Abstract

Comprehending the dynamics of paddy productivity is imperative for enhancing the efficacy of agricultural land developments. This study provides the application of principal component analysis (PCA) as a method for visualizing the spatial-temporal changes in paddy productivity. The analysis is conducted using the 8-day NDVI (normalized difference vegetation index) anomaly data of MODIS (Moderate Resolution Imaging Spectroradiometer) data spanning the period from 2000 to 2020. The regencies of Karawang, Subang, and Indramayu on the north coast of Java island are chosen as the study area because of their top rice production areas in Indonesia. The results show that the first leading PCA of the NDVI anomaly is related to the interannual variability of paddy productivity with 3-4 year cycles. The spatial and temporal dynamics of the first mode of eigenvectors and principal component time series can generally be grouped into nine categories. Two important categories to note are category-1 (1 January – 19 March) and category-8 (12 September – 16 December). In category-1, the NDVI anomalies move from north to middle and middle to north areas in Karawang and Subang regencies, respectively. In Indramayu Regency, the NDVI anomalies relatively remain in almost all areas. In contrast, in category-8 the NDVI anomalies move from the middle to northern areas in Karawang, Subang, and Indramayu regencies.

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