Urban pattern recognition from multi-spectral satellite images and flood prediction using machine learning models

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

Detalhes bibliográficos
Principais autores:	Tasnia, Rifah, Fuad, Sorder Md Farhan
Outros Autores:	Islam, Md. Saiful
Formato:	Tese
Idioma:	English
Publicado em:	Brac University 2024
Assuntos:	Flood prediction Machine learning UNET Multi-spectral satellite image Neural network VGG16 Pattern recognition. Optical data processing. Flood forecasting > Remote sensing.
Acesso em linha:	http://hdl.handle.net/10361/24340

id	10361-24340
record_format	dspace
spelling	10361-243402024-10-17T21:03:25Z Urban pattern recognition from multi-spectral satellite images and flood prediction using machine learning models Tasnia, Rifah Fuad, Sorder Md Farhan Islam, Md. Saiful Rahman, Rafeed Department of Computer Science and Engineering, Brac University Flood prediction Machine learning UNET Multi-spectral satellite image Neural network VGG16 Pattern recognition. Optical data processing. Flood forecasting--Remote sensing. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024. Cataloged from PDF version of thesis. Includes bibliographical references (pages 37-39). Bangladesh suffers from the cumulative effects of floods brought on by water flashing from nearby hills, the accumulation of the inflow of water from upstream catchments, and locally heavy rainfall made worse by drainage congestion because it is located in such a basin and is less than 5 meters above mean sea level. Additionally, the rapid landscape changes in river areas brought on by the strong water flow make them more vulnerable to flooding. The purpose of this study is to create a system of detection of flooding in a given area using satellite-collected Multi-Spectral satellite imagery and numerical data collected from Bangladesh Water Development Board. It can then forecast if a flood will occur in the area shortly based on the landscape presented and its current shape. Additionally, it can show the likelihood of a flood as well as whether there is a chance of one. Five classification algorithms, VGG19, GoogleLeNet, UNET, ResNet, and Inception which represent various machine learning concepts, have been chosen and implemented on a free and open-source basis on the image datasets and MLP was used on the numerical dataset and output of the models was feed forwarded to an FCNN model to detect the likelihood of a flood. The multi-spectral image datasets and numerical datasets used for this study’ s foundation date from 2015 to 2023. Rifah Tasnia Sorder Md Farhan Fuad B.Sc. in Computer Science 2024-10-17T04:02:25Z 2024-10-17T04:02:25Z ©2024 2024-05 Thesis ID 20101452 ID 20301058 http://hdl.handle.net/10361/24340 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 47 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Flood prediction Machine learning UNET Multi-spectral satellite image Neural network VGG16 Pattern recognition. Optical data processing. Flood forecasting--Remote sensing.
spellingShingle	Flood prediction Machine learning UNET Multi-spectral satellite image Neural network VGG16 Pattern recognition. Optical data processing. Flood forecasting--Remote sensing. Tasnia, Rifah Fuad, Sorder Md Farhan Urban pattern recognition from multi-spectral satellite images and flood prediction using machine learning models
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.
author2	Islam, Md. Saiful
author_facet	Islam, Md. Saiful Tasnia, Rifah Fuad, Sorder Md Farhan
format	Thesis
author	Tasnia, Rifah Fuad, Sorder Md Farhan
author_sort	Tasnia, Rifah
title	Urban pattern recognition from multi-spectral satellite images and flood prediction using machine learning models
title_short	Urban pattern recognition from multi-spectral satellite images and flood prediction using machine learning models
title_full	Urban pattern recognition from multi-spectral satellite images and flood prediction using machine learning models
title_fullStr	Urban pattern recognition from multi-spectral satellite images and flood prediction using machine learning models
title_full_unstemmed	Urban pattern recognition from multi-spectral satellite images and flood prediction using machine learning models
title_sort	urban pattern recognition from multi-spectral satellite images and flood prediction using machine learning models
publisher	Brac University
publishDate	2024
url	http://hdl.handle.net/10361/24340
work_keys_str_mv	AT tasniarifah urbanpatternrecognitionfrommultispectralsatelliteimagesandfloodpredictionusingmachinelearningmodels AT fuadsordermdfarhan urbanpatternrecognitionfrommultispectralsatelliteimagesandfloodpredictionusingmachinelearningmodels
_version_	1814308776928346112

Urban pattern recognition from multi-spectral satellite images and flood prediction using machine learning models

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