SPATIAL ANALYSIS OF LANDSLIDE DETECTION USING THE RELATIVE DIFFERENT NDVI (rdNDVI) METHOD THROUGH THE GOOGLE EARTH ENGINE PLATFORM (CASE STUDY OF SUKAMAKMUR DISTRICT, BOGOR REGENCY)
DOI:
https://doi.org/10.53840/ejpi.v12i5.325Keywords:
Landslide; rdNDVI; Remote Sensing; Sentinel-2A; Google Earth EngineAbstract
One of the areas prone to landslide disasters In Bogor Regency, Sukamakmur District. The area is experiencing serious problems due to the high frequency of landslide disasters, such as land damage, loss of homes, and negative impacts on the community's economy. From 2020 to 2023, a total of 57 landslide incidents were recorded in this region. Remote sensing technology can be used to obtain information about objects on the Earth's surface, analyze and map areas that are prone to landslides, and those affected by landslides. The research uses the Relative Different NDVI (rdNDVI) method in Google Earth Engine (GEE), utilizing Sentinel-2A time series images from 2019 and 2023 for vegetation change identification. Data processing in GEE includes image preprocessing, NDVI calculation, and rdNDVI calculation. The result of this research is the mapping of rdNDVI by visualizing the areas affected by landslide detection. The areas most affected by landslides in 2023 are Wargajaya and Sukawangi villages. With the results of the threshold slope accuracy test, the best accuracy achieved was 86.6% (10% slope) and 86% (15% slope).
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References
A. J. Viera and J. M. Garrett, "Understanding the Interobserver Agreement: Kappa Statistics," pp. 360–363, 2005.
BNPB, "Agile and resilient response to disasters," Health. Mass., vol. 22, pp. 256–265, 2020, [Online]. Available: http://dx.doi.org/10.1016/j.tsc.2016.10.002
BPBD.bogorkab.go.id/, "Disasters, Data 665, 02-09-2020 2025, Disaster Occurrence Data 2011 -," bpbd.bogorkab.go.id/, 2020. https://bpbd.bogorkab.go.id/berita/data-bencana# (accessed Jan. 20, 2025).
C. M. Scheip and K. W. Wegmann, “HazMapper: A global open-source natural hazard mapping application in Google Earth Engine,” Nat. Hazards Earth Syst. Sci., vol. 21, no. 5, pp. 1495–1511, 2021, doi: 10.5194/nhess-21-1495-2021.
D. Afasel, R. Purnamasari, and Edwar, "Land Cover Classification Using Supervised Machine Learning on Satellite Imagery Using Google Earth Engine," e-Proceeding Eng., vol. 8, no. 6, p. 3281, 2022.
D. Astari, W. F. Banggur, N. Santi, and N. Najib, "Mapping of Pyroclastic Flow Danger Zones of Mount Merapi, Central Java and Surrounding Areas using Titan2D Application," J. Geoscience and Technology., vol. 5, no. 1, pp. 76–82, 2022, doi: 10.14710/jgt.5.1.2022.76-82.
D. Notti, M. Cignetti, D. Godone, and D. Giordan, "Semi-automated mapping of shallow landslides using the free Sentinel-2 and Google Earth Engine.," pp. 1–34, 2022.
E. Ihda, B. Sudarsono, and M. Awaluddin, "Analysis of the Order of Building Layout Towards River Boundaries in the Flood River of the East Canal of Semarang City (Case Study: Along the Flood of the East Canal from the Estuary to the Brig. Gen. Sudiarto Bridge (STA 0-
Fatimah and Nuryaningsih, Textbooks. 2018.
Firman F.M., Spi., M.sc REMOTE SENSING, UTMPRESS, Jl.RayaTelang, PO Box 2 Kamal, Bangkalan Madura, 2015
H. Muzaky and L. M. Jaelani, "Analysis of the Effect of Land Cover on Surface Temperature Distribution: An Urban Heat Island Study in Jakarta, Bandung and Surabaya," J. Indonesian Remote Sensing., vol. 1, no. 2, pp. 45–51, 2019, [Online]. Available: http://jurnal.mapin.or.id/index.php/jpji/article/view/14
I. G. Indrayana, Geographic Information System, no. 140030655. 2017.
I. Komala Dewi, M. Yogie Syahbadar, and Muhammad Hatta Ope, "The Risk of Landslide Disasters on Space Utilization in Sukamakmur District, Bogor Regency," J. Tek. | Maj. Ilm. Fak. Tech. UNPAK, vol. 22, no. 2, pp. 17–25, 2021, doi: 10.33751/teknik.v22i2.4692.
N. Wakhidatus, A. L. Nugraha, and M. Awaluddin, "Threat Analysis of Floods and Landslides in Residential Areas in Jepara Regency,"
R. Baxter, Software engineering is software engineering. 2006. doi: 10.1049/ic:20040411.
T. Fawcett, “An introduction to ROC analysis,” Pattern Recognit. Lett., vol. 27, no. 8, pp. 861–874, 2006, doi: 10.1016/j.patrec.2005.10.010.
W. Zhang, B. Hu, and G. S. Brown, “Automatic surface water mapping using polarimetric SAR data for long-term change detection,” Water (Switzerland), vol. 12, no. 3, pp. 1–14, 2020, doi: 10.3390/w12030872.
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