Assessing sustainable development in industrial regions towards smart built environment management using Earth observation big data
dc.contributor.author | Zhang, Zehua | |
dc.contributor.supervisor | Yongze Song | en_US |
dc.contributor.supervisor | Peng Wu | en_US |
dc.date.accessioned | 2023-06-08T07:48:11Z | |
dc.date.available | 2023-06-08T07:48:11Z | |
dc.date.issued | 2023 | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/92344 | |
dc.description.abstract |
This thesis investigates the sustainability of nationwide industrial regions using Earth observation big data, from environmental and socio-economic perspectives. The research contributes to spatial methodology design and decision-making support. New spatial methods, including the robust geographical detector and the concept of geocomplexity, are proposed to demonstrate the spatial properties of industrial sustainability. The study delivers scientific decision-making advice to industry stakeholders and policymakers for the post-construction assessment and future planning phases. The research has been published in prestigious geography journals, demonstrating its success. | en_US |
dc.publisher | Curtin University | en_US |
dc.title | Assessing sustainable development in industrial regions towards smart built environment management using Earth observation big data | en_US |
dc.type | Thesis | en_US |
dcterms.educationLevel | PhD | en_US |
curtin.department | School of Design and the Built Environment | en_US |
curtin.accessStatus | Open access | en_US |
curtin.faculty | Humanities | en_US |
curtin.contributor.orcid | Zhang, Zehua | en_US |