Ltd, New Delhi, pp. 66-78
[22]Websites:
https://wiki.seg.org/wiki/Remote_sensing,
https://nrsc.gov.in/Agriculture

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Application of Remote Sensing GIS in Agriculture.pdf

  • 1. International Journal of Advanced Engineering Research and Science (IJAERS) [Vol-5, Issue-4, Apr- 2018] https://dx.doi.org/10.22161/ijaers.5.4.10 ISSN: 2349-6495(P) | 2456-1908(O) www.ijaers.com Page | 63 Application of Remote Sensing & GIS in Agriculture Acharya S.M1 , Pawar S.S2 , Wable N.B3 1 Assistant professor, Department of Soil Science & Agril. Chemistry, College of Agriculture Business Management, Narayangaon, Pune. India Email:smacharya.baif@gmail.com 2 Assistant professor, Department of Agriculture Marketing, College of Agriculture Business Management, Narayangaon, Pune. India Email:pawarsiddhesh22@gmail.com 3 Assistant professor, Department of Agriculture Marketing, College of Agriculture Business Management, Narayangaon, Pune. India Email:nitinwable5@gmail.com Abstract—This article provides an overview of some of the recent research in agriculture involving remote sensing and GIS. Attention focuses on application of remote sensing and GIS specially in agriculture including geography, land surveying, most Earth Science disciplines, parent child relationship, unique identification, attributes, technical parameters, 2D/3D view and any other requirement customized. These advances have been made over recent years and foundations for future research established and can be efficiently used in Agriculture for better results. Keywords— Agriculture, GIS, Information, Remote sensing, Satellite. I. INTRODUCTION Agriculture is the backbone of Indian economy and the pivotal sector for ensuring food security. Timely availability of information on agriculture is vital for taking informed decisions on food security issues. India is one of the few countries in the world that uses space technology and land-based observations for generating regular updates on crop production statistics and providing inputs to achieve sustainable agriculture. Satellite-based optical and radar imagery are used widely in monitoring agriculture. Radar imagery are especially used during monsoon season. Integrated use of geospatial tools with crop models and in-situ observation network enables timely crop production forecasts and drought assess-ment & monitoring. In India, Agriculture plays a vital role in the Indian economy. Over 50 per cent of the rural households depend on agriculture. Agriculture is an important sector of Indian economy as it contributes about 17% to the total GDP and provides employment to over 60% of the population. Government recently launched some major schemes like crop insurance, per drop more crop, Rashtriya Krishi Vikas Yojna to enhance the productivity of the crops. Initiatives like organic farming and increase in the production of pulses are also been taken. II. REMOTE SENSING Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object and thus in contrast to on-site observation. Remote sensing is used in numerous fields, including geography, land surveying and most Earth Science disciplines (for example, hydrology, ecology, oceanography, glaciology, geology); it also has military, intelligence, commercial, economic, planning, and humanitarian applications. 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 by the object is detected by the sensor) and "passive" remote sensing (i.e., when the reflection of sunlight is detected by the sensor). Who needs remote sensing for agriculture? Govt. authorities or local agencies can use remote sensing data, in order to make important decisions about the policies they will adopt or measures 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.
  • 2. International Journal of Advanced Engineering Research and Science (IJAERS) [Vol-5, Issue-4, Apr- 2018] https://dx.doi.org/10.22161/ijaers.5.4.10 ISSN: 2349-6495(P) | 2456-1908(O) www.ijaers.com Page | 64 III. GEOGRAPHICAL INFORMATION SYSTEM (GIS) Geographical Information System (GIS) combines location data with both quantitative and qualitative information about the location, allowing you to visualize, analyze, and report information through maps and charts. Using the technology, you can answer questions, conduct what-if scenarios, and visualize results. GIS is identified as a system used to manage infrastructure assets, natural resources and any objects as per requirement. It is easier to analyze and manage facility and asset data stored in GIS, making design, construction, and maintenance more efficient and profitable. GIS is a software based system which facilitates end to end information of assets or any type of objects as required by end user on maps having desired accuracy in raster and vector forms. GIS aids geographical location, parent child relationship, unique identification, attributes, technical parameters, 2D/3D view and any other requirement customized. GIS information/data is most adoptable, accurate and user-friendly to meet general requirements of operations and other software applications. Using main GIS application, other GIS based applications can be easily developed to meet specific requirements of users. Such systems are essential in Utility (Water, Electric, Gas), Local Government Authorities, Defense Services, Aviation, Roads, Transportation Services, Space, Mining and any multi- location business operations requirements. These utilities are managed under various GIS based domains like Utility GIS, Municipal GIS. In ancient India apparently had a clear concept of remote sensing. For instance epic ‘Maha Bharata’ Sanjaya had been endowed, presumably with some equipment which enabled him to report (in real time) all the events at the distant “Kurukshetra” battle field, whether they were open or camouflaged and occurred in day or by night. In recent times, Frenchman Mr. Tournachen took photographs for the first time from a balloon which floated over Paris in 1858. The term “Remote sensing” was first used in 1961 when U.S. Naval project on the study of Aerial photographs was renamed as “remote sensing”.The application of remote sensing technology to agriculture and forestry was presented in couple of papers in 1968 at the occasion of U.N. conference on peaceful uses of on the space uses and the first satellite in remote sensing technology was launched in July 1972 in U.S.A. In India the remote sensing activities Agricultural plants, as living organisms require water and nutrients in order to grow and are sensitive to extreme weather phenomena, diseases and pests. Remote sensing can provide data that helps identify and monitor crops. When these data is organised in a Geographical Information System (GIS) along with other parameters, they become an important tool that helps in making decisions about crops and agricultural strategies. IV. IMPORTANCE OF REMOTE SENSING AND GIS To identify the potential land for any particular crop, GIS is the best technique as it brings all the data on a single platform for the analysis. Different vegetation indices like NDVI, FPAR and TVI. are widely used to monitor crop health which is also directly proportional to yield. In case of crop insurance, actual damage can be assessed. Claims and compensations can be given on fair basis. To monitor crop health, its growth and production various factors come into play such as temperature, irrigation facilities and the most important soil health condition. For this purpose government has launched a nation-wide scheme called soil health card. Under this scheme mapping of soil is done along with its nutrient and sub-nutrient information like pH content, nitrogen, phosphorus, soil moisture etc. Mapping of soil has been done by Ceinsys in Jharkhand, state of India. The project was successfully implemented in 06 districts of Jharkhand state covering 13000 Sq. Km. area. V. CONCLUSION In order to implement these programs effectively it is vital to use the latest technologies like remote sensing and GIS. The decision makers can visualize all the farmlands with their allied information and current situation on one click. The tasks like yield estimation & crop damage assessment done by traditional means take month or two and a whole lot of manpower to complete the work. By using these technologies the same task can be completed within half or even in lesser time frame with minimum number of resources and high accuracy. Balancing the inputs and outputs on a crop farm is essential to its success and cost- effectiveness. The ability of GIS to study and envisage agricultural environments and workflows has proved to be favourable to those involved in the farming industry. While natural inputs in farming cannot be
  • 3. International Journal of Advanced Engineering Research and Science (IJAERS) [Vol-5, Issue-4, Apr- 2018] https://dx.doi.org/10.22161/ijaers.5.4.10 ISSN: 2349-6495(P) | 2456-1908(O) www.ijaers.com Page | 65 measured but, can be better understood and managed with GIS applications such as crop yield estimates, soil amendment analysis, erosion identification and remediation. REFERENCES [1] A blog from Ceinysys Tech Ltd 20 Mar-17 Remote Sensing & Agriculture GIS [2] Anji Reddy, M., 2000, Remote Sensing and Geographic Information Systems, The Book Syndicate, Hyderabad, pp. 22-24 [3] Asner G P 1998. Biophysical and biochemical sources of variability in canopy reflectance. Remote Sens Environ 64: 234-53. [4] Atzberger C 2013. Advances in remote sensing of agriculture: context description, existing operational monitoring systems and major information needs. Remote Sens 5: 949 – 81. [5] Agarwal, C.S., and Garg, P.K., 2000, Remote Sensing in Natural Resources Monitoring and Management, Wheeler publishing, A Division of A.H. Wheeler & Co.Ltd, New Delhi, pp. 19-25 [6] Barnes E M, Sudduth K A, Hummel J W, Lesch S M, Corwin D L, Yang C, Daughtry C S T and Bausch W C 2003. Remote- and ground-based sensor techniques to map soil properties, Photogrammetric Engineering & Remote Sensing 69(6): 619– 30. [7] Basso B, Cammarano D and De Vita P 2004. Remotely sensed vegetation indices: theory and applications for crop management. Rivista Italiana di Agrometeorologia (1): 36-53. [8] Batra N, Islam S, Venturini V, Bisht G and Jiang L 2006. Estimation and comparison of evapotranspiration from MODIS and AVHRR sensors for clear sky days over the Southern Great Plains. Remote Sens Environ 103: 1-15. [9] Bernardes T, Meriera M A, Adami M, Giarolle A and Rudor B F T 2012. Monitoring biennial bearing e ect on co ee yield using MODIS remote sensing imagery. Remote Sens 4: 2492 – 2509. [10]Brackenridge R, Anderson E and Nghiem S V 2006. Satellite microwave detection and measurement of river floods. NASA Spring Annual General Conference 2006.www.nasa.gov/ vision/earth/lookingatearth/springagu_2006.html (Accessed 4 October 2006). [11]Burrows J P, Dehn A, Deters B, Himmelmann S, Richter A, Voigt S and Orphal J 1998. Atmospheric remote-sensing reference data from GOME: part 1. Temperature-dependent absorption cross- sections of NO2 in the 231—794 nm range. J Quant Spectrosc Radiat Transf 60 (6): 1025-31. [12]Chapman L and Thornes J E 2003. The use of geographical information system in climatology and meteorology. Climate and Atmospheric Research Group, School of Geography and Environmental Science, University of Birmingham, Birmingham B15 2TT, UK. [13]Desmond Ball, 1989, Geographic Information System: Defense Applications, Pergamon Press (Australia) P.Ltd, Australia, pp. 42-60. [14]Estes, E John., and Senger, W Leslie., 1974, Remote Sensing Techniques for Environmental Analysis, Hamilton publishing company, California, pp. 189-214. [15]Eckert S, Ratsimba H R, Rakotondrasoa L O, Rajoelison L G and Ehrensperger A 2011. Deforestation and forest degradation monitoring and assessment of biomass and carbon stock of lowland rainforest in the Analanjirofo region, Madagascar. Forest Ecology and Management 262: 1996–2007. [16]Mather, P.M., 1987, Computer processing of Remotely sensed image: An introduction, John Wiley & Sons, p357 [17]Magurie, D. J David., 1989, Computer in Geography , Longman Group (FE) Ltd, Hongkong, pp. 63-67 [18]Mohan Sundran Rajan., 1995, Space Today, National book trust, New Delhi, pp. 165168. [19]Patel Surendra Singh, A.N., 1992, Remote Sensing: Principles and Applications, Scientific publishers, Jodhpur, pp. 1-40 [20]Pisharoty, P.R., 1984, Introduction to Remote Sensing, Indian Academy of Science, Bangalore, pp. 45-47 [21]Rao, U.R., 1996, Space Technology for Sustainable Development, Tata McGraw-Hill Publishing company Ltd, New Delhi, pp. 66-78 [22]Websites: https://wiki.seg.org/wiki/Remote_sensing, https://nrsc.gov.in/Agriculture