Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020
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...
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MDPI AG
2022-09-01
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author | 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 |
author_facet | 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 |
author_sort | Sajjad Hussain |
collection | DOAJ |
description | 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. |
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language | English |
last_indexed | 2024-03-09T20:43:22Z |
publishDate | 2022-09-01 |
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series | Atmosphere |
spelling | doaj.art-082db6d9680e4f3a868885e6d1d7e7b92023-11-23T22:50:54ZengMDPI AGAtmosphere2073-44332022-09-011310160910.3390/atmos13101609Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020Sajjad Hussain0Shujing Qin1Wajid Nasim2Muhammad Adnan Bukhari3Muhammad Mubeen4Shah Fahad5Ali Raza6Hazem Ghassan Abdo7Aqil Tariq8B. G. Mousa9Faisal Mumtaz10Muhammad Aslam11Department of Environmental Sciences, COMSATS University Islamabad, Vehari Campus, Vehari 61100, PakistanState Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, ChinaDepartment of Agronomy, University College of Agriculture and Environmental Sciences, The Islamia University of Bahawalpur (IUB), Bahawalpur 63100, PakistanDepartment of Agronomy, University College of Agriculture and Environmental Sciences, The Islamia University of Bahawalpur (IUB), Bahawalpur 63100, PakistanDepartment of Environmental Sciences, COMSATS University Islamabad, Vehari Campus, Vehari 61100, PakistanDepartment of Agronomy, The University of Haripur, Haripur 22620, PakistanSchool of Agriculture Engineering, Jiangsu University, Zhenjiang 212013, ChinaGeography Department, Faculty of Arts and Humanities, Damascus University, Damascus P.O. Box 30621, SyriaDepartment of Wildlife, Fisheries and Aquaculture, College of Forest Resources, Mississippi State University, 775 Stone Boulevard, Stackwelly, MS 39762, USADepartment of Mining and Petroleum Engineering, Faculty of Engineering, Al-Azhar University, Cairo 11884, EgyptState Key Laboratory of Remote Sensing Sciences, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaSchool of Computing Engineering and Physical Sciences, University of West of Scotland, Paisley G72 0LH, UKAnthropogenic 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.https://www.mdpi.com/2073-4433/13/10/1609climate changeGISnormalized difference vegetation indexSouthern Punjabremote sensing |
spellingShingle | 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 Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020 Atmosphere climate change GIS normalized difference vegetation index Southern Punjab remote sensing |
title | Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020 |
title_full | Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020 |
title_fullStr | Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020 |
title_full_unstemmed | Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020 |
title_short | Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020 |
title_sort | monitoring the dynamic changes in vegetation cover using spatio temporal remote sensing data from 1984 to 2020 |
topic | climate change GIS normalized difference vegetation index Southern Punjab remote sensing |
url | https://www.mdpi.com/2073-4433/13/10/1609 |
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