Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020
Sajjad Hussain,
Shujing Qin,
Wajid Nasim,
Muhammad Adnan Bukhari,
Muhammad Mubeen,
Shah Fahad,
Ali Raza,
Hazem Ghassan Abdo,
Aqil Tariq,
B. G. Mousa,
Faisal Mumtaz,
Muhammad Aslam
Affiliations
Sajjad Hussain
Department of Environmental Sciences, COMSATS University Islamabad, Vehari Campus, Vehari 61100, Pakistan
Shujing Qin
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
Wajid Nasim
Department of Agronomy, University College of Agriculture and Environmental Sciences, The Islamia University of Bahawalpur (IUB), Bahawalpur 63100, Pakistan
Muhammad Adnan Bukhari
Department of Agronomy, University College of Agriculture and Environmental Sciences, The Islamia University of Bahawalpur (IUB), Bahawalpur 63100, Pakistan
Muhammad Mubeen
Department of Environmental Sciences, COMSATS University Islamabad, Vehari Campus, Vehari 61100, Pakistan
Shah Fahad
Department of Agronomy, The University of Haripur, Haripur 22620, Pakistan
Ali Raza
School of Agriculture Engineering, Jiangsu University, Zhenjiang 212013, China
Hazem Ghassan Abdo
Geography Department, Faculty of Arts and Humanities, Damascus University, Damascus P.O. Box 30621, Syria
Aqil Tariq
Department of Wildlife, Fisheries and Aquaculture, College of Forest Resources, Mississippi State University, 775 Stone Boulevard, Stackwelly, MS 39762, USA
B. G. Mousa
Department of Mining and Petroleum Engineering, Faculty of Engineering, Al-Azhar University, Cairo 11884, Egypt
Faisal Mumtaz
State Key Laboratory of Remote Sensing Sciences, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Muhammad Aslam
School of Computing Engineering and Physical Sciences, University of West of Scotland, Paisley G72 0LH, UK
Anthropogenic activities and natural climate changes are the central driving forces of global ecosystems and agriculture changes. Climate changes, such as rainfall and temperature changes, have had the greatest impact on different types of plant production around the world. In the present study, we investigated the spatiotemporal variation of major crops (cotton, rice, wheat, and sugarcane) in the District Vehari, Pakistan, from 1984 to 2020 using remote sensing (RS) technology. The crop identification was pre-processed in ArcGIS software based on Landsat images. After pre-processing, supervised classification was used, which explains the maximum likelihood classification (MLC) to identify the vegetation changes. Our results showed that in the study area cultivated areas under wheat and cotton decreased by almost 5.4% and 9.1% from 1984 to 2020, respectively. Vegetated areas have maximum values of NDVI (>0.4), and built-up areas showed fewer NDVI values (0 to 0.2) in the District Vehari. During the Rabi season, the temperature was increased from 19.93 °C to 21.17 °C. The average temperature was calculated at 34.28 °C to 35.54 °C during the Kharif season in the District Vehari. Our results showed that temperature negatively affects sugarcane, rice, and cotton crops during the Rabi season, and precipitation positively affects sugarcane, rice, and cotton crops during the Kharif season in the study area. Accurate and timely assessment of crop estimation and relation to climate change can give very useful information for decision-makers, governments, and planners in formulating policies regarding crop management and improving agriculture yields.
