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All Journal Journal of Innovation Information Technology and Application (JINITA) Jurnal Sains dan Teknologi
Daniel Anthoni Sihasale
Universitas Pattimura
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Veterinary

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Analysis of Vegetation Index in Ambon City Using Sentinel-2 Satellite Image Data with Normalized Difference Vegetation Index (NDVI) Method based on Google Earth Engine Heinrich Rakuasa; Daniel Anthoni Sihasale
Journal of Innovation Information Technology and Application (JINITA) Vol 5 No 1 (2023): JINITA, June 2023
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v5i1.1869

Abstract

Rapid urban development and increasing human activities in the city can affect the decline in the Vegetation Index in Ambon City. The research aims to analyze the vegetation index using sentinel-2 satellite image data with the Normalized Difference Vegetation Index (NDVI) method based on Google Earth Engine (GEE) in Ambon City in 2023. This research uses Sentinel-2 Satellite Image data which is analyzed using Google Earth Engine with the Normalized Difference Vegetation Index (NDVI) method. The results showed that the vegetation index value in Ambon City in 2023 was the lowest value of -0.672381 and the highest value of 0.949297. The vegetation index value is then divided into four classes, namely No Vegetation which has an area of 4,448.99 ha or 13.67%, Low Vegetation areas have an area of 1,611.06 ha or 4.95%, Moderate Vegetation areas have an area of 2,895.12 ha or 8.89% and High Vegetation areas have an area of 23,597.35 ha or 72.49%. Analysis of the vegetation index in Ambon City is very important to maintain environmental balance and a healthy and sustainable environment.
Pemetaan Daerah Potensi Longsor di Kecamatan Leihitu Barat, Kabupaten Maluku Tengah, Menggunakan Metode Slope Morphology (SMORPH) Philia Christi Latue; Daniel Anthoni Sihasale; Heinrich Rakuasa
INSOLOGI: Jurnal Sains dan Teknologi Vol. 2 No. 3 (2023): Juni 2023
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v2i3.1912

Abstract

Landslide prone area mapping is an important step in mitigation and natural disaster management efforts in West Leihitu Sub-district, Central Maluku Regency. This research aims to map landslide prone areas in West Leihitu District, Central Maluku Regency, using Slope Morphology (SMORPH) method. This research uses DEMNAS data. The Slope Morphology (SMORPH) method was used in this research to overlay the slope map and slope shape to produce a map of landslide prone areas in West Leihitu Sub-district. The results showed that very low landslide potential class has an area of 465.40 ha (4.47%), low landslide potential class has an area of 4,232.96 ha or 40.63%, medium landslide potential class has an area of 2,524.30 ha or 24.23% and high landslide potential class has an area of 3196.19 ha or 30.68%. The results of this research are expected to be useful for the government and community in West Leihitu Sub-district, Central Maluku Regency in mitigating landslides in the future.
Co-Authors Heinrich Rakuasa Philia Christi Latue