Articles | Volume 12, issue 1
https://doi.org/10.5194/essd-12-357-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-12-357-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
17 Feb 2020
Data description paper |
| 17 Feb 2020
| 17 Feb 2020
A national dataset of 30 m annual urban extent dynamics (1985–2015) in the conterminous United States
Xuecao Li
Department of Geological and Atmospheric Sciences, Iowa State
University, Ames, IA 50011, USA
Department of Geological and Atmospheric Sciences, Iowa State
University, Ames, IA 50011, USA
Zhengyuan Zhu
Department of Statistics, Iowa State University, Ames, IA 50011,
USA
Wenting Cao
Department of Geological and Atmospheric Sciences, Iowa State
University, Ames, IA 50011, USA
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Cited
29 citations as recorded by crossref.
- Implementation of the CCDC algorithm to produce the LCMAP Collection 1.0 annual land surface change product G. Xian et al. 10.5194/essd-14-143-2022
- A 30 m resolution dataset of China's urban impervious surface area and green space, 2000–2018 W. Kuang et al. 10.5194/essd-13-63-2021
- Large-scale deep learning based binary and semantic change detection in ultra high resolution remote sensing imagery: From benchmark datasets to urban application S. Tian et al. 10.1016/j.isprsjprs.2022.08.012
- Long-Term Analysis of Regional Vegetation Correlation with Climate and Phenology in the Midsection of Maowusu Sandland Z. Li et al. 10.3390/w16050623
- Integrating remote sensing and geospatial big data for urban land use mapping: A review J. Yin et al. 10.1016/j.jag.2021.102514
- Increasing global urban exposure to flooding: An analysis of long-term annual dynamics W. Cao et al. 10.1016/j.scitotenv.2022.153012
- Landsat-Derived Annual Maps of Agricultural Greenhouse in Shandong Province, China from 1989 to 2018 C. Ou et al. 10.3390/rs13234830
- Characterizing annual dynamics of urban form at the horizontal and vertical dimensions using long-term Landsat time series data Y. Wang et al. 10.1016/j.isprsjprs.2023.07.025
- Transboundary Basins Need More Attention: Anthropogenic Impacts on Land Cover Changes in Aras River Basin, Monitoring and Prediction S. Khoshnoodmotlagh et al. 10.3390/rs12203329
- Monitoring long-term annual urban expansion (1986–2017) in the largest archipelago of China W. Cao et al. 10.1016/j.scitotenv.2021.146015
- Performance Evaluation of a Smart Mobile Air Temperature and Humidity Sensor for Characterizing Intracity Thermal Environment C. Cao et al. 10.1175/JTECH-D-20-0012.1
- Mapping Rural Settlements from Landsat and Sentinel Time Series by Integrating Pixel- and Object-Based Methods R. Xu 10.3390/land10030244
- Monitoring Annual Land Use/Land Cover Change in the Tucson Metropolitan Area with Google Earth Engine (1986–2020) F. Dubertret et al. 10.3390/rs14092127
- Evaluation of Light Pollution in Global Protected Areas from 1992 to 2018 H. Mu et al. 10.3390/rs13091849
- Mapping global urban boundaries from the global artificial impervious area (GAIA) data X. Li et al. 10.1088/1748-9326/ab9be3
- 30 m global impervious surface area dynamics and urban expansion pattern observed by Landsat satellites: From 1972 to 2019 X. Huang et al. 10.1007/s11430-020-9797-9
- The spatiotemporal assessments for tidal flat erosion associated with urban expansion in the conterminous coastal United States from 1985 to 2015 C. Xu & W. Liu 10.1016/j.scitotenv.2023.165660
- A global record of annual terrestrial Human Footprint dataset from 2000 to 2018 H. Mu et al. 10.1038/s41597-022-01284-8
- Conterminous United States Land-Cover Change (1985–2016): New Insights from Annual Time Series R. Auch et al. 10.3390/land11020298
- Identifying discrepant regions in urban mapping from historical and projected global urban extents H. Mu et al. 10.1080/27669645.2022.2104990
- Regularity of rural settlement changes driven by rapid urbanization in North China over the three decades Y. Liu et al. 10.1016/j.scib.2023.08.006
- High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015 X. Liu et al. 10.1038/s41893-020-0521-x
- The Spatiotemporal Characteristics and Interactions between Urban Expansion and Tidal Flat Dynamics: A Case Study of Three Highly Urbanized Coastal Counties in the Southeastern United States C. Xu & W. Liu 10.3390/earth3020033
- Variability of urban fractional vegetation cover and its driving factors in 328 cities in China F. Feng et al. 10.1007/s11430-022-1219-2
- Mapping High-Resolution Global Impervious Surface Area: Status and Trends H. Ren et al. 10.1109/JSTARS.2022.3201380
- A novel approach for quantifying high-frequency urban land cover changes at the block level with scarce clear-sky Landsat observations C. Jing et al. 10.1016/j.rse.2021.112293
- Assessment of Sustainability Development in Urban Areas of Morocco L. Bounoua et al. 10.3390/urbansci4020018
- A standardized dataset of built-up areas of China’s cities with populations over 300,000 for the period 1990–2015 H. Jiang et al. 10.1080/20964471.2021.1950351
- Diversity in global urban sprawl patterns revealed by Zipfian dynamics X. Li et al. 10.1080/2150704X.2022.2073794
29 citations as recorded by crossref.
- Implementation of the CCDC algorithm to produce the LCMAP Collection 1.0 annual land surface change product G. Xian et al. 10.5194/essd-14-143-2022
- A 30 m resolution dataset of China's urban impervious surface area and green space, 2000–2018 W. Kuang et al. 10.5194/essd-13-63-2021
- Large-scale deep learning based binary and semantic change detection in ultra high resolution remote sensing imagery: From benchmark datasets to urban application S. Tian et al. 10.1016/j.isprsjprs.2022.08.012
- Long-Term Analysis of Regional Vegetation Correlation with Climate and Phenology in the Midsection of Maowusu Sandland Z. Li et al. 10.3390/w16050623
- Integrating remote sensing and geospatial big data for urban land use mapping: A review J. Yin et al. 10.1016/j.jag.2021.102514
- Increasing global urban exposure to flooding: An analysis of long-term annual dynamics W. Cao et al. 10.1016/j.scitotenv.2022.153012
- Landsat-Derived Annual Maps of Agricultural Greenhouse in Shandong Province, China from 1989 to 2018 C. Ou et al. 10.3390/rs13234830
- Characterizing annual dynamics of urban form at the horizontal and vertical dimensions using long-term Landsat time series data Y. Wang et al. 10.1016/j.isprsjprs.2023.07.025
- Transboundary Basins Need More Attention: Anthropogenic Impacts on Land Cover Changes in Aras River Basin, Monitoring and Prediction S. Khoshnoodmotlagh et al. 10.3390/rs12203329
- Monitoring long-term annual urban expansion (1986–2017) in the largest archipelago of China W. Cao et al. 10.1016/j.scitotenv.2021.146015
- Performance Evaluation of a Smart Mobile Air Temperature and Humidity Sensor for Characterizing Intracity Thermal Environment C. Cao et al. 10.1175/JTECH-D-20-0012.1
- Mapping Rural Settlements from Landsat and Sentinel Time Series by Integrating Pixel- and Object-Based Methods R. Xu 10.3390/land10030244
- Monitoring Annual Land Use/Land Cover Change in the Tucson Metropolitan Area with Google Earth Engine (1986–2020) F. Dubertret et al. 10.3390/rs14092127
- Evaluation of Light Pollution in Global Protected Areas from 1992 to 2018 H. Mu et al. 10.3390/rs13091849
- Mapping global urban boundaries from the global artificial impervious area (GAIA) data X. Li et al. 10.1088/1748-9326/ab9be3
- 30 m global impervious surface area dynamics and urban expansion pattern observed by Landsat satellites: From 1972 to 2019 X. Huang et al. 10.1007/s11430-020-9797-9
- The spatiotemporal assessments for tidal flat erosion associated with urban expansion in the conterminous coastal United States from 1985 to 2015 C. Xu & W. Liu 10.1016/j.scitotenv.2023.165660
- A global record of annual terrestrial Human Footprint dataset from 2000 to 2018 H. Mu et al. 10.1038/s41597-022-01284-8
- Conterminous United States Land-Cover Change (1985–2016): New Insights from Annual Time Series R. Auch et al. 10.3390/land11020298
- Identifying discrepant regions in urban mapping from historical and projected global urban extents H. Mu et al. 10.1080/27669645.2022.2104990
- Regularity of rural settlement changes driven by rapid urbanization in North China over the three decades Y. Liu et al. 10.1016/j.scib.2023.08.006
- High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015 X. Liu et al. 10.1038/s41893-020-0521-x
- The Spatiotemporal Characteristics and Interactions between Urban Expansion and Tidal Flat Dynamics: A Case Study of Three Highly Urbanized Coastal Counties in the Southeastern United States C. Xu & W. Liu 10.3390/earth3020033
- Variability of urban fractional vegetation cover and its driving factors in 328 cities in China F. Feng et al. 10.1007/s11430-022-1219-2
- Mapping High-Resolution Global Impervious Surface Area: Status and Trends H. Ren et al. 10.1109/JSTARS.2022.3201380
- A novel approach for quantifying high-frequency urban land cover changes at the block level with scarce clear-sky Landsat observations C. Jing et al. 10.1016/j.rse.2021.112293
- Assessment of Sustainability Development in Urban Areas of Morocco L. Bounoua et al. 10.3390/urbansci4020018
- A standardized dataset of built-up areas of China’s cities with populations over 300,000 for the period 1990–2015 H. Jiang et al. 10.1080/20964471.2021.1950351
- Diversity in global urban sprawl patterns revealed by Zipfian dynamics X. Li et al. 10.1080/2150704X.2022.2073794
Latest update: 18 Apr 2024
Short summary
The information of urban dynamics with fine spatial and temporal resolutions is highly needed in urban studies. In this study, we generated a long-term (1985–2015), fine-resolution (30 m) product of annual urban extent dynamics in the conterminous United States using all available Landsat images on the Google Earth Engine (GEE) platform. The data product is of great use for relevant studies such as urban growth projection, urban sprawl modeling, and urbanization impacts on environments.
The information of urban dynamics with fine spatial and temporal resolutions is highly needed in...
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