Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables
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...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Research
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/113375/ http://psasir.upm.edu.my/id/eprint/113375/1/113375.pdf |
| _version_ | 1848866204842721280 |
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| author | Mehmood, Kaleem Anees, Shoaib Ahmad Muhammad, Sultan Hussain, Khadim Shahzad, Fahad Liu, Qijing Ansari, Mohammad Javed Alharbi, Sulaiman Ali Khan, Waseem Razzaq |
| author_facet | Mehmood, Kaleem Anees, Shoaib Ahmad Muhammad, Sultan Hussain, Khadim Shahzad, Fahad Liu, Qijing Ansari, Mohammad Javed Alharbi, Sulaiman Ali Khan, Waseem Razzaq |
| author_sort | Mehmood, Kaleem |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T14:16:53Z |
| format | Article |
| id | upm-113375 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:16:53Z |
| publishDate | 2024 |
| publisher | Nature Research |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1133752024-11-22T03:32:16Z http://psasir.upm.edu.my/id/eprint/113375/ Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables Mehmood, Kaleem Anees, Shoaib Ahmad Muhammad, Sultan Hussain, Khadim Shahzad, Fahad Liu, Qijing Ansari, Mohammad Javed Alharbi, Sulaiman Ali Khan, Waseem Razzaq 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. Nature Research 2024 Article PeerReviewed text en cc_by_4 http://psasir.upm.edu.my/id/eprint/113375/1/113375.pdf Mehmood, Kaleem and Anees, Shoaib Ahmad and Muhammad, Sultan and Hussain, Khadim and Shahzad, Fahad and Liu, Qijing and Ansari, Mohammad Javed and Alharbi, Sulaiman Ali and Khan, Waseem Razzaq (2024) Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables. Scientific Reports, 14 (1). art. no. 11775. pp. 1-22. ISSN 2045-2322; eISSN: 2045-2322 https://www.nature.com/articles/s41598-024-62464-7 10.1038/s41598-024-62464-7 |
| spellingShingle | Mehmood, Kaleem Anees, Shoaib Ahmad Muhammad, Sultan Hussain, Khadim Shahzad, Fahad Liu, Qijing Ansari, Mohammad Javed Alharbi, Sulaiman Ali Khan, Waseem Razzaq Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables |
| title | Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables |
| title_full | Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables |
| title_fullStr | Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables |
| title_full_unstemmed | Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables |
| title_short | Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables |
| title_sort | analyzing vegetation health dynamics across seasons and regions through ndvi and climatic variables |
| url | http://psasir.upm.edu.my/id/eprint/113375/ http://psasir.upm.edu.my/id/eprint/113375/ http://psasir.upm.edu.my/id/eprint/113375/ http://psasir.upm.edu.my/id/eprint/113375/1/113375.pdf |