4.7 Article

Using Satellite Data to Analyse Raw Material Consumption in Hanoi, Vietnam

期刊

REMOTE SENSING
卷 13, 期 3, 页码 -

出版社

MDPI
DOI: 10.3390/rs13030334

关键词

land cover; material consumption analysis; construction materials; cloud computing; machine learning

资金

  1. British Geological Survey-Official Development Assistance programme [NE/R000069/1]
  2. NERC [bgs06001, come30001] Funding Source: UKRI

向作者/读者索取更多资源

This study provides an innovative approach in analysing urban expansion, population growth, and construction material consumption in Vietnam's Hanoi Province by combining satellite data with material consumption analysis. By calculating and forecasting construction material consumption and measuring its statistical correlation with urban expansion, the study reveals that official figures for sand consumption are currently underestimated and predicts a significant increase in steel and sand consumption by 2030.
In this work, we provide an innovative route for analysing urban expansion and population growth and their link to the consumption of construction materials by combining satellite data with material consumption analysis within the Hanoi Province (Vietnam). Urban expansion is investigated with the use of landcover maps for the period 1975-2020 derived from satellite. During this period, artificial surfaces and agricultural areas have increased by 11.6% and 15.5%, respectively, while forests have decreased by 26.7%. We have used publicly available datasets to calculate and forecast the construction materials consumption and measure its statistical correlation with urban expansion between 2007 and 2018. Our results show that official figures for sand consumption are currently underestimated, and that by 2030, steel and sand and gravel consumption will increase even further by three and two times, respectively. Our analysis uses a new method to assess urban development and associated impacts by combining socio-economic and Earth Observation datasets. The analysis can provide evidence, underpin decision-making by authorities, policymakers, urban planners and sustainability experts, as well as support the development of informed strategies for resource consumption. It can also provide important information for identifying areas of land conservation and ecological greenways during urban planning.

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