Evaluating the Influence of La Niña on Tropical Greening in Borneo Through Geographically Weighted Regression
DOI:
https://doi.org/10.11113/jagst.v5n1.102Keywords:
Borneo, CMORPH, ENSO, Geographically Weighted Regression, NDVI, RainfallAbstract
This study evaluates the influence of the 2007 strong La Niña event on tropical greening in Borneo by using geographically weighted regression (GWR) to assess spatial variations in vegetation response based on remotely sensed NDVI data. Moran’s I value, ranging from 0.012 to 0.034, indicates low positive spatial autocorrelation and significant spatial clustering of rainfall across Borneo, underscoring the importance of incorporating spatial factors in the analysis. The ANOVA test shows that each monthly GWR model significantly outperforms the Ordinary Least Squares (OLS) model (F > 1, p < 0.05), with September, October, and December exhibiting the strongest fit (Quasi-global R²: 0.2744, 0.3125, 0.2899; RSS: 0.2626, 0.2539, 0.2785). During the Northeast Monsoon (NEM), the rainfall-NDVI relationship is strongest, with maximum R2 values peaking at 0.74 in December, followed by 0.54 in February and 0.27 in November. Central and southern Borneo show the highest correlations, indicating that rainfall is a key driver of vegetation growth. During the Southwest Monsoon (SWM), the rainfall-NDVI relationship weakens, with maximum R2 dropping to 0.36 in August before rising to 0.49 in September. The lowest R2 (0.00–0.04) in northern and eastern Borneo reflects reduced rainfall influence due to orographic rain shadow effects from the Crocker Range and East Kalimantan highlands. Western Borneo’s peatlands and riparian zones retain moisture and sustain vegetation, while degraded forests, mixed land use, and plantations in the north and east show more significant NDVI fluctuations due to lower soil moisture retention. The predicted NDVI values during the 2007 La Niña event ranged from 0.5 to 0.9, with the model effectively capturing seasonal and spatial variations across Borneo, particularly during peak rainfall. However, it missed localized fluctuations and smaller-scale variations in February and November due to elevation, soil and vegetation type, and extreme rainfall variability. These findings suggest that local factors mediate La Niña’s influence on tropical greening, emphasizing the importance of spatial analysis in understanding climate-vegetation interactions under extreme conditions.