Estimating Time of Urbanization with Moderate-Resolution Sensors
Bibliographic Data
| ID | 21373561 |
|---|---|
| Authors | José Luis Silván-Cárdenas (0000-0002-7091-4372, Centro de Investigación en Ciencias de Información Geoespacial CDMX, Mexico), Rodrigo Tapia-McClung (0000-0002-7784-5867, Centro de Investigación en Ciencias de Información Geoespacial CDMX, Mexico), Juan Carlos Valdiviezo-Navarro (Centro de Investigación en Ciencias de Información Geoespacial CDMX, Mexico), Adán Salazar-Garibay (0000-0002-3764-6273, Agencia Espacial Mexicana) |
| Year | 2023 |
| Volume | 75 |
| Issue | 3 |
| Pages | 463-480 |
| Publication date | 2023-05-04 |
| Open Access | No |
| Type | ARTICLE |
| Venue | The Professional Geographer (JOURNAL) |
| Journal identifiers | ISSN: 0033-0124 • E-ISSN: 1467-9272 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00330124.2022.2125882 |
| OpenAlex | W4307407425 |
| Language | EN |
| References cited | 31 |
The continuous recording of images of the Earth’s surface through Earth observation satellites has enabled the study of large-scale dynamical process, such as urbanization. Mapping the urban land cover at a given time is a first-order problem that has been largely addressed, and for which several acceptable solutions exist. A second-order problem is the analysis of change through time, which has been generally addressed through change vector or change matrix analyses, but they tend to neglect the spatial dimensions in favor of the temporal one. In this study, we propose the estimation of the time of urbanization across space as a useful indicator of the spatiotemporal structure of the urbanization process. A map of the time of urbanization can be considered a third-order product, as it compresses time series of urban land cover in one image that can effectively help identify areas of accelerated development and the time when they occurred. We apply linear spectral unmixing to quarterly composites of Landsat 8 imagery over the metropolitan corridor in central Mexico, from which a time series of urban percentage coverage is generated for the period between 2013 and 2021. Time filters were then applied to the time series and the time of urbanization was detected as the time when an increase of 25 percent of urbanization or larger first occurred. The accuracy assessment of the urbanization time showed a good correspondence with reference points that were randomly selected in the area of study
Cartography · Civil engineering · Geography · Land cover · Land use · Meteorology · Metropolitan area · Physical geography · Remote sensing · Scale (ratio) · Time series · Urbanization · Computer Science · Environmental Science · Impact of Light on Environment and Health · Land Use and Ecosystem Services · Remote-Sensing Image Classification
Land-Use and Land-Cover Change
High-resolution multi-temporal mapping of global urban land using Landsat images based on the Google Earth Engine Platform
Surface Urban Heat Island Across 419 Global Big Cities
Annual maps of global artificial impervious area (Gaia) between 1985 and 2018
How much of the world’s land has been urbanized, really? A hierarchical framework for avoiding confusion
Year (1978–2017) human settlement changes in China reflected by impervious surfaces from satellite remote sensing
Mapping global urban areas using Modis 500-m data
Remote sensing of impervious surfaces in the urban areas
Expansion and growth in Chinese cities, 1978–2010
High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015
| Highly cited | No |
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