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Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis
Uncontrolled urban expansion resulting from urbanization has a disastrous impact on agricultural land. This situation is being experienced by the densely populated and fertile island Java in Indonesia. Remote sensing technologies have developed rapidly in recent years, including the creation of Goog...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769866/ https://www.ncbi.nlm.nih.gov/pubmed/35069036 http://dx.doi.org/10.1155/2022/3123788 |
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author | Gandharum, Laju Hartono, Djoko Mulyo Karsidi, Asep Ahmad, Mubariq |
author_facet | Gandharum, Laju Hartono, Djoko Mulyo Karsidi, Asep Ahmad, Mubariq |
author_sort | Gandharum, Laju |
collection | PubMed |
description | Uncontrolled urban expansion resulting from urbanization has a disastrous impact on agricultural land. This situation is being experienced by the densely populated and fertile island Java in Indonesia. Remote sensing technologies have developed rapidly in recent years, including the creation of Google Earth Engine (GEE). Intensity analysis (IA) is increasingly being used to systematically and substantially analyze land-use/land-cover (LULC) change. As yet, however, no study of land conversion from agriculture to urban areas in Indonesia has adopted GEE and IA approaches simultaneously. Therefore, this study aims to monitor urban penetration to agricultural land in the north coastal region of West Java Province by applying both methods to two time intervals: 2003–2013 and 2013–2020. Landsat data and a robust random forest (RF) classifier available in GEE were chosen for producing LULC maps. Monitoring LULC change using GEE and IA has demonstrated reliable findings. The overall accuracy of Landsat image classification results for 2003, 2013, and 2020 were 88%, 87%, and 88%, respectively. IA outputs at interval levels for all categories showed that the annual change-of-area rate was higher during 2013–2020 than during 2003–2013. At the category level, IA results showed that the area of agricultural land experienced net losses in both periods, with net loss in 2013–2020 being 2.3 times greater than that in 2003–2013 (∼1,850 ha per year). In contrast, the built-up area made net gains in both periods, reaching almost twice as much in the second period as in the first (∼2,030 ha per year). The transition-level IA performed proved that agricultural land had been the primary target for the expansion of built-up areas. The most extensive spatial distribution of land conversion from agriculture to built-up area was concentrated in the regencies of Bekasi, Karawang, and Cirebon. These findings are intended to provide stakeholders with enrichment in terms of available literature and with valuable inputs useful for identifying better urban and regional planning policies in Indonesia and similar regions. |
format | Online Article Text |
id | pubmed-8769866 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-87698662022-01-20 Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis Gandharum, Laju Hartono, Djoko Mulyo Karsidi, Asep Ahmad, Mubariq ScientificWorldJournal Research Article Uncontrolled urban expansion resulting from urbanization has a disastrous impact on agricultural land. This situation is being experienced by the densely populated and fertile island Java in Indonesia. Remote sensing technologies have developed rapidly in recent years, including the creation of Google Earth Engine (GEE). Intensity analysis (IA) is increasingly being used to systematically and substantially analyze land-use/land-cover (LULC) change. As yet, however, no study of land conversion from agriculture to urban areas in Indonesia has adopted GEE and IA approaches simultaneously. Therefore, this study aims to monitor urban penetration to agricultural land in the north coastal region of West Java Province by applying both methods to two time intervals: 2003–2013 and 2013–2020. Landsat data and a robust random forest (RF) classifier available in GEE were chosen for producing LULC maps. Monitoring LULC change using GEE and IA has demonstrated reliable findings. The overall accuracy of Landsat image classification results for 2003, 2013, and 2020 were 88%, 87%, and 88%, respectively. IA outputs at interval levels for all categories showed that the annual change-of-area rate was higher during 2013–2020 than during 2003–2013. At the category level, IA results showed that the area of agricultural land experienced net losses in both periods, with net loss in 2013–2020 being 2.3 times greater than that in 2003–2013 (∼1,850 ha per year). In contrast, the built-up area made net gains in both periods, reaching almost twice as much in the second period as in the first (∼2,030 ha per year). The transition-level IA performed proved that agricultural land had been the primary target for the expansion of built-up areas. The most extensive spatial distribution of land conversion from agriculture to built-up area was concentrated in the regencies of Bekasi, Karawang, and Cirebon. These findings are intended to provide stakeholders with enrichment in terms of available literature and with valuable inputs useful for identifying better urban and regional planning policies in Indonesia and similar regions. Hindawi 2022-01-12 /pmc/articles/PMC8769866/ /pubmed/35069036 http://dx.doi.org/10.1155/2022/3123788 Text en Copyright © 2022 Laju Gandharum et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Gandharum, Laju Hartono, Djoko Mulyo Karsidi, Asep Ahmad, Mubariq Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis |
title | Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis |
title_full | Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis |
title_fullStr | Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis |
title_full_unstemmed | Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis |
title_short | Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis |
title_sort | monitoring urban expansion and loss of agriculture on the north coast of west java province, indonesia, using google earth engine and intensity analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769866/ https://www.ncbi.nlm.nih.gov/pubmed/35069036 http://dx.doi.org/10.1155/2022/3123788 |
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