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All Journal International Journal of Advances in Applied Sciences Jurnal Ilmiah MITSU (Media Informasi Teknik Sipil Universitas Wiraraja)
Dewi, Listya
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Civil Engineering, Building, Construction & Architecture Decision Sciences, Operations Research & Management Earth & Planetary Sciences Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics Transportation

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PENGELOMPOKAN KELAS TUTUPAN LAHAN DI KABUPATEN JEMBRANA BERDASARKAN EKSTRAKSI CITRA LANDSAT 8 Aryastana, Putu; Dewi, Listya; Sinda, Longginus; Budha, I Ketut
Jurnal Ilmiah MITSU (Media Informasi Teknik Sipil Universitas Wiraraja) Vol 12 No 1 (2024): Jurnal Ilmiah MITSU
Publisher : Fakultas Teknik, Universitas Wiraraja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24929/ft.v12i1.2509

Abstract

The rapid development of infrastructure as it is today has resulted in the closure of green land or vegetation areas. Jembrana Regency is one of the districts that has experienced a shift in land function due to infrastructure development activities and community needs in land use. This study aims to compare the level of vegetation density and the area of density of vegetation area using the NDVI vegetation index method. The results of land cover classification with Landsat 8 imagery in 2016 and 2022 in Jembrana Regency as a data source to analyze NDVI values using the Supervised Classification method resulted in 5 classes consisting of forests, settlements, vacant land, rice fields, and water bodies. The results of the study explained that there was a decrease in land cover in 2016 and 2022 in forests/vegetation, namely 41.76 km2 or 6.23%, , and water bodies by 0.07 km2 or 5.34% . However, on the other hand, there was an increase in the area of land cover in the class of rice fields, settlements, and vacant land by 21,74 km2 or 38,86%; 14.95 km2 or 50.18%; dan 5,14 km2 or 6,05%.. In addition, the overall accuracy test result of land cover classification is 87.50%. The results showed that the map classified by Landsat 8 imagery could be used.
A study of rainfall thresholds for landslides in Badung Regency using satellite-derived rainfall grid datasets Aryastana, Putu; Dewi, Listya; Wahyuni, Putu Ika
International Journal of Advances in Applied Sciences Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i2.pp197-208

Abstract

Integrating field rainfall data with satellite data improves data accuracy and overcomes rainfall data limitations for rain thresholds. Integration can involve field rainfall data, satellite rainfall data, or a different satellite dataset. Merging these rainfall data sources provides more spatial coverage of satellite data. To determine how well rainfall thresholds predict rainfall-triggered landslides, the threshold model must be validated. This study will evaluate satellite rainfall data before and after integration in developing a rainfall threshold model for landslide prediction in Badung Regency. To do so, the study used a cumulative rainfall threshold over 3, 7, 15, and 30 days and two rainfall satellite products (integrated merged multi-satellite retrievals (IMERG) and precipitation estimation from remotely sensed information using artificial neural networks (PERSIANN)). Median, first, and third quartiles were used to set thresholds. The area under the curve (AUC) was calculated to validate rainfall threshold outcomes using receiver operating characteristic (ROC) curves. Analysis showed that integrating satellite rainfall data into the rainfall threshold model for landslide prediction yields better results than other methods. An AUC value of 0.903 (90.3%) for the 30-day cumulative rainfall thresholds supports this claim. This model could be a good input for a landslide early warning system in Badung Regency.
Co-Authors Budha, I Ketut Putu Aryastana PUTU IKA WAHYUNI Sinda, Longginus