Flood inundation prediction model related to land subsidence with Lidar in North Coastal Jakarta

Mohammad Ardha; Galdita Aruba Chulafak; Nanin Anggraini; Agung Syetiawan; Muhammad Rokhis Khomarudin

doi:10.1117/12.3009685

29 January 2024 Flood inundation prediction model related to land subsidence with Lidar in North Coastal Jakarta

Mohammad Ardha, Galdita Aruba Chulafak, Nanin Anggraini, Agung Syetiawan, Muhammad Rokhis Khomarudin

Proceedings Volume 12977, Eighth Geoinformation Science Symposium 2023: Geoinformation Science for Sustainable Planet; 1297716 (2024) https://doi.org/10.1117/12.3009685
Event: 8th Geoinformation Science Symposium 2023: Geoinformation Science for Sustainable Planet, 2023, Yogyakarta, Indonesia

Abstract

The subsidence of the land surface in the north coast of Java has become a national and international concern, which says that Jakarta will sink in the next few years. Remote sensing, especially with SAR data, is widely used to view the deformation and subsidence of the ground. Several studies have indeed shown a trend of land subsidence in Jakarta in recent years. This research processing uses Sentinel 1 data to obtain information related to the rate of subsidence using the Insar method, which results. The Lidar data is then used to predict inundation models in recent years to see areas below sea level. Then, a Land Use Land Cover analysis is carried out to see the use of land that will experience inundation in the future. The results show that the total area inundated in 2031 is 1393.6 ha, with the most significant area will inundated in North Jakarta, and for future potential LULC in Jakarta The largest land use land cover in Urban Area with 85 % from total LULC. And for total Potential LULC will be inundated is urban area with 1197.79 ha.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Mohammad Ardha, Galdita Aruba Chulafak, Nanin Anggraini, Agung Syetiawan, and Muhammad Rokhis Khomarudin "Flood inundation prediction model related to land subsidence with Lidar in North Coastal Jakarta", Proc. SPIE 12977, Eighth Geoinformation Science Symposium 2023: Geoinformation Science for Sustainable Planet, 1297716 (29 January 2024); https://doi.org/10.1117/12.3009685

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KEYWORDS

LIDAR

Data modeling

Floods

Land cover

Artificial neural networks

Data conversion

Industry

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