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International Conference on

Recent Trends in Environmental Sustainability

ESCON22/CDMP/16
Spatio-temporal variation of cotton in Southern Punjab using different satellites

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Muhammad Imran , Muhammad Mubeen , Saeed Ahmad Qaisrani , Muhammad Akram ,
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Mazhar Ali , Sajjad Hussain , Rizwan Tariq , Ali Ijaz , Samra Tariq , Mazhar Hussain
Department of Environmental Sciences, COMSATS University Islamabad, Vehari Campus-
Pakistan
Correspondence: imran.jindwadda@gmail.com
Abstract
Cotton is Pakistan's second most important crop after wheat. Remote Sensing techniques and
data, combined with Geographic Information System (GIS), are essential to analyse and
characterize cotton area and its changes over a certain period of time. Cropping system
classification was based on Satellite imageries of Landsat and Sentinel. Data were pre-
processed in some GIS software like ERDAS imagine and Arc GIS for layer stacking,
mosaicking and subsetting of images. After pre-processing, the supervised classification
scheme was applied on temporal satellite datasets for the cropping year 2005, 2008, 2011,
2014, 2017 and 2020 which explains the maximum likelihood algorithm using ERDAS imagine
software to identify agricultural land use classification changes observed over a specific area.
The results showed that cotton area was decreased 16302.6 ha (14.74 %) during 2005 to 2020
in tahsil Burewala. Similarly, there was 20106.54 ha (12.45 %) reduction in cotton area in tahsil
Mailsi and reduction of 17932,86 ha (13.15 %) in tehsil Vehari during the corresponding
period. The NDVI value was significantly low (~0.2 to 0.30) during June and July due to the
sowing phase and was high (~0.51 to 0.55) in the month September and October representing
high vegetation. Overall, the average NDVI value of study area show that it has heavy
vegetation cover and sufficient amount of water bodies with very less amount of bare soil.
Cotton production is gradually becoming a challenge for national governments. Hence,
verification and traceability of good agronomic practices is significant and to attain this, the
requirements for spatial data are estimated to grow quickly.

Keywords: Gossypium hirsutum L., Vehari; Landsat; Sentinel; NDVI; Remote Sensing; GIS

Department of Environmental Sciences, COMSATS University Islamabad, Vehari Campus

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