Volume 9, Issue 1, June 2020, Page: 1-7
Modelling the Climate Change on Crop Estimation in the Semi-Arid Region of Pakistan Using Multispectral Remote Sensing
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
Received: Oct. 30, 2020;       Accepted: Nov. 23, 2020;       Published: Dec. 4, 2020
DOI: 10.11648/j.optics.20200901.11      View  78      Downloads  18
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.
Metrological Data, Remote Sensing, Crop Yield Estimation, Semi-arid, Chakwal
To cite this article
Zeeshan Zafar, Shoaib Farooq, Muhammad Irfan Ahamad, Muhammad Sajid Mehmood, Nasir Abbas, Summar Abbas, Modelling the Climate Change on Crop Estimation in the Semi-Arid Region of Pakistan Using Multispectral Remote Sensing, Optics. Vol. 9, No. 1, 2020, pp. 1-7. doi: 10.11648/j.optics.20200901.11
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This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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