Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables

Kaleem Mehmood; Shoaib Ahmad Anees; Sultan Muhammad; Khadim Hussain; Fahad Shahzad; Qijing Liu; Mohammad Javed Ansari; Sulaiman Ali Alharbi; Waseem Razzaq Khan

doi:10.1038/s41598-024-62464-7

Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables

Sci Rep. 2024 May 23;14(1):11775. doi: 10.1038/s41598-024-62464-7.

Authors

Kaleem Mehmood^{1

2

3}, Shoaib Ahmad Anees⁴, Sultan Muhammad³, Khadim Hussain^{1

5}, Fahad Shahzad⁶, Qijing Liu^{7

8}, Mohammad Javed Ansari⁹, Sulaiman Ali Alharbi¹⁰, Waseem Razzaq Khan^{11

12

13}

Affiliations

¹ College of Forestry, Beijing Forestry University, Beijing, 100083, People's Republic of China.
² Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing, 100083, People's Republic of China.
³ Institute of Forest Science, University of Swat, Main Campus Charbagh, Swat, 19120, Pakistan.
⁴ Department of Forestry, The University of Agriculture, Dera Ismail Khan, 29050, Pakistan.
⁵ State Forestry and Grassland Administration Key Laboratory of Forest Resources and Environmental Management, Beijing Forestry University, Beijing, 100083, People's Republic of China.
⁶ Precision Forestry Key Laboratory of Beijing, Beijing Forestry University, Beijing, 100083, People's Republic of China.
⁷ College of Forestry, Beijing Forestry University, Beijing, 100083, People's Republic of China. liuqijing@bjfu.edu.cn.
⁸ Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing, 100083, People's Republic of China. liuqijing@bjfu.edu.cn.
⁹ Department of Botany, Hindu College Moradabad (Mahatma Jyotiba Phule Rohilkhand University Bareilly), Moradabad, 244001, India.
¹⁰ Department of Botany and Microbiology, College of Science King Saud University, P.O Box 2455, 11451, Riyadh, Saudi Arabia.
¹¹ Department of Forestry Science and Biodiversity, Faculty of Forestry and Environment, Universiti Putra Malaysia, 43400, Serdang, Malaysia. khanwaseem@upm.edu.my.
¹² Advanced Master in Sustainable Blue Economy, National Institute of Oceanography and Applied Geophysics - OGS, University of Trieste, 34127, Trieste, Italy. khanwaseem@upm.edu.my.
¹³ Institut Ekosains Borneo (IEB), Universiti Putra Malaysia Bintulu Campus, 97008, Sarawak, Malaysia. khanwaseem@upm.edu.my.

Abstract

This study assesses the relationships between vegetation dynamics and climatic variations in Pakistan from 2000 to 2023. Employing high-resolution Landsat data for Normalized Difference Vegetation Index (NDVI) assessments, integrated with climate variables from CHIRPS and ERA5 datasets, our approach leverages Google Earth Engine (GEE) for efficient processing. It combines statistical methodologies, including linear regression, Mann-Kendall trend tests, Sen's slope estimator, partial correlation, and cross wavelet transform analyses. The findings highlight significant spatial and temporal variations in NDVI, with an annual increase averaging 0.00197 per year (p < 0.0001). This positive trend is coupled with an increase in precipitation by 0.4801 mm/year (p = 0.0016). In contrast, our analysis recorded a slight decrease in temperature (- 0.01011 °C/year, p < 0.05) and a reduction in solar radiation (- 0.27526 W/m²/year, p < 0.05). Notably, cross-wavelet transform analysis underscored significant coherence between NDVI and climatic factors, revealing periods of synchronized fluctuations and distinct lagged relationships. This analysis particularly highlighted precipitation as a primary driver of vegetation growth, illustrating its crucial impact across various Pakistani regions. Moreover, the analysis revealed distinct seasonal patterns, indicating that vegetation health is most responsive during the monsoon season, correlating strongly with peaks in seasonal precipitation. Our investigation has revealed Pakistan's complex association between vegetation health and climatic factors, which varies across different regions. Through cross-wavelet analysis, we have identified distinct coherence and phase relationships that highlight the critical influence of climatic drivers on vegetation patterns. These insights are crucial for developing regional climate adaptation strategies and informing sustainable agricultural and environmental management practices in the face of ongoing climatic changes.

Keywords: Climatic variability; Cross wavelet transform; NDVI; Seasonal variations; Vegetation dynamics.

MeSH terms

Climate Change
Climate*
Environmental Monitoring / methods
Pakistan
Plant Development
Plants
Seasons*
Temperature