Multi-Source and Multitemporal Urban and Rural Settlement Mapping Under Spatial Constraint: Qinghai–Tibetan Plateau Case Study
Accurately extracting long-term urban and rural settlement (URS) information is crucial for studying urbanization processes and their impacts on the ecological environment. However, existing remote sensing extraction methods often rely on independent classification strategies for each period, leadin...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/3/401 |
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| Summary: | Accurately extracting long-term urban and rural settlement (URS) information is crucial for studying urbanization processes and their impacts on the ecological environment. However, existing remote sensing extraction methods often rely on independent classification strategies for each period, leading to error accumulation and increased uncertainty in long-term sequence extraction. To address this, this study proposed a data/model-constrained dynamic extraction method for URS information and validated it using the Qinghai–Tibetan Plateau at five-year intervals from 1985 to 2020. The area of URS extracted by this method had a matching degree of 97.79% with the reference, with an average overall accuracy of 93.25% and a kappa of 0.89 for the 1985–2020 confusion matrix sample. The urban and rural settlement boundary (URSB) extracted by this method were more accurate than the Global Urban Boundary (GUB) dataset, particularly in spatial completeness and boundary detail. The results provide technical support for uncovering urban development patterns and their environmental impacts. |
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| ISSN: | 2072-4292 |