Erosion Susceptibility mapping using Machine Learning and GIS: A case study of Kelantan

The issue of soil erosion in Kelantan resulted in mudflow, river bank degradation and drinking water pollution. Therefore, this project is focused on predicting the location of soil erosion by using logistic regression Machine Learning algorithm and GIS. Erosion causative factors such as DEM, curvat...

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Main Author: Azizan, Nur Afiqah
Format: Final Year Project
Language: English
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.20792 /
Published: Universiti Teknologi PETRONAS 2020
Subjects:
TA Engineering (General). Civil engineering (General)
Online Access: http://utpedia.utp.edu.my/20792/1/DISSERTATION%20NUR%20AFIQAH_%2025638_.pdf
http://utpedia.utp.edu.my/20792/
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spelling utp-utpedia.207922021-09-09T12:59:42Z http://utpedia.utp.edu.my/20792/ Erosion Susceptibility mapping using Machine Learning and GIS: A case study of Kelantan Azizan, Nur Afiqah TA Engineering (General). Civil engineering (General) The issue of soil erosion in Kelantan resulted in mudflow, river bank degradation and drinking water pollution. Therefore, this project is focused on predicting the location of soil erosion by using logistic regression Machine Learning algorithm and GIS. Erosion causative factors such as DEM, curvature, slope, rainfall, landuse, soil erodibility and geology were evaluated. Based on the selected causative factors (CF), the map of CFs was being produced by using the ArcGIS software. Then, the data of causative factor from the ArcGIS was being used in training in machine learning (ML). There are 175-point location of soil erosion was used as to validate the soil erosion map.The weighted value of each factor was calculated according to the logistic regression (LR) and soil erosion susceptibility map was created. Universiti Teknologi PETRONAS 2020-01 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/20792/1/DISSERTATION%20NUR%20AFIQAH_%2025638_.pdf Azizan, Nur Afiqah (2020) Erosion Susceptibility mapping using Machine Learning and GIS: A case study of Kelantan. Universiti Teknologi PETRONAS. (Submitted)
institution Universiti Teknologi Petronas
collection UTPedia
language English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Azizan, Nur Afiqah
Erosion Susceptibility mapping using Machine Learning and GIS: A case study of Kelantan
description The issue of soil erosion in Kelantan resulted in mudflow, river bank degradation and drinking water pollution. Therefore, this project is focused on predicting the location of soil erosion by using logistic regression Machine Learning algorithm and GIS. Erosion causative factors such as DEM, curvature, slope, rainfall, landuse, soil erodibility and geology were evaluated. Based on the selected causative factors (CF), the map of CFs was being produced by using the ArcGIS software. Then, the data of causative factor from the ArcGIS was being used in training in machine learning (ML). There are 175-point location of soil erosion was used as to validate the soil erosion map.The weighted value of each factor was calculated according to the logistic regression (LR) and soil erosion susceptibility map was created.
format Final Year Project
author Azizan, Nur Afiqah
author_sort Azizan, Nur Afiqah
title Erosion Susceptibility mapping using Machine Learning and GIS: A case study of Kelantan
title_short Erosion Susceptibility mapping using Machine Learning and GIS: A case study of Kelantan
title_full Erosion Susceptibility mapping using Machine Learning and GIS: A case study of Kelantan
title_fullStr Erosion Susceptibility mapping using Machine Learning and GIS: A case study of Kelantan
title_full_unstemmed Erosion Susceptibility mapping using Machine Learning and GIS: A case study of Kelantan
title_sort erosion susceptibility mapping using machine learning and gis: a case study of kelantan
publisher Universiti Teknologi PETRONAS
publishDate 2020
url http://utpedia.utp.edu.my/20792/1/DISSERTATION%20NUR%20AFIQAH_%2025638_.pdf
http://utpedia.utp.edu.my/20792/
_version_ 1741195665645502464
score 11.62408

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