TY - JOUR
T1 - Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020
AU - Hussain, Sajjad
AU - Qin, Shujing
AU - Nasim, Wajid
AU - Bukhari, Muhammad Adnan
AU - Mubeen, Muhammad
AU - Fahad, Shah
AU - Raza, Ali
AU - Abdo, Hazem Ghassan
AU - Tariq, Aqil
AU - Mousa, B. G.
AU - Mumtaz, Faisal
AU - Aslam, Muhammad
N1 - Funding Information:
The research is financially supported by the National Natural Science Foundation of China (52209068), Postdoctoral Research Foundation of China (2020M682477), and the Fundamental Research Funds for the Central Universities (2042021kf0053).
Publisher Copyright:
© 2022 by the authors.
PY - 2022/9/30
Y1 - 2022/9/30
N2 - 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.
AB - 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.
KW - climate change
KW - GIS
KW - normalized difference vegetation index
KW - remote sensing
KW - Southern Punjab
UR - http://www.scopus.com/inward/record.url?scp=85140430447&partnerID=8YFLogxK
U2 - 10.3390/atmos13101609
DO - 10.3390/atmos13101609
M3 - Article
SN - 2073-4433
VL - 13
SP - 1609
JO - Atmosphere
JF - Atmosphere
IS - 10
M1 - 1609
ER -
