PEMODELAN INDEKS PENCEMARAN DINAMIS SAMPAH PLASTIK SUNGAI ASIA TENGGARA MENGGUNAKAN INTEGRASI DATA PENGINDERAAN JAUH DAN DATA SOSIO-EKONOMI

As a lightweight, inexpensive, and easy-to-obtain material, plastic has experienced a significant increase in production in the world over the last few decades. In addition, the nature of plastic that is difficult to decompose will eventually become plastic waste that accumulates, both on land and i...

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Main Author: Rezqy Hafidzah, Dyah
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/65216
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:65216
spelling id-itb.:652162022-06-21T13:08:20ZPEMODELAN INDEKS PENCEMARAN DINAMIS SAMPAH PLASTIK SUNGAI ASIA TENGGARA MENGGUNAKAN INTEGRASI DATA PENGINDERAAN JAUH DAN DATA SOSIO-EKONOMI Rezqy Hafidzah, Dyah Indonesia Final Project plastic waste generation, streamflow index, geospatial analysis, remote sensing, socioeconomic parameters INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/65216 As a lightweight, inexpensive, and easy-to-obtain material, plastic has experienced a significant increase in production in the world over the last few decades. In addition, the nature of plastic that is difficult to decompose will eventually become plastic waste that accumulates, both on land and in the ocean. Strategic steps need to be implemented by each country to reduce the amount of plastic waste produced every time. This study uses a geospatial information approach to determine plastic waste pollution, which can be used by integrating various data sources. This study aims to create a dynamic pollution model of untreated plastic waste in rivers in Southeast Asia by combining remote sensing data and socioeconomic data. The parameters used to determine the plastic waste potential index are the amount of plastic waste generated, socioeconomic, and climate. Remote sensing data used are DEM, slope, rainfall, and wind speed. Meanwhile, data on population density, human development index, and gross domestic product are used as socioeconomic parameters. The estimation model for plastic waste entering the river and the streamflow model were made using the weighting method and overlapping analysis of the existing parameters. The results show that basins in densely populated areas such as the cities of Jakarta, Bangkok, Kuala Lumpur, Hanoi, and Manila have the potential to produce high levels of plastic waste from the mainland. The increased amount of plastic waste is influenced by climatic conditions in certain months, which will be of high value in September – February and low in the middle of 2021. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description As a lightweight, inexpensive, and easy-to-obtain material, plastic has experienced a significant increase in production in the world over the last few decades. In addition, the nature of plastic that is difficult to decompose will eventually become plastic waste that accumulates, both on land and in the ocean. Strategic steps need to be implemented by each country to reduce the amount of plastic waste produced every time. This study uses a geospatial information approach to determine plastic waste pollution, which can be used by integrating various data sources. This study aims to create a dynamic pollution model of untreated plastic waste in rivers in Southeast Asia by combining remote sensing data and socioeconomic data. The parameters used to determine the plastic waste potential index are the amount of plastic waste generated, socioeconomic, and climate. Remote sensing data used are DEM, slope, rainfall, and wind speed. Meanwhile, data on population density, human development index, and gross domestic product are used as socioeconomic parameters. The estimation model for plastic waste entering the river and the streamflow model were made using the weighting method and overlapping analysis of the existing parameters. The results show that basins in densely populated areas such as the cities of Jakarta, Bangkok, Kuala Lumpur, Hanoi, and Manila have the potential to produce high levels of plastic waste from the mainland. The increased amount of plastic waste is influenced by climatic conditions in certain months, which will be of high value in September – February and low in the middle of 2021.
format Final Project
author Rezqy Hafidzah, Dyah
spellingShingle Rezqy Hafidzah, Dyah
PEMODELAN INDEKS PENCEMARAN DINAMIS SAMPAH PLASTIK SUNGAI ASIA TENGGARA MENGGUNAKAN INTEGRASI DATA PENGINDERAAN JAUH DAN DATA SOSIO-EKONOMI
author_facet Rezqy Hafidzah, Dyah
author_sort Rezqy Hafidzah, Dyah
title PEMODELAN INDEKS PENCEMARAN DINAMIS SAMPAH PLASTIK SUNGAI ASIA TENGGARA MENGGUNAKAN INTEGRASI DATA PENGINDERAAN JAUH DAN DATA SOSIO-EKONOMI
title_short PEMODELAN INDEKS PENCEMARAN DINAMIS SAMPAH PLASTIK SUNGAI ASIA TENGGARA MENGGUNAKAN INTEGRASI DATA PENGINDERAAN JAUH DAN DATA SOSIO-EKONOMI
title_full PEMODELAN INDEKS PENCEMARAN DINAMIS SAMPAH PLASTIK SUNGAI ASIA TENGGARA MENGGUNAKAN INTEGRASI DATA PENGINDERAAN JAUH DAN DATA SOSIO-EKONOMI
title_fullStr PEMODELAN INDEKS PENCEMARAN DINAMIS SAMPAH PLASTIK SUNGAI ASIA TENGGARA MENGGUNAKAN INTEGRASI DATA PENGINDERAAN JAUH DAN DATA SOSIO-EKONOMI
title_full_unstemmed PEMODELAN INDEKS PENCEMARAN DINAMIS SAMPAH PLASTIK SUNGAI ASIA TENGGARA MENGGUNAKAN INTEGRASI DATA PENGINDERAAN JAUH DAN DATA SOSIO-EKONOMI
title_sort pemodelan indeks pencemaran dinamis sampah plastik sungai asia tenggara menggunakan integrasi data penginderaan jauh dan data sosio-ekonomi
url https://digilib.itb.ac.id/gdl/view/65216
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