Perbandingan Metode Soil Adjusted Vegetation Index (SAVI) dan Forest Canopy Density (FCD) untuk Identifikasi Tutupan Vegetasi (Kasus; Area Pembuatan Jalan Baru Singaraja-Mengwi)

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This research uses Landsat 8 OLI/TIRS image which objective to determine the accuracy level of SAVI method and FCD model in the identification of vegetation cover. It is done as an effort to assist in determining the right method of monitoring the change of vegetation cover in the forest area. Therefore, this research compares the vegetation index of Soil Adjusted Vegetation Index (SAVI) because it is able to suppress the background of the soil so that the vegetation cover is able to be displayed according to the conditions in the field. While the FCD model uses four variables such as; Advanced Vegetation Index (AVI), Bare Soil Index (BI), Shadow Index (SI), and thermal index using the Split-Windows Algorithm (SWA) method. Comparison results between SAVI and FCD models indicate that the higher accuracy of SAVI is 84% and FCD model is only 82%. It is possible because the limited use of research areas that show SAVI is superior due to heterogeneous conditions and it approaches the conditions in the field than the FCD model that is more group and only able to be realized in three classes. Based on the results, it was concluded that the vegetation index can be used in monitoring the limited area of research but it is also not absolute because it is possible that FCD model is better.