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Journal : Journal of Data Analytics, Information, and Computer Science (JDAICS)

IDENTIFICATION OF POTENTIAL LANDSLIDE AREAS IN NUSANIWE SUB-DISTRICT USING SLOPE MORPHOLOGY METHOD Latue, Philia Christi; Rakuasa, Heinrich
Journal of Data Analytics, Information, and Computer Science Vol. 1 No. 3 (2024): Juli
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jdaics.v1i3.750

Abstract

This study aims to identify landslide-prone areas in Nusaniwe District using the Slope Morphology Method (SMORPH), which is based on slope and slope shape analysis. The research method uses the Slope Morphology Method (SMORPH) to assess landslide potential in Nusaniwe District. The analysis was carried out by mapping the slope gradient and slope shape in the area to determine areas at high risk of landslides. Topographic and geological data were collected and analyzed to identify factors that contribute to landslide risk. The results of the analysis show that  complex geological and topographic conditions in Nusaniwe District increase the risk of landslides. Areas with high slope gradients and steep slope shapes are identified as the most landslide-prone areas. This assessment revealed a significant relationship between slope gradient, slope shape, and landslide potential in the area. The conclusion is that the analysis of slope and slope shape using the Slope Morphology Method (SMORPH) is effective in identifying landslide-prone areas in Nusaniwe District. To reduce landslide risk, interdisciplinary collaboration, community education, and development of effective mitigation strategies are needed. These findings provide a basis for planning and implementing landslide prevention measures in areas with similar conditions. Keywords: Landslide, Nusaniwe, Slope Morphology
SPATIAL TEMPORAL ANALYSIS OF LAND SURFACE TEMPERATURE CHANGES IN AMBON ISLAND FROM LANDSAT 8 IMAGE DATA USING GEOGLE EARTH ENGINE Latue, Philia Christi; Rakuasa, Heinrich
Journal of Data Analytics, Information, and Computer Science Vol. 1 No. 3 (2024): Juli
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jdaics.v1i3.751

Abstract

This study aims to analyze land surface temperature changes on Ambon Island using Landsat 8 imagery data and Google Earth Engine. The research method involves the use of Ambon Island boundary data from the Geospatial Information Agency (BIG) as well as Landsat 8 Collection 2 Tier 1 and Real-Time satellite image data that have been calibrated to reflect the reflectance of the Earth's surface to the atmosphere. The analysis steps include temperature conversion from Kelvin to Celsius, land surface temperature classification, and data export to Arc GIS software. The results showed an increase in land surface temperature associated with urban development in Ambon City, highlighting the importance of sustainable urban planning and good resource management to mitigate the negative impacts of land surface temperature increase and support adaptation to climate change. Keywords: Ambon Island, Geogle Earth Engine, Land Surface Temperature