Fine-grained, spatiotemporal datasets measuring 200 years of land development in the United States

Uhl, Johannes; Leyk, Stefan; McShane, Caitlin M.; Braswell, Anna; Connor, Dylan; Balk, Deborah

doi:10.5194/essd-13-119-2021

Cited by 26 publications

(33 citation statements)

References 56 publications

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“…However, novel data sources such as the industry-generated property database ZTRAX (Zillow Transaction and Assessment Dataset [ 86 ]), assembled from heterogeneous county-level assessor data, holds the year-built information for large parts of the US building stock and has recently been leveraged to generate the Historical Settlement Data Compilation for the US (HISDAC-US). HISDAC-US is a fine-grained historical settlement database for the conterminous US, composed of gridded surfaces consistently enumerated in a grid of 250 m × 250 m, measuring for example, the number of built-up properties per grid cell from 1810 to 2016, which is a proxy measure for building density [ 9 , 80 ] ( Figure 4a , b ).…”

Section: Methodsmentioning

confidence: 99%

“…Hence, we expect this bias to be marginal for the presented work. We applied our method to historical maps from six cities in four continents dated between 1890 and 1960, using historical built-up property data from the Historical Settlement Data Compilation for the US (HISDAC-US) [ 8 , 80 ] as well as urban area estimates from the History Database of the Global Environment (HYDE) [ 6 ] to evaluate and cross-compare our results.…”

Section: Introductionmentioning

confidence: 99%

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Combining Remote-Sensing-Derived Data and Historical Maps for Long-Term Back-Casting of Urban Extents

Uhl

Leyk

et al. 2021

Remote Sensing

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Spatially explicit, fine-grained datasets describing historical urban extents are rarely available prior to the era of operational remote sensing. However, such data are necessary to better understand long-term urbanization and land development processes and for the assessment of coupled nature–human systems (e.g., the dynamics of the wildland–urban interface). Herein, we propose a framework that jointly uses remote-sensing-derived human settlement data (i.e., the Global Human Settlement Layer, GHSL) and scanned, georeferenced historical maps to automatically generate historical urban extents for the early 20th century. By applying unsupervised color space segmentation to the historical maps, spatially constrained to the urban extents derived from the GHSL, our approach generates historical settlement extents for seamless integration with the multi-temporal GHSL. We apply our method to study areas in countries across four continents, and evaluate our approach against historical building density estimates from the Historical Settlement Data Compilation for the US (HISDAC-US), and against urban area estimates from the History Database of the Global Environment (HYDE). Our results achieve Area-under-the-Curve values >0.9 when comparing to HISDAC-US and are largely in agreement with model-based urban areas from the HYDE database, demonstrating that the integration of remote-sensing-derived observations and historical cartographic data sources opens up new, promising avenues for assessing urbanization and long-term land cover change in countries where historical maps are available.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Combining Remote-Sensing-Derived Data and Historical Maps for Long-Term Back-Casting of Urban Extents

Uhl

Leyk

et al. 2021

Remote Sensing

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show abstract

“…However, novel data sources such as the industry-generated property database ZTRAX (Zillow Transaction and Assessment Dataset [82]), assembled from heterogeneous county-level assessor data, holds the yearbuilt information for large parts of the US building stock and has recently been leveraged to generate the Historical Settlement Data Compilation for the US (HISDAC-US). HIS-DAC-US is a fine-grained, historical settlement database for the conterminous US, composed of gridded surfaces consistently enumerated in a grid of 250x250m, measuring e.g., the number of built-up properties per grid cell from 1810 to 2016 [9,76] (Fig. 3a,b).…”

Section: Historical Mapsmentioning

confidence: 99%

“…We applied our method to six cities in four continents and thus four map products, dated between 1890 and 1960. We used historical builtup property data from the Historical Settlement Data Compilation for the US (HISDAC-US) [8,76] as well as urban areas from the History Database of the Global Environment (HYDE) [6] to evaluate and cross-compare our results.…”

Section: Introductionmentioning

confidence: 99%

Combining Remote Sensing Derived Data and Historical Maps for Long-Term Back-Casting of Urban Extents

Uhl¹,

Leyk²,

Li³

et al. 2021

Preprint

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Spatially explicit, fine-grained datasets describing historical urban extents are rarely available prior to the era of operational remote sensing. However, such data are necessary to better understand long-term urbanization and land development processes and for the assessment of coupled nature-human systems, e.g., the dynamics of the wildland-urban interface. Herein, we propose a framework that jointly uses remote sensing derived human settlement data (i.e., the Global Human Settlement Layer, GHSL) and scanned, georeferenced historical maps to automatically generate historical urban extents for the early 20th century. By applying unsupervised color segmentation to the historical maps, spatially constrained to the urban extents derived from the GHSL, our approach generates historical settlement extents for seamless integration with the multi-temporal GHSL. We apply our method to study areas in countries across four continents, and evaluate our approach for two U.S. study sites against historical settlement extents derived from the Historical Settlement Data Compilation for the US, HISDAC-US, achieving Area-under-the-Curve values >0.9. Our results are largely in agreement with model-based urban areas from the HYDE database, and demonstrate that the integration of remote sensing derived observations and historical cartographic data sources opens up new, promising avenues for assessing urbanization, and long-term land cover change in countries where historical maps are available.

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“…Another way to explore the urbanization process in the historical period is the restoration of the urban extents or the built-up areas of cities (He et al, 2002;Hedefalk et al, 2017;Lin et al, 2017;Qin et al, 2019;Uhl et al, 2021). However, before the popularization of scientific cartography in the 20th century, maps in China generally lacked the basis of surveying and mapping (Yee et al, 1994;Cheng, 2019) and could not be used to restore the built-up urban areas in the late imperial period precisely.…”

Section: Introductionmentioning

confidence: 99%

The dataset of walled cities and urban extent in late imperial China in the 15th–19th centuries

Xue

Jin

Cheng

et al. 2021

Earth Syst. Sci. Data

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Abstract. Long-term urban extent data are highly desirable for understanding urban land use patterns. However, urban observation data based on remote sensing are typically confined to recent decades. In this study, we advance in this arena by reconstructing the walled cities for China that extend from the 15th century to the 19th century based on multiple historical documents. Cities in late imperial China (the Ming and the Qing dynasties, 1368–1911) generally had city walls, and these walls were usually built around the built-up urban area. By restoring the extent of the city walls, it is helpful to explore the urban extent in this period. Firstly, we collected the years of construction or reconstruction of city walls from the historical data. Specifically, the period in which the size of the city wall remains unchanged is recorded as a lifetime of it. Secondly, a specialization on the extent of the city wall could be conducted based on the urban morphology method and a variety of documentation, including the historical literature materials, the military topographic maps of the first half of the 20th century, and the remote sensing images of the 1970s. The correlation and integration of the lifetime and the spatial data led to the creation of the China City Wall Areas Dataset (CCWAD) for the late imperial period. Based on the proximity to the time of most of the city walls, we selected six representative years (i.e., 1400, 1537, 1648, 1708, 1787, and 1866) from CCWAD to produce the China Urban Extent Dataset (CUED) for the 15th–19th centuries. These datasets are available at https://doi.org/10.6084/m9.figshare.14112968.v3 (Xue et al., 2021).

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Fine-grained, spatiotemporal datasets measuring 200 years of land development in the United States

Cited by 26 publications

References 56 publications

Combining Remote-Sensing-Derived Data and Historical Maps for Long-Term Back-Casting of Urban Extents

Combining Remote-Sensing-Derived Data and Historical Maps for Long-Term Back-Casting of Urban Extents

Combining Remote Sensing Derived Data and Historical Maps for Long-Term Back-Casting of Urban Extents

The dataset of walled cities and urban extent in late imperial China in the 15th–19th centuries

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