High-Resolution Urban Vegetation Gross Primary Productivity Simulation via Plant Functional Type Unmixing: A Case Study in Toronto, Canada
Despite extensive studies on the productivity of vegetation in natural ecosystems outside cities, remote sensing-based research on urban vegetation and its productivity remains limited due to spectral mixing phenomenon resulting from the vegetation’s fragmented distribution across heterogeneous urba...
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| Format: | Dissertation |
| Language: | English |
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ProQuest Dissertations & Theses
01-01-2024
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| Online Access: | Get full text |
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| Summary: | Despite extensive studies on the productivity of vegetation in natural ecosystems outside cities, remote sensing-based research on urban vegetation and its productivity remains limited due to spectral mixing phenomenon resulting from the vegetation’s fragmented distribution across heterogeneous urban landscapes. To assess the contribution of carbon fixation more accurately by urban vegetation, this study quantified its Gross Primary Productivity (GPP) at high spatial resolution in Toronto, Canada. Regression-based urban vegetation fraction unmixing was conducted on Landsat-8 imagery to separate signals reflected by urban vegetation, whose GPP was then modeled with derived physiological parameters and relevant meteorological data. This study demonstrates the feasibility of estimating urban GPP at a spatial resolution of 30 m using readily available input data. The developed algorithms can be further utilized to investigate spatiotemporal patterns of urban GPP and provide valuable information to conservation agencies and governments in tracking and managing carbon revenues and expenditures at a fine scale. |
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| ISBN: | 9798342757737 |