Modelling the Climate Change on Crop Estimation in the Semi-Arid Region of Pakistan Using Multispectral Remote Sensing

Zeeshan Zafar; Shoaib Farooq; Muhammad Irfan Ahamad; Muhammad Sajid Mehmood; Nasir Abbas; Summar Abbas

doi:doi:10.11648/j.optics.20200901.11

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Modelling the Climate Change on Crop Estimation in the Semi-Arid Region of Pakistan Using Multispectral Remote Sensing

Zeeshan Zafar, Shoaib Farooq, Muhammad Irfan Ahamad, Muhammad Sajid Mehmood, Nasir Abbas, Summar Abbas

Published in Optics (Volume 9, Issue 1)

Received: 30 October 2020 Accepted: 23 November 2020 Published: 4 December 2020

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Abstract

Remote sensing (RS) is a tool in modern years for the monitoring of crops. Normalized Difference Vegetation Index (NDVI) derived from multi-temporal satellite imagery facilitates the analysis of vegetation growth stage, while comparing it with field/historical departmental yield data. Historical metrological data is also very useful in crop yield estimation especially in arid/semi-arid climatic zones. The metrological conditions including rainfall, humidity, sunshine, and temperature plays vital role in the growth and yield of crops; thus, the climatic conditions can adversely affect the crop yields if are not in accordance with growth requirement of a particular crop. Most of the agricultural land of Punjab province is in semi-arid climatic zone including Chakwal, Jhelum, Mianwali, Khushab, Sargodha, Mandi Bahauddin, Gujranwala, Hafizabad, Shiekhupura, Nankana Sahib, Lahore, Kasur, Faislabad and Chiniot districts. The study will investigate the impact of climate change on wheat crop yields of Chakwal district using advanced RS techniques from 1990 to 2015. Image classification to determine arable and non-arable lands; estimation of changes in temperature using thermal bands of satellite imagery, comparison of historical NDVI profiles; use of climatic data along with nonspatial departmental data for crop yield estimation and drawing its relationship with climatic variables.

Published in	Optics (Volume 9, Issue 1)
DOI	10.11648/j.optics.20200901.11
Page(s)	1-7
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), 2020. Published by Science Publishing Group

Keywords

Metrological Data, Remote Sensing, Crop Yield Estimation, Semi-arid, Chakwal

References

[1]	Ahamad, M. I., Zafar, Z., Arsalan, M., Rehman, A., Sajid, M., Zulqarnain, R. M., Mehmood, M. S., Abdal, S., Aslam, M., 2020. Effects of Temperature and Pressure on Reservoir Fluids and Seismic Properties of Reservoir Rocks. Int. J. Pharm. Sci. Rev. Res. 63, 36–43.
[2]	Ahamad, Song, Sun, Wang, Mehmood, Sajid, Su, Khan, 2020. Contamination Level, Ecological Risk, and Source Identification of Heavy Metals in the Hyporheic Zone of the Weihe River, China. Int. J. Environ. Res. Public Health 17, 1070. https://doi.org/10.3390/ijerph17031070
[3]	Ahemad & Kibert 2014. Crop Phenological Phase based Wheat yield estimation using MODIS NDVI Product. PhD Thesis, Islamabad.
[4]	Ahmad, W., Noor, M. A., Afzal, I., Bakhtavar, M. A., Nawaz, M. M., Sun, X., Zhou, B., Ma, M., Zhao, M., 2016. Improvement of Sorghum Crop through Exogenous Application of Natural Growth-Promoting Substances under a Changing Climate. Sustainability. 8, 1330; http://dx.doi.org/10.3390/su8121330
[5]	Baig, M. B., Straquadine, G., 2011. ‘‘Sustainable agriculture ensures sustainable ruraldevelopment: a reality or a myth”. In: M. Behnassi et al. (Eds.), Global food insecurity: rethinking agricultural and rural development paradigm and policy, pp. 21–32. http://dx.doi.org/10.1007/978-94-007-0890-7_3, Springer Science +Business Media B. V.
[6]	Government of Pakistan, 2015. Ministry of Finance. Pakistan economic survey 2015–16. pp. 5–8.
[7]	Noor, M. A., Ahmad, W., Afzal, I., Salamh, A., Afzal, M., Ahmad, A., Ming, Z., Wei, M., 2016. Pea seed invigoration by priming with magnetized water and moringa leaf extract. Philipp. Agric. Sci 99, 171–175.
[8]	Noor, M. A., Fiaz, S., Nawaz, A., Nawaz, M. M., 2018. The effects of cutting interval on agro-qualitative traits of different millet (Pennisetum americanum L.) cultivars. J. Saudi Soc. Agric. Sci. 17 (3), 317–322. http://dx.doi.org/10.1016/j.jssas.2016.07.002
[9]	Reynolds, C. A., Yitayew, M., Slack, D. C., Hutchison, C. F., Huete, A., & Peteresen, M. S. (2000). Estimating crop yields and production by intergratingthe FAO crop specific Water Balance model with real-time satellite data and ground based ancilliary data. International Journal of Remote Sensing, 348='y 7-3508.
[10]	Waqas, M. A., Khan, I., Akhter, M. J., Noor, M. A., Ashraf, U., 2017. Exogenous application of plant growth regulators (PGRs) induces chilling tolerance in short-duration hybrid maize. Environ. Sci. Pollut. Res. 24, 11459–11471.
[11]	Zafar, S. A., Hameed, A., Khan, A. S., Ashraf, M., 2017. Heat shock induced morphophysiological response in indica rice (Oryza sativa L.) at early seedling stage. Pak. J. Bot. 49 (2), 453–463.

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APA Style

Zeeshan Zafar, Shoaib Farooq, Muhammad Irfan Ahamad, Muhammad Sajid Mehmood, Nasir Abbas, et al. (2020). Modelling the Climate Change on Crop Estimation in the Semi-Arid Region of Pakistan Using Multispectral Remote Sensing. Optics, 9(1), 1-7. https://doi.org/10.11648/j.optics.20200901.11

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ACS Style

Zeeshan Zafar; Shoaib Farooq; Muhammad Irfan Ahamad; Muhammad Sajid Mehmood; Nasir Abbas, et al. Modelling the Climate Change on Crop Estimation in the Semi-Arid Region of Pakistan Using Multispectral Remote Sensing. Optics. 2020, 9(1), 1-7. doi: 10.11648/j.optics.20200901.11

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AMA Style

Zeeshan Zafar, Shoaib Farooq, Muhammad Irfan Ahamad, Muhammad Sajid Mehmood, Nasir Abbas, et al. Modelling the Climate Change on Crop Estimation in the Semi-Arid Region of Pakistan Using Multispectral Remote Sensing. Optics. 2020;9(1):1-7. doi: 10.11648/j.optics.20200901.11

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@article{10.11648/j.optics.20200901.11,
  author = {Zeeshan Zafar and Shoaib Farooq and Muhammad Irfan Ahamad and Muhammad Sajid Mehmood and Nasir Abbas and Summar Abbas},
  title = {Modelling the Climate Change on Crop Estimation in the Semi-Arid Region of Pakistan Using Multispectral Remote Sensing},
  journal = {Optics},
  volume = {9},
  number = {1},
  pages = {1-7},
  doi = {10.11648/j.optics.20200901.11},
  url = {https://doi.org/10.11648/j.optics.20200901.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.optics.20200901.11},
  abstract = {Remote sensing (RS) is a tool in modern years for the monitoring of crops. Normalized Difference Vegetation Index (NDVI) derived from multi-temporal satellite imagery facilitates the analysis of vegetation growth stage, while comparing it with field/historical departmental yield data. Historical metrological data is also very useful in crop yield estimation especially in arid/semi-arid climatic zones. The metrological conditions including rainfall, humidity, sunshine, and temperature plays vital role in the growth and yield of crops; thus, the climatic conditions can adversely affect the crop yields if are not in accordance with growth requirement of a particular crop. Most of the agricultural land of Punjab province is in semi-arid climatic zone including Chakwal, Jhelum, Mianwali, Khushab, Sargodha, Mandi Bahauddin, Gujranwala, Hafizabad, Shiekhupura, Nankana Sahib, Lahore, Kasur, Faislabad and Chiniot districts. The study will investigate the impact of climate change on wheat crop yields of Chakwal district using advanced RS techniques from 1990 to 2015. Image classification to determine arable and non-arable lands; estimation of changes in temperature using thermal bands of satellite imagery, comparison of historical NDVI profiles; use of climatic data along with nonspatial departmental data for crop yield estimation and drawing its relationship with climatic variables.},
 year = {2020}
}

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TY  - JOUR
T1  - Modelling the Climate Change on Crop Estimation in the Semi-Arid Region of Pakistan Using Multispectral Remote Sensing
AU  - Zeeshan Zafar
AU  - Shoaib Farooq
AU  - Muhammad Irfan Ahamad
AU  - Muhammad Sajid Mehmood
AU  - Nasir Abbas
AU  - Summar Abbas
Y1  - 2020/12/04
PY  - 2020
N1  - https://doi.org/10.11648/j.optics.20200901.11
DO  - 10.11648/j.optics.20200901.11
T2  - Optics
JF  - Optics
JO  - Optics
SP  - 1
EP  - 7
PB  - Science Publishing Group
SN  - 2328-7810
UR  - https://doi.org/10.11648/j.optics.20200901.11
AB  - Remote sensing (RS) is a tool in modern years for the monitoring of crops. Normalized Difference Vegetation Index (NDVI) derived from multi-temporal satellite imagery facilitates the analysis of vegetation growth stage, while comparing it with field/historical departmental yield data. Historical metrological data is also very useful in crop yield estimation especially in arid/semi-arid climatic zones. The metrological conditions including rainfall, humidity, sunshine, and temperature plays vital role in the growth and yield of crops; thus, the climatic conditions can adversely affect the crop yields if are not in accordance with growth requirement of a particular crop. Most of the agricultural land of Punjab province is in semi-arid climatic zone including Chakwal, Jhelum, Mianwali, Khushab, Sargodha, Mandi Bahauddin, Gujranwala, Hafizabad, Shiekhupura, Nankana Sahib, Lahore, Kasur, Faislabad and Chiniot districts. The study will investigate the impact of climate change on wheat crop yields of Chakwal district using advanced RS techniques from 1990 to 2015. Image classification to determine arable and non-arable lands; estimation of changes in temperature using thermal bands of satellite imagery, comparison of historical NDVI profiles; use of climatic data along with nonspatial departmental data for crop yield estimation and drawing its relationship with climatic variables.
VL  - 9
IS  - 1
ER  -

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Author Information

Zeeshan Zafar

College of Urban and Environmental Sciences, Northwest University, Xi’an, China
Shoaib Farooq

Institute of Geo-Information and Earth Observation, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi, Pakistan
Muhammad Irfan Ahamad

College of Urban and Environmental Sciences, Northwest University, Xi’an, China
Muhammad Sajid Mehmood

College of Urban and Environmental Sciences, Northwest University, Xi’an, China
Nasir Abbas

College of Urban and Environmental Sciences, Northwest University, Xi’an, China
Summar Abbas

Geological Survey of Pakistan (GSP), Quetta, Pakistan

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APA Style

Zeeshan Zafar, Shoaib Farooq, Muhammad Irfan Ahamad, Muhammad Sajid Mehmood, Nasir Abbas, et al. (2020). Modelling the Climate Change on Crop Estimation in the Semi-Arid Region of Pakistan Using Multispectral Remote Sensing. Optics, 9(1), 1-7. https://doi.org/10.11648/j.optics.20200901.11

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ACS Style

Zeeshan Zafar; Shoaib Farooq; Muhammad Irfan Ahamad; Muhammad Sajid Mehmood; Nasir Abbas, et al. Modelling the Climate Change on Crop Estimation in the Semi-Arid Region of Pakistan Using Multispectral Remote Sensing. Optics. 2020, 9(1), 1-7. doi: 10.11648/j.optics.20200901.11

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AMA Style

Zeeshan Zafar, Shoaib Farooq, Muhammad Irfan Ahamad, Muhammad Sajid Mehmood, Nasir Abbas, et al. Modelling the Climate Change on Crop Estimation in the Semi-Arid Region of Pakistan Using Multispectral Remote Sensing. Optics. 2020;9(1):1-7. doi: 10.11648/j.optics.20200901.11

Copy | Download

@article{10.11648/j.optics.20200901.11,
  author = {Zeeshan Zafar and Shoaib Farooq and Muhammad Irfan Ahamad and Muhammad Sajid Mehmood and Nasir Abbas and Summar Abbas},
  title = {Modelling the Climate Change on Crop Estimation in the Semi-Arid Region of Pakistan Using Multispectral Remote Sensing},
  journal = {Optics},
  volume = {9},
  number = {1},
  pages = {1-7},
  doi = {10.11648/j.optics.20200901.11},
  url = {https://doi.org/10.11648/j.optics.20200901.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.optics.20200901.11},
  abstract = {Remote sensing (RS) is a tool in modern years for the monitoring of crops. Normalized Difference Vegetation Index (NDVI) derived from multi-temporal satellite imagery facilitates the analysis of vegetation growth stage, while comparing it with field/historical departmental yield data. Historical metrological data is also very useful in crop yield estimation especially in arid/semi-arid climatic zones. The metrological conditions including rainfall, humidity, sunshine, and temperature plays vital role in the growth and yield of crops; thus, the climatic conditions can adversely affect the crop yields if are not in accordance with growth requirement of a particular crop. Most of the agricultural land of Punjab province is in semi-arid climatic zone including Chakwal, Jhelum, Mianwali, Khushab, Sargodha, Mandi Bahauddin, Gujranwala, Hafizabad, Shiekhupura, Nankana Sahib, Lahore, Kasur, Faislabad and Chiniot districts. The study will investigate the impact of climate change on wheat crop yields of Chakwal district using advanced RS techniques from 1990 to 2015. Image classification to determine arable and non-arable lands; estimation of changes in temperature using thermal bands of satellite imagery, comparison of historical NDVI profiles; use of climatic data along with nonspatial departmental data for crop yield estimation and drawing its relationship with climatic variables.},
 year = {2020}
}

Copy | Download

TY  - JOUR
T1  - Modelling the Climate Change on Crop Estimation in the Semi-Arid Region of Pakistan Using Multispectral Remote Sensing
AU  - Zeeshan Zafar
AU  - Shoaib Farooq
AU  - Muhammad Irfan Ahamad
AU  - Muhammad Sajid Mehmood
AU  - Nasir Abbas
AU  - Summar Abbas
Y1  - 2020/12/04
PY  - 2020
N1  - https://doi.org/10.11648/j.optics.20200901.11
DO  - 10.11648/j.optics.20200901.11
T2  - Optics
JF  - Optics
JO  - Optics
SP  - 1
EP  - 7
PB  - Science Publishing Group
SN  - 2328-7810
UR  - https://doi.org/10.11648/j.optics.20200901.11
AB  - Remote sensing (RS) is a tool in modern years for the monitoring of crops. Normalized Difference Vegetation Index (NDVI) derived from multi-temporal satellite imagery facilitates the analysis of vegetation growth stage, while comparing it with field/historical departmental yield data. Historical metrological data is also very useful in crop yield estimation especially in arid/semi-arid climatic zones. The metrological conditions including rainfall, humidity, sunshine, and temperature plays vital role in the growth and yield of crops; thus, the climatic conditions can adversely affect the crop yields if are not in accordance with growth requirement of a particular crop. Most of the agricultural land of Punjab province is in semi-arid climatic zone including Chakwal, Jhelum, Mianwali, Khushab, Sargodha, Mandi Bahauddin, Gujranwala, Hafizabad, Shiekhupura, Nankana Sahib, Lahore, Kasur, Faislabad and Chiniot districts. The study will investigate the impact of climate change on wheat crop yields of Chakwal district using advanced RS techniques from 1990 to 2015. Image classification to determine arable and non-arable lands; estimation of changes in temperature using thermal bands of satellite imagery, comparison of historical NDVI profiles; use of climatic data along with nonspatial departmental data for crop yield estimation and drawing its relationship with climatic variables.
VL  - 9
IS  - 1
ER  -

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