Estimation of fractional vegetation cover dynamics based on satellite remote sensing in pakistan: A comprehensive study on the FVC and its drivers
Journal of King Saud University - Science, ISSN: 1018-3647, Vol: 34, Issue: 3, Page: 101848
2022
- 29Citations
- 26Captures
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Article Description
The present investigation exposes the significant variations of Fractional Vegetation Cover (FVC) and drivers from year 2003 to 2013 in Pakistan. It is directly calculated by remote-sensing data using Moderate Resolution Imaging Spectroradiometer-Normalized Difference Vegetation Index (MODIS-NDVI) and Compound Night Light Index/Defense Meteorological Program/Operational Line-Scan System (CNLI/DMSP/OLS). The spatial patterns of FVC variation are mainly categorized into three levels, low (<10%), medium (40%) and high (70%), with consequent findings. The FVC time series analysis exhibited the fitting curve with straight lines at 0.29 (29%). These findings displayed the utmost annual mean values 26% to 31% and 28% and 29% correspond to level 70% and 40%, respectively. Among all levels, level 10% has the lowest mean. The trend analysis displayed the low FVC for the southwest and south-eastern regions. This is attributed to industrialization, urbanization, land use, land cover change, and related climatic factors: the northeast and the northwest areas displayed medium and high FVC due to less human disturbance. Using different remotely sensed data, human activities (industrialization and urbanization, etc.) and climatic factors such as rainfall and temperature are considered driving factors of FVC dynamics. Finally, the correlation value of the coefficient verified the link between climatic factors, FVC and CNLI. These findings present the positive correlation of FVC with rainfall and the negative with compounded night light index and temperature.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S1018364722000295; http://dx.doi.org/10.1016/j.jksus.2022.101848; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85124005792&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S1018364722000295; https://dx.doi.org/10.1016/j.jksus.2022.101848
Elsevier BV
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