Intra-urban land use maps for a global sample of cities from Sentinel-2 satellite imagery and computer vision

Guzder-Williams, B. P.; Mackres, Eric; Angel, Shlomo; Blei, Alejandro M.; Lamson-Hall, Patrick

doi:10.1016/j.compenvurbsys.2022.101917

Cited by 16 publications

(11 citation statements)

References 32 publications

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“…AI has enabled urban researchers, designers, and planners with extensive proficiency in utilizing CV for designing, observing, and modeling urban environments and planning, evaluation processes, and stakeholder participation (Wael et al., 2022). Visual data are of critical importance in the process of urban planning and design, thereby the significance of CV [ 130 , 136 ] as a valuable tool for decision-making and planning processes [ 136 ]. In particular, CV holds significant promise in its ability to provide accessible and cost-effective tools for urban assessment and modeling [ 137 , 138 ].…”

Section: Results: Analysis and Synthesismentioning

confidence: 99%

The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: A comprehensive systematic review

Bibri,

Huang,

Jagatheesaperumal

et al. 2024

Environmental Science and Ecotechnology

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Section: Results: Analysis and Synthesismentioning

confidence: 99%

The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: A comprehensive systematic review

Bibri,

Huang,

Jagatheesaperumal

et al. 2024

Environmental Science and Ecotechnology

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“…For 'formal land use' we merged the sub-classes 'housing projects' and 'formal subdivision'. This procedure was also performed in the original paper to assess the data set's ability to detect informal settlements [21]. We used information from all 19 sub-Saharan cities available.…”

Section: Methodsmentioning

confidence: 99%

“…Table 1: Cities investigated in this study. The total population was calculated by merging WorldPop data with the land use data from [21]. The healthcare data was taken from Maina et al [22] and includes all healthcare facilities inside the above mentioned 15 km buffer zone around the land use maps of each city.…”

Section: Methodsmentioning

confidence: 99%

“…To work as consistently as possible we used global or continental wide available products such as the health-care dataset from Maina et al [22], the WorldPop data [23] for gridded population maps, land use data [21] to distinguish between formal and informal areas and OpenStreetMap to calculate travel times. All of these products introduce various types of uncertainties into our analysis.…”

Section: Limitationsmentioning

confidence: 99%

“…In this work, we broaden the understanding of accessibility to health-care in deprived urban areas by using recently produced datasets of settlement types from the World Resource Institute which classifies land use in more than 200 cities worldwide out of which 19 are in sub-Saharan Africa (SSA) [21].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Differences in walking access to health-care services between formal and informal areas in 19 sub-Saharan cities

Friesen,

Georganos,

Haas

2024

Preprint

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Purpose: Spatial accessibility to health-care is a critical factor in ensuring equitable health outcomes. While studies on a global, continental, and national level exist, our understanding of intra-urban differences, particularly between formal and informal areas within cities in sub-Saharan Africa, remains limited. Methods: This study integrates openly available datasets on land use in 19 sub-Saharan cities, health-care facilities in the region, and street networks from OpenStreetMap. Using these datasets, we calculate service areas around hospitals, considering travel times ranging from 1 to 180 minutes with walking as the mode of travel. The resulting service areas are then merged with population data from WorldPop, allowing us to assess the proportion of the population with specific travel times for different land uses. Results: Our analysis reveals that 43% of the urban population can reach hospitals within 15 minutes, 69% within 30 minutes, and 85% within 60 minutes. Importantly, we observe significant differences between formal and informal areas, with informal areas experiencing a disadvantage in terms of spatial accessibility to health-care facilities. Conclusion: This study sheds light on the spatial accessibility landscape of health-care facilities in sub-Saharan African cities, emphasizing the need to consider intra-urban disparities, particularly in informal areas. The findings underscore the importance of targeted interventions and urban planning strategies to address these disparities and ensure that health-care services are accessible to all segments of the urban population.

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The State of the Streets: Measurements of Connectivity in the Atlas of Urban Expansion

Lamson-Hall,

Angel

2024

Remote Sensing and Digital Image Processing

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Intra-urban land use maps for a global sample of cities from Sentinel-2 satellite imagery and computer vision

Cited by 16 publications

References 32 publications

The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: A comprehensive systematic review

The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: A comprehensive systematic review

Differences in walking access to health-care services between formal and informal areas in 19 sub-Saharan cities

The State of the Streets: Measurements of Connectivity in the Atlas of Urban Expansion

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