Reconstruction of Rainfall Patterns with the SpVAR Method: Spatial Analysis in DKI Jakarta
DOI:
10.29303/jppipa.v9i12.4895Published:
2023-12-20Downloads
Abstract
Unexpected rainfall is often a challenge for urban areas such as DKI Jakarta. Therefore, this study aims to establish a Spatial Vector Autoregressive (SpVAR) model to analyze rainfall data in DKI Jakarta from 2017 to 2021. This study used three endogenous variables: the amount of rainfall, air temperature and humidity. The use of the SpVAR method with uniform spatial weighting in the DKI Jakarta area was chosen to provide an initial picture of the potential for spatial interactions between various locations in a complex climate context. This method provides valuable insight into the possibility of spatial dependence during climate change in DKI Jakarta. The SpVAR (1.3) model is based on the VAR (p) model by limiting the spatial orders to one. Parameters of the SpVAR model (1.3) were estimated using the FIML method to identify significant factors in the influence of rainfall in the region. The results showed that the SpVAR model (1.3) shows that rainfall, air temperature and humidity in one location are affected by the same variables in other locations. However, not all of them significantly affect five areas in DKI Jakarta Province. This study confirms the effectiveness of the SpVAR method in analyzing spatial patterns of rainfall, provides essential insights for understanding climate, and supports decision-making that is more responsive to urban disasters in the future.
Keywords:
Rainfall Spatial vector autoregressive Uniform VARReferences
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