Developing data approaches for accumulation of plastic waste modelling using environment and socio-economic data product

Abstract

Today the world faces the fact that 10 million tonnes of waste, primarily plastic waste, pas through the river. This global issue has become a serious problem that can be resolved with location-based that utilizes remote sensing technology, following recent developments of technology. This study aims to estimate the weight of potential plastic waste at the estuary before it enters the ocean and becomes marine debris. Several parameters are developed based on three main aspects, which are environment as graded by LULC, social aspect as provided by population density using building data, and economic aspect as provided by nightlight from NOAA’s VIIRS. The estimation used raster-based digital numbers processing, by using estimated data and providing weight. As a result, it shows that most of the metropolitan cities such as Jakarta contribute almost 507 tonne of plastic waste per day. For other cities, its generation is directly proportional to the increase in population. This study could become a consideration to synthesize policies, with the fact that massive population density impacts the increasing of the plastic waste generation.

Multi-Scenario Model of Plastic Waste Accumulation Potential in Indonesia Using Integrated Remote Sensing, Statistic and Socio-Demographic Data

“…The plastic waste generation unit was in weight (tonnes/day), with an initial indication that one regency had the same average value. This method also part of the developing study for waste generation data approach [50] for modelling of plastic waste generation per possible smallest administrative unit.…”

“…Red indicated larger plastic waste generation, and blue indicated lower generation of plastic waste. The map of plastic waste generation data per regency can be observed in Figure 4, which also developed from the previous study to creating an approaching model of plastic waste generation data [50]. The results show that the total amount of plastic waste per regency was between 1.18 to 954 tonnes/day for one administrative regency and city area in Indonesian territory; this indicates that every regency and city in Indonesia has plastic waste generation that varies depending on the profile in the area.…”

Assessing Potential Climatic and Human Pressures in Indonesian Coastal Ecosystems Using a Spatial Data-Driven Approach

“…Future research should focus on monitoring the quantity and quality of blue carbon ecosystems in Indonesia by utilizing a proven methodology using basic data for conserving coastal and marine ecosystems by developing global climate change mitigation strategies and exploring the potential for ecotourism in the tropical regions [128,129]. In addition, other spatial data products, such as nighttime lights, population, and accessibility, can be integrated to develop an indicator of human activity pressure in coastal areas to detect potential degradation of aquatic waste [79,130].…”

Fate identification and management strategies of non-recyclable plastic waste through the integration of material flow analysis and leakage hotspot modeling

“…To address and quantify this issue, approaches have been developed by utilizing spatial analysis using Geographic Information Systems (GIS). GIS approaches are developing through three pillars of sustainability identification aspects 11 , 12 : developing waste management scenarios by monetization of the economic condition 13 , 14 , implying seasonal changes 15 , and adapting the hydrological model 16 . Approaches to identify the amount of plastic waste leakage have also been developed with remote sensing monitoring technologies in aquatic and terrestrial environments using Unmanned Aerial Vehicle 17 , 18 and satellite-based monitoring 19 – 22 .…”

“…Approaches to identify the amount of plastic waste leakage have also been developed with remote sensing monitoring technologies in aquatic and terrestrial environments using Unmanned Aerial Vehicle 17 , 18 and satellite-based monitoring 19 – 22 . Further, some approaches have been designed towards integrating waste management systems with spatial analysis using GIS 11 , 23 , 24 . Based on these, the discarded plastic waste in open environments has been identified, although the existing conditions do not allow the source identification.…”