Assessing sustainable development in industrial regions towards smart built environment management using Earth observation big data
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 geographica...
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| Format: | Thesis |
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Curtin University
2023
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| Online Access: | http://hdl.handle.net/20.500.11937/92344 |
| _version_ | 1848765636509958144 |
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| author | Zhang, Zehua |
| author_facet | Zhang, Zehua |
| author_sort | Zhang, Zehua |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T11:38:24Z |
| format | Thesis |
| id | curtin-20.500.11937-92344 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:38:24Z |
| publishDate | 2023 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-923442023-06-08T07:48:11Z Assessing sustainable development in industrial regions towards smart built environment management using Earth observation big data Zhang, Zehua 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. 2023 Thesis http://hdl.handle.net/20.500.11937/92344 Curtin University fulltext |
| spellingShingle | Zhang, Zehua Assessing sustainable development in industrial regions towards smart built environment management using Earth observation big data |
| title | Assessing sustainable development in industrial regions towards
smart built environment management using Earth observation big
data |
| title_full | Assessing sustainable development in industrial regions towards
smart built environment management using Earth observation big
data |
| title_fullStr | Assessing sustainable development in industrial regions towards
smart built environment management using Earth observation big
data |
| title_full_unstemmed | Assessing sustainable development in industrial regions towards
smart built environment management using Earth observation big
data |
| title_short | Assessing sustainable development in industrial regions towards
smart built environment management using Earth observation big
data |
| title_sort | assessing sustainable development in industrial regions towards
smart built environment management using earth observation big
data |
| url | http://hdl.handle.net/20.500.11937/92344 |