Relationship Between Normalized Difference Vegetation Index (NDVI) and Rice Growth Phases in Danda Jaya Swamp Irrigation Area Regency Barito Kuala

Abstract

One of the factors that influence the success of rice productivity is rice growth, from land preparation to harvesting. With remote sensing technology, the phase of rice growth can be known more quickly. The purpose of this study was to analyze the NDVI value as a representation of vegetation density characteristics and analyze cluster data grouping based on the results of the identification of the rice growth phase using Sentinel-2 Imagery in the 2019 planting season cycle in Danda Jaya Swamp Irrigation Area. The method used in this study is a quantitative descriptive method with the interpretation of Sentinel-2 Image. Image data were collected in the form of time series in 2019 and downloaded via the Google Earth Engine (GEE) platform. Rice productivity was calculated using NDVI to identify plant vegetation density. Then calculate the statistical zone using a GIS application to get the average NDVI value per rice field plot. NDVI values were analyzed using the K-means Cluster method for class determination. These results support the hypothesis that the time series NDVI value in the sentinel-2 image with a high spatial resolution (10 m) computed from the Google Earth Engine produces a strong correlation with the rice growth phase. The next research development is to analyze the estimation model of rice productivity on Sentinel-2 Image by utilizing the relationship between rice productivity and NDVI.