EXAMINING THE NDVI-RAINFALL RELATIONSHIP UNDER HIGH ENSO EVENT INFLUENCE USING GEOGRAPHICALLY WEIGHTED REGRESSION IN PENINSULAR MALAYSIA

被引:0
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作者
Sa'adi, Zulfaqar [1 ,2 ]
Alias, Nor Eliza [1 ,2 ]
Yusop, Zulkifli [1 ,2 ]
Mazilamani, Lelavathy Samikan [2 ]
Houmsi, Mohamad Rajab [3 ,4 ]
Houmsi, Lama Nasrallah [5 ]
Shahid, Shamsuddin [6 ]
Aris, Azmi [1 ,2 ]
Ramli, Muhammad Wafiy Adli [7 ]
Khan, Najeebullah [8 ]
Shukla, Prabhakar [9 ]
机构
[1] Univ Teknol Malaysia, Ctr Environm Sustainabil & Water Secur, Res Inst Sustainable Environm, Utm Skudai 81310, Johor Bahru, Malaysia
[2] Univ Teknol Malaysia, Fac Civil Engn, Dept Water & Environm Engn, Utm Skudai 81310, Johor Bahru, Malaysia
[3] Univ Teknol Malaysia, Ctr River & Coastal Engn CRCE, Utm Sekudai 81310, Johor, Malaysia
[4] Al Ayen Univ, Sci Res Ctr, New Era & Dev Civil Engn Res Grp, Thi Qar 64001, Nasiriyah, Iraq
[5] Aleppo Univ, Coll Econ, Finance & Banking Dept, Aleppo Halab Syria 15310, Mouhafaza, Syria
[6] Univ Teknol Malaysia, Fac Engn, Sch Civil Engn, Dept Water & Environm Engn, Johor Baharu 81310, Malaysia
[7] Univ Sains Malaysia, Sch Humanities, Geog Sect, George Town 11700, Malaysia
[8] Univ Teknol Malaysia, Fac Civil Engn, Utm Skudai 81310, Johor Bahru, Malaysia
[9] Indian Inst Technol IIT Delhi, Dept Civil Engn, Delhi 110016, India
来源
IGARSS 2024-2024 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, IGARSS 2024 | 2024年
基金
英国科研创新办公室;
关键词
CMORPH; ENSO; Geographically Weighted Regression; NDVI; Peninsular Malaysia; PERFORMANCE; FOREST; MODEL;
D O I
10.1109/IGARSS53475.2024.10642469
中图分类号
学科分类号
摘要
The NDVI and rainfall connections are complex, spatially non- stationary, non-linear, and scale-dependent. To address this, a local modelling approach, Geographically Weighted Regression (GWR) was employed, to accommodate for spatial variability. By employing Climate Prediction Center morphing method (CMORPH) satellite dataset, this study investigates the Normalized Difference Vegetation Index (NDVI)-rainfall relationship in Peninsula Malaysia (PM), focusing on periods influenced by El Nino-Southern Oscillation (ENSO). The outcomes of Moran's I spatial autocorrelation confirm the presence of rainfall spatial variability which endorses the application of the GWR model. The findings suggest that there is a contrasting spatial relationship between NDVI and rainfall during the El Nino events, but positive relationship during the La Nina events. The southern region generally exhibited a positive relationship, while the northern and northeastern regions showed negative or weak associations. These results indicate that for a more precise, localized representation of a consistent relationship (either increasing or decreasing), it is essential to identify specific regions under the influence of El Nino.
引用
收藏
页码:1908 / 1913
页数:6
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