A Web Based Google Earth Engine Approach for Irrigation Scheduling in Uttar Pradesh India Using Crop Water Stress Index

Pragati Singh; Ashutosh Singh; Rajesh Kumar Upadhyay

doi:doi:10.11648/j.ajrs.20210901.15

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A Web Based Google Earth Engine Approach for Irrigation Scheduling in Uttar Pradesh India Using Crop Water Stress Index

Pragati Singh, Ashutosh Singh, Rajesh Kumar Upadhyay

Published in American Journal of Remote Sensing (Volume 9, Issue 1)

Received: 10 March 2021 Accepted: 25 March 2021 Published: 1 April 2021

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Abstract

Upgrading water use in agricultural crops requires advancements in location of crop water stress for irrigation scheduling, at different phases of the developing season to limit crop physiological harm and yield reduction. Potential of satellite data provide spatial and temporal dynamics of crop growth condition under water stress and analyse for suggestion of irrigation. This study is based on real time open-source web-based Google Earth Engine (GEE) approach for irrigation scheduling at field level based on its water stress condition. Sentinel-2 data was used for detecting water stress using the NDVI and NDWI indices. NDVI shows the crop growth and health whereas NDWI its water stress condition, by combining both the indices we have generated a new index, which is Crop Water Stress Index (CWSI) to schedule the irrigation. The real time Sentinel-2 data was used extract NDVI and NDWI indices and by combining both the indices a new indice was generated for detecting crop water stress condition to schedule the irrigation in real time. The output comes in five group of water stress condition as; No Stress, Low stress, Moderate stress, High stress and Severe stress. Using the result of CWSI the immediate irrigation should be given to those fields which are facing severe and high stress, delayed in moderate and low stress and no irrigation in no-stress. The overall study indicates that, GEE provide a real time better platform for analysing Crop Water Stress situation for scheduling proper irrigation practices for proper growth of crops to improve the production and income of farmers as well as It helps the irrigation planner for proper management of canals and other irrigation resources to the wastage of water.

Published in	American Journal of Remote Sensing (Volume 9, Issue 1)
DOI	10.11648/j.ajrs.20210901.15
Page(s)	42-46
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

CWSI, Irrigation Scheduling, NDVI, NDWI

References

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[2]	A. A. &. N. D. C. Alderfasi, "Use of crop water stress index for monitoring water status and scheduling irrigation in wheat," Agricultural Water Management, pp. 69-75, (2001)..
[3]	"Chapter 1 The role of water in agricultural development," FAO, 2003. [Online]. Available: http://www.fao.org/3/y5582e/y5582e04.htm. [Accessed 18 02 2018].
[4]	D. R. EM Perry, "Sensitivity of Narrow-Band and Broad-Band Indices for Assessing Nitrogen Availability and Water Stress in an Annual Crop," Agronomy journal, vol. 100, no. 4, pp. 1211-1219, 2008.
[5]	M. A. El-Shirbeny, "Sentinel-1 Radar Data Assessment to Estimate Crop Water Stress," World Journal of Engineering and Technology, vol. 5, no. 2, p. 47, 2017.
[6]	"Wikepedia," 2014. [Online]. Available: https://en.wikipedia.org/wiki/Wheat#:~:text=The%20archaeological%20record%20suggests%20that,220.4%20million%20hectares%2C%202014).. [Accessed 16 04 2018].
[7]	P. K. P. S. N. K. R. K. U. a. S. P. S. J. Yadav, "Impact of Canal Restructuring on Agricultural Land Use in 23 Down Haidergarh Canal Command System, Uttar Pradesh, India," International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vols. Volume XLII-3/W6, no. 345-350, 2019.
[8]	C. M. SO Ihuoma, "Recent advances in crop water stress detection," Computers and Electronics in Agriculture, vol. 141, pp. 267-275, 2017.
[9]	R. U. H. P. B. M. O. S. V. Pragati Singh, "CROP SUITABILITY ANALYSIS FOR CEREAL CROPS OF UTTAR PRADESH, INDIA," International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, vol. XLII, no. 5, pp. 353-360, 2018.
[10]	"Use of crop water stress index for monitoring water status and scheduling irrigation in wheat," Agricultural Water Management.
[11]	M. O. JH Patel, "Deriving crop calendar using NDVI time-series," The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 40, no. 8, pp. 869-873, 2014.
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[13]	G. R. F. V. A. M. JA Alvarez, Drought Management and Planning for Water Resources, CRC Press, 2005.
[14]	S. I. R. R. RD Jackson, "Canopy temperature as a crop water stress indicator," Water resources, vol. 17, no. 4, pp. 1133-1138, 1981.
[15]	N. P. M. K. S. S. N Dangwal, "Monitoring of water stress in wheat using multispectral indices derived from Landsat-TM," Geocarto International, vol. Volume 31, no. 6, pp. 682-693., 2016.
[16]	P. S. S. P. S. J. N. K. a. R. K. U. Sunil Kumar Yadav, "SOIL MOISTURE ANALYSIS OF LALITPUR DISTRICT UTTAR PRADESH INDIA USING LANDSAT AND SENTINEL DATA.," International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, Vols. Volume XLII-3/W6, pp. 351-356, 2019.
[17]	Ulaval.ca, "Thermal water stress index from satellite images," [Online]. Available: http://theses.ulaval.ca/archimede/fichiers/21726/ch06.html. [Accessed 12 04 2018].
[18]	A. V. F. A. JD Jang, "Thermal-water stress index from satellite images," International Journal of Remote Sensing, vol. 27, no. 8, pp. 1619-1639, 2006.
[19]	H. C. B. D. D. U. S. L. &. K. S. C. Stimson, "Spectral sensing of foliar water conditions in two co-occurring conifer species: Pinus edulis and Juniperus monosperma," Remote Sensing of Environment, vol. 96, no. 1, pp. 108-118, 2005.

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APA Style

Pragati Singh, Ashutosh Singh, Rajesh Kumar Upadhyay. (2021). A Web Based Google Earth Engine Approach for Irrigation Scheduling in Uttar Pradesh India Using Crop Water Stress Index. American Journal of Remote Sensing, 9(1), 42-46. https://doi.org/10.11648/j.ajrs.20210901.15

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ACS Style

Pragati Singh; Ashutosh Singh; Rajesh Kumar Upadhyay. A Web Based Google Earth Engine Approach for Irrigation Scheduling in Uttar Pradesh India Using Crop Water Stress Index. Am. J. Remote Sens. 2021, 9(1), 42-46. doi: 10.11648/j.ajrs.20210901.15

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AMA Style

Pragati Singh, Ashutosh Singh, Rajesh Kumar Upadhyay. A Web Based Google Earth Engine Approach for Irrigation Scheduling in Uttar Pradesh India Using Crop Water Stress Index. Am J Remote Sens. 2021;9(1):42-46. doi: 10.11648/j.ajrs.20210901.15

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@article{10.11648/j.ajrs.20210901.15,
  author = {Pragati Singh and Ashutosh Singh and Rajesh Kumar Upadhyay},
  title = {A Web Based Google Earth Engine Approach for Irrigation Scheduling in Uttar Pradesh India Using Crop Water Stress Index},
  journal = {American Journal of Remote Sensing},
  volume = {9},
  number = {1},
  pages = {42-46},
  doi = {10.11648/j.ajrs.20210901.15},
  url = {https://doi.org/10.11648/j.ajrs.20210901.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajrs.20210901.15},
  abstract = {Upgrading water use in agricultural crops requires advancements in location of crop water stress for irrigation scheduling, at different phases of the developing season to limit crop physiological harm and yield reduction. Potential of satellite data provide spatial and temporal dynamics of crop growth condition under water stress and analyse for suggestion of irrigation. This study is based on real time open-source web-based Google Earth Engine (GEE) approach for irrigation scheduling at field level based on its water stress condition. Sentinel-2 data was used for detecting water stress using the NDVI and NDWI indices. NDVI shows the crop growth and health whereas NDWI its water stress condition, by combining both the indices we have generated a new index, which is Crop Water Stress Index (CWSI) to schedule the irrigation. The real time Sentinel-2 data was used extract NDVI and NDWI indices and by combining both the indices a new indice was generated for detecting crop water stress condition to schedule the irrigation in real time. The output comes in five group of water stress condition as; No Stress, Low stress, Moderate stress, High stress and Severe stress. Using the result of CWSI the immediate irrigation should be given to those fields which are facing severe and high stress, delayed in moderate and low stress and no irrigation in no-stress. The overall study indicates that, GEE provide a real time better platform for analysing Crop Water Stress situation for scheduling proper irrigation practices for proper growth of crops to improve the production and income of farmers as well as It helps the irrigation planner for proper management of canals and other irrigation resources to the wastage of water.},
 year = {2021}
}

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TY  - JOUR
T1  - A Web Based Google Earth Engine Approach for Irrigation Scheduling in Uttar Pradesh India Using Crop Water Stress Index
AU  - Pragati Singh
AU  - Ashutosh Singh
AU  - Rajesh Kumar Upadhyay
Y1  - 2021/04/01
PY  - 2021
N1  - https://doi.org/10.11648/j.ajrs.20210901.15
DO  - 10.11648/j.ajrs.20210901.15
T2  - American Journal of Remote Sensing
JF  - American Journal of Remote Sensing
JO  - American Journal of Remote Sensing
SP  - 42
EP  - 46
PB  - Science Publishing Group
SN  - 2328-580X
UR  - https://doi.org/10.11648/j.ajrs.20210901.15
AB  - Upgrading water use in agricultural crops requires advancements in location of crop water stress for irrigation scheduling, at different phases of the developing season to limit crop physiological harm and yield reduction. Potential of satellite data provide spatial and temporal dynamics of crop growth condition under water stress and analyse for suggestion of irrigation. This study is based on real time open-source web-based Google Earth Engine (GEE) approach for irrigation scheduling at field level based on its water stress condition. Sentinel-2 data was used for detecting water stress using the NDVI and NDWI indices. NDVI shows the crop growth and health whereas NDWI its water stress condition, by combining both the indices we have generated a new index, which is Crop Water Stress Index (CWSI) to schedule the irrigation. The real time Sentinel-2 data was used extract NDVI and NDWI indices and by combining both the indices a new indice was generated for detecting crop water stress condition to schedule the irrigation in real time. The output comes in five group of water stress condition as; No Stress, Low stress, Moderate stress, High stress and Severe stress. Using the result of CWSI the immediate irrigation should be given to those fields which are facing severe and high stress, delayed in moderate and low stress and no irrigation in no-stress. The overall study indicates that, GEE provide a real time better platform for analysing Crop Water Stress situation for scheduling proper irrigation practices for proper growth of crops to improve the production and income of farmers as well as It helps the irrigation planner for proper management of canals and other irrigation resources to the wastage of water.
VL  - 9
IS  - 1
ER  -

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Author Information

Pragati Singh

Agriculture Resources Division, Remote Sensing Applications Centre, Lucknow, Uttar Pradesh, India
Ashutosh Singh

Agriculture Resources Division, Remote Sensing Applications Centre, Lucknow, Uttar Pradesh, India
Rajesh Kumar Upadhyay

Agriculture Resources Division, Remote Sensing Applications Centre, Lucknow, Uttar Pradesh, India

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Plain Text BibTeX RIS

APA Style

Pragati Singh, Ashutosh Singh, Rajesh Kumar Upadhyay. (2021). A Web Based Google Earth Engine Approach for Irrigation Scheduling in Uttar Pradesh India Using Crop Water Stress Index. American Journal of Remote Sensing, 9(1), 42-46. https://doi.org/10.11648/j.ajrs.20210901.15

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ACS Style

Pragati Singh; Ashutosh Singh; Rajesh Kumar Upadhyay. A Web Based Google Earth Engine Approach for Irrigation Scheduling in Uttar Pradesh India Using Crop Water Stress Index. Am. J. Remote Sens. 2021, 9(1), 42-46. doi: 10.11648/j.ajrs.20210901.15

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AMA Style

Pragati Singh, Ashutosh Singh, Rajesh Kumar Upadhyay. A Web Based Google Earth Engine Approach for Irrigation Scheduling in Uttar Pradesh India Using Crop Water Stress Index. Am J Remote Sens. 2021;9(1):42-46. doi: 10.11648/j.ajrs.20210901.15

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@article{10.11648/j.ajrs.20210901.15,
  author = {Pragati Singh and Ashutosh Singh and Rajesh Kumar Upadhyay},
  title = {A Web Based Google Earth Engine Approach for Irrigation Scheduling in Uttar Pradesh India Using Crop Water Stress Index},
  journal = {American Journal of Remote Sensing},
  volume = {9},
  number = {1},
  pages = {42-46},
  doi = {10.11648/j.ajrs.20210901.15},
  url = {https://doi.org/10.11648/j.ajrs.20210901.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajrs.20210901.15},
  abstract = {Upgrading water use in agricultural crops requires advancements in location of crop water stress for irrigation scheduling, at different phases of the developing season to limit crop physiological harm and yield reduction. Potential of satellite data provide spatial and temporal dynamics of crop growth condition under water stress and analyse for suggestion of irrigation. This study is based on real time open-source web-based Google Earth Engine (GEE) approach for irrigation scheduling at field level based on its water stress condition. Sentinel-2 data was used for detecting water stress using the NDVI and NDWI indices. NDVI shows the crop growth and health whereas NDWI its water stress condition, by combining both the indices we have generated a new index, which is Crop Water Stress Index (CWSI) to schedule the irrigation. The real time Sentinel-2 data was used extract NDVI and NDWI indices and by combining both the indices a new indice was generated for detecting crop water stress condition to schedule the irrigation in real time. The output comes in five group of water stress condition as; No Stress, Low stress, Moderate stress, High stress and Severe stress. Using the result of CWSI the immediate irrigation should be given to those fields which are facing severe and high stress, delayed in moderate and low stress and no irrigation in no-stress. The overall study indicates that, GEE provide a real time better platform for analysing Crop Water Stress situation for scheduling proper irrigation practices for proper growth of crops to improve the production and income of farmers as well as It helps the irrigation planner for proper management of canals and other irrigation resources to the wastage of water.},
 year = {2021}
}

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TY  - JOUR
T1  - A Web Based Google Earth Engine Approach for Irrigation Scheduling in Uttar Pradesh India Using Crop Water Stress Index
AU  - Pragati Singh
AU  - Ashutosh Singh
AU  - Rajesh Kumar Upadhyay
Y1  - 2021/04/01
PY  - 2021
N1  - https://doi.org/10.11648/j.ajrs.20210901.15
DO  - 10.11648/j.ajrs.20210901.15
T2  - American Journal of Remote Sensing
JF  - American Journal of Remote Sensing
JO  - American Journal of Remote Sensing
SP  - 42
EP  - 46
PB  - Science Publishing Group
SN  - 2328-580X
UR  - https://doi.org/10.11648/j.ajrs.20210901.15
AB  - Upgrading water use in agricultural crops requires advancements in location of crop water stress for irrigation scheduling, at different phases of the developing season to limit crop physiological harm and yield reduction. Potential of satellite data provide spatial and temporal dynamics of crop growth condition under water stress and analyse for suggestion of irrigation. This study is based on real time open-source web-based Google Earth Engine (GEE) approach for irrigation scheduling at field level based on its water stress condition. Sentinel-2 data was used for detecting water stress using the NDVI and NDWI indices. NDVI shows the crop growth and health whereas NDWI its water stress condition, by combining both the indices we have generated a new index, which is Crop Water Stress Index (CWSI) to schedule the irrigation. The real time Sentinel-2 data was used extract NDVI and NDWI indices and by combining both the indices a new indice was generated for detecting crop water stress condition to schedule the irrigation in real time. The output comes in five group of water stress condition as; No Stress, Low stress, Moderate stress, High stress and Severe stress. Using the result of CWSI the immediate irrigation should be given to those fields which are facing severe and high stress, delayed in moderate and low stress and no irrigation in no-stress. The overall study indicates that, GEE provide a real time better platform for analysing Crop Water Stress situation for scheduling proper irrigation practices for proper growth of crops to improve the production and income of farmers as well as It helps the irrigation planner for proper management of canals and other irrigation resources to the wastage of water.
VL  - 9
IS  - 1
ER  -

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