The Relationship of Rainfall Variability to Flood Events Using Google Earth Engine (GEE) In Makassar City

Indonesian people are most harmed by flood hydrometeorological disasters, which cause material and immaterial losses. Floods often occur in some areas of Makassar City due to high rainfall and the high density of people and buildings, especially in the rainy season. This study aims to find out: the rainfall variability in the city of Makassar for 7 years (2017-2023), a map of flood inundation areas in the city of Makassar for 7 years (2017-2023), and the relationship between rainfall variability to flood events using Google Earth Engine (GEE) in the city of Makassar. This study is quantitative descriptive, using correlation and regression analysis between rainfall variables and flood inundation area. A cloud-based processing approach. CHIRPS data was used for rainfall analysis in Makassar City (2017-2023), and Sentinel 1 to analyze the distribution of flood inundation. The results showed that 1) rainfall variability occurred in January, February, March, November, and March. With the highest coefficient of variance value with a value of 73% in November. 2) floods that often occur in the sub-districts of Manggala, Biringkanaya, Tamalate, Tamalanrea, and Rappocini. 3) There is a significant relationship between rainfall and events in Makassar City. Spatially there were 12 flood events, temporal flood events for 7 years (2017-2023) occurred in December, January, and February. The parameters in this study are limited to rainfall and flood inundation, for that the next study is to add various relevant parameters based on Google Earth Engine.

Authors

Publication Details

Journal
Sainsmat Jurnal Ilmiah Ilmu Pengetahuan Alam
Published
2025-03-17
DOI
https://doi.org/10.35580/sainsmat141709192025
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Relationship of Rainfall Variability to Flood Events Using Google Earth Engine (GEE) In Makassar City

Mutmainnah Ali, Rosmini Maru, Arfandi Arfandi, Sukri Nyompa et al.
Sainsmat Jurnal Ilmiah Ilmu Pengetahuan Alam
Data Mining and Machine Learning Applications
article

The Relationship of Rainfall Variability to Flood Events Using Google Earth Engine (GEE) In Makassar City

Mutmainnah Ali, Rosmini Maru, Arfandi Arfandi, Sukri Nyompa, Nasrul Nasrul
article en

Abstract

Indonesian people are most harmed by flood hydrometeorological disasters, which cause material and immaterial losses. Floods often occur in some areas of Makassar City due to high rainfall and the high density of people and buildings, especially in the rainy season. This study aims to find out: the rainfall variability in the city of Makassar for 7 years (2017-2023), a map of flood inundation areas in the city of Makassar for 7 years (2017-2023), and the relationship between rainfall variability to flood events using Google Earth Engine (GEE) in the city of Makassar. This study is quantitative descriptive, using correlation and regression analysis between rainfall variables and flood inundation area. A cloud-based processing approach. CHIRPS data was used for rainfall analysis in Makassar City (2017-2023), and Sentinel 1 to analyze the distribution of flood inundation. The results showed that 1) rainfall variability occurred in January, February, March, November, and March. With the highest coefficient of variance value with a value of 73% in November. 2) floods that often occur in the sub-districts of Manggala, Biringkanaya, Tamalate, Tamalanrea, and Rappocini. 3) There is a significant relationship between rainfall and events in Makassar City. Spatially there were 12 flood events, temporal flood events for 7 years (2017-2023) occurred in December, January, and February. The parameters in this study are limited to rainfall and flood inundation, for that the next study is to add various relevant parameters based on Google Earth Engine.

Sainsmat Jurnal Ilmiah Ilmu Pengetahuan AlamVol. 14(1)
Openalex Percentile: Top 81%
Data Mining and Machine Learning Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

The Relationship of Rainfall Variability to Flood Events Using Google Earth Engine (GEE) In Makassar City — Mutmainnah Ali, Rosmini Maru, et al. · Sainsmat Jurnal Ilmiah Ilmu Pengetahuan Alam (2025) | TGRS Research Map | TGRS