2021
DOI: 10.3390/ijgi10070481
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Multi-Scenario Model of Plastic Waste Accumulation Potential in Indonesia Using Integrated Remote Sensing, Statistic and Socio-Demographic Data

Abstract: As a significant contributor of plastic waste to the marine environment, Indonesia is striving to construct a national strategy for reducing plastic debris. Hence, the primary aim of this study is to create a model for plastic waste quantity originating from the mainland, accumulated in estuaries. This was achieved by compiling baseline data of marine plastic disposal from the mainland via comprehensive contextualisation of data generated by remote sensing technology and spatial analysis. The parameters used i… Show more

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Cited by 40 publications
(28 citation statements)
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“…Other disasters such as land subsidence [69,70], volcanic eruption [71,72], tsunami [73,74], and wildfire [75,76] should be considered in Indonesia. This multi-hazard analysis and comfort index could be applied in other potential sectors such as transportation [77] or other infrastructure developments such as power plants [78] and river networks [79]. Moreover, disaster vulnerability could be estimated, especially when ecosystem service calculation is used.…”
Section: Limitations and Future Possible Directionmentioning
confidence: 99%
“…Other disasters such as land subsidence [69,70], volcanic eruption [71,72], tsunami [73,74], and wildfire [75,76] should be considered in Indonesia. This multi-hazard analysis and comfort index could be applied in other potential sectors such as transportation [77] or other infrastructure developments such as power plants [78] and river networks [79]. Moreover, disaster vulnerability could be estimated, especially when ecosystem service calculation is used.…”
Section: Limitations and Future Possible Directionmentioning
confidence: 99%
“…In this case, a comprehensive study involving historical and political view has not been explored to propose wildfire mitigation prioritization concept and its relation to conservation. In addition, multi-source remote sensing data products and socio-economic data have been integrated to support a comprehensive spatial analysis at the national and regional levels [32][33][34][35][36]. Hence, A spatial data-driven approach exposes an opportunity to analyze tropical wildfire mitigation strategy extensively from multiple aspects [37][38][39].…”
Section: Introductionmentioning
confidence: 99%
“…Jambeck et al 2015, Lebreton andAndrady 2019). However, there are many other factors which could potentially influence the distribution of litter, including socio-economic status (SES) (Matsunaga and Themelis 2002), environmental variables such land cover (Sakti et al 2021), and waste and transport infrastructure (Willis et al 2017).…”
Section: Introductionmentioning
confidence: 99%