Spatio-Temporal Analysis of Water Hyacinth Density (Eichhornia crassipes) in Lake Rawa Pening 2019 - 2023 Using NDVI Algorithm on Google Earth Engine (GEE)

Abstract Water hyacinth (Eichhornia crassipes) is an aquatic plant that floats in freshwater waters that has the ability to grow very fast and is invasive. This plant is able to reproduce vegetatively and generatively and is able to double its population within two weeks so that it can endanger the ecosystem in the waters. The purpose of this research is to map the distribution pattern, dynamics of changes in vegetation density and changes in water hyacinth area with spatial-temporal techniques using remote sensing technology processed using GEE in Lake Rawa Pening. The satellite image used is Sentinel level-2A with high spatial resolution with a recording time of May 2019 - 2023. This study uses the NDVI method to measure the greenness of vegetation and help identify the density of water hyacinth vegetation. The results of the vegetation density index show that there are five classification for vegetation density levels, and the outcomes of the accuracy test that was conducted range from -0.15 to 0.94. obtained an overall accuracy of 86.6% and a kappa coefficient value of 0.81. These results show that the use of Sentinel 2A imagery can be used for vegetation density index mapping using the NDVI algorithm in GEE with a good level of accuracy and conformity between map and field and the image processing that has been done is appropriate.