The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Zooming into temperature conditions in the city of Leipzig: How do urban built and green structures influence earth surface temperatures in the city?
Abstract
Urban landscape and land-use structure, particularly that of built space, were found to have a significant impact on environmental exposures, e.g., on the level and spatial distribution of particle and noise exposure in cities. Climate change will increase the frequency, duration and intensity of heat waves. Hence, the question arises: how do urban structures affect the shape and intensity of urban temperature conditions? To answer this question, multiple urban structures have been quantified in terms of their structural patterns and configuration using the landscape metric (LSM) approach. The results of a linear regression analysis showed that both the edge density and patch size ratio are significantly correlated with the spread and intensity of temperatures across all urban built structures. The analysis shows that the higher the proportion and structural complexity of the built area, the higher are the morning and evening surface temperatures. LSMs were found to be very well suited as analysis models of the site-specific temperature impact beyond the aggregate city level. Hence, they may serve as a planning tool for urban adaptation measures to climate change.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Sprawling urban areas with complex structures of buildings affect the heat storage capability of buildings.
“Studies claim that sprawling urban areas with complex structures of buildings affect the heat storage capability of the buildings [90].”
From Heatwaves in South Asia: Characterization, Consequences on Human Health, and Adaptation Strategies (2022) · cites this paper as [90]
Citations
Cites
Prediction of the indoor temperatures of an urban area with an in-time regression mapping approach
Smargiassi, A., Fournier, M., Griot, C., Baudouin, Y., & Kosatsky, T. (2008) · Journal of Exposure Science & Environmental Epidemiology · doi:10.1038/sj.jes.7500588 · Cited by 72
Flagged first, then by citations
Research works printed but not linked: 44
- Connors, 2013, Landscape configuration and urban heat island effects: assessing the relationship between landscape characteristics and land surface temperature in Phoenix, Arizona, Landsc Ecol, 28, 271, 10.1007/s10980-012-9833-1 · DOI
- Conti, 2005, Epidemiologic study of mortality during the Summer 2003 heat wave in Italy, Environ Res, 98, 390, 10.1016/j.envres.2004.10.009 · DOI
- Correy, 2005, Limitations of using landscape pattern indices to evaluate the ecological consequences of alternative plans and designs, Landsc Urban Plan, 72, 265, 10.1016/j.landurbplan.2004.04.003 · DOI
- Coseo, 2014, How factors of land use/land cover, building configuration, and adjacent heat sources and sinks explain Urban Heat Islands in Chicago, Landsc Urban Plan, 125, 117, 10.1016/j.landurbplan.2014.02.019 · DOI
- Cushman, 2012, Separating the effects of habitat area, fragmentation and matrix resistance on genetic differentiation in complex landscapes, Landsc Ecol, 27, 369, 10.1007/s10980-011-9693-0 · DOI
- DiBari, 2007, Evaluation of five landscape-level metrics for measuring the effects of urbanization on landscape structure: the case of Tucson, Arizona, USA, Landsc. Urban Plan., 79, 308, 10.1016/j.landurbplan.2006.04.004 · DOI
- Franck, 2013, Heat stress in urban areas: indoor and outdoor temperatures in different urban structure types and subjectively reported well-being during a heat wave in the city of Leipzig, Meteorol Z, 22, 167, 10.1127/0941-2948/2013/0384 · DOI
- Gabriel, 2011, Urban and rural mortality rates during heat waves in Berlin and Brandenburg, Germany, Environ Pollut, 159, 2044, 10.1016/j.envpol.2011.01.016 · DOI
- Garcia, 2012, Studying street geometry influence in PM10 concentration, Environ Pollut, 50, 283
- Haase, 2007, Does urban sprawl drive changes in the water balance and policy? The case of Leipzig (Germany) 1870–2003, Landsc Urban Plan, 80, 1, 10.1016/j.landurbplan.2006.03.011 · DOI
- Haines-Young, 1996, Quantifying landscape structure: a review of landscape indices and their application to forested landscapes, Prog Phys Geogr, 20, 418, 10.1177/030913339602000403 · DOI
- Harlan, 2006, Neighborhood microclimates and vulnerability to heat stress, Soc Sci Med, 63, 2847, 10.1016/j.socscimed.2006.07.030 · DOI · Paper page
- Hassett, 2012, Estimating landscape pattern metrics from a sample of land cover, Landsc Ecol, 27, 133, 10.1007/s10980-011-9657-4 · DOI
- Höbinger, 2012, Impact of oil palm plantations on the structure of the agroforestry mosaic of La Gamba, southern Costa Rica: potential implications for biodiversity, Agrofor Syst, 85, 367, 10.1007/s10457-011-9425-0 · DOI
- Kabisch, 2010, Evolving reurbanisation? Spatio-temporal dynamics exemplified at the eastern German city of Leipzig, Urban Stud, 47, 967, 10.1177/0042098009353072 · DOI
- Kan, 2012, Ambient air pollution, climate change, and population health in China, Environ Int, 42, 10, 10.1016/j.envint.2011.03.003 · DOI
- Lai, 2010, Urban heat island and air pollution—an emerging role for hospital respiratory admissions in an urban area, J Environ Health, 72, 32
- Li, 2004, Use and misuse of landscape indices, Landsc Ecol, 19, 389, 10.1023/B:LAND.0000030441.15628.d6 · DOI
- Li, 2011, Impacts of landscape structure on surface urban heat islands: a case study of Shanghai, China, Remote Sens Environ, 115, 3249, 10.1016/j.rse.2011.07.008 · DOI
- Martiello, 2010, High temperatures and health outcomes: a review of the literature, Scand J Public Health, 38, 826, 10.1177/1403494810377685 · DOI
- McKenzie, 2011, The ecological impact of rural building on habitats in an agricultural landscape, Landsc Urban Plan, 101, 262, 10.1016/j.landurbplan.2011.02.031 · DOI
- McPherson, 1997, Quantifying urban forest structure, function and value: the Chicago urban forest climate project, Urban Ecosyst, 1, 49, 10.1023/A:1014350822458 · DOI
- Mostovoy, 2006, Statistical estimation of daily maximum and minimum air temperatures from MODIS LST data over the state of Mississippi, GIScience & Remote Sensing, 43, 78, 10.2747/1548-1603.43.1.78 · DOI
- O'Neill, 2009, Temperature extremes and health: impacts of climate variability and change in the United States, J Occup Environ Med, 51, 13, 10.1097/JOM.0b013e318173e122 · DOI · Paper page
- Oke, 1981, Canyon geometry and the nocturnal urban heat island: comparison of scale model and field observations, Int J Climatol, 1, 237, 10.1002/joc.3370010304 · DOI
- Oke, 1982, The energetic basis of the urban heat island, Q J Roy Meteorol Soc, 108, 1
- Prihodko, 1997, Estimation of air temperature from remotely sensed surface observations, Remote Sens Environ, 60, 335, 10.1016/S0034-4257(96)00216-7 · DOI
- Santos-Filho, 2012, Habitat patch and matrix effects on small-mammal persistence in Amazonian forest fragments, Biodivers Conserv, 21, 1127, 10.1007/s10531-012-0248-8 · DOI
- Schindler, 2013, Multiscale performance of landscape metrics as indicators of species richness of plants, insects and vertebrates, Ecol Indic, 31, 41, 10.1016/j.ecolind.2012.04.012 · DOI
- Schwarz, 2010, Urban form revisited — selecting indicators for characterising European cities, Landsc Urban Plan, 96, 29, 10.1016/j.landurbplan.2010.01.007 · DOI
- Schwarz, 2011, Exploring indicators for quantifying surface urban heat islands of European cities with MODIS land surface temperatures, Remote Sens Environ, 115, 3175, 10.1016/j.rse.2011.07.003 · DOI
- Schwarz, 2012, Relationship of land surface and air temperatures and its implications for quantifying urban heat island indicators—an application for the city of Leipzig (Germany), Ecol Indic, 18, 693, 10.1016/j.ecolind.2012.01.001 · DOI
- Semazzi, 2003, Air quality research: perspective from climate change modeling research, Environ Int, 29, 253, 10.1016/S0160-4120(02)00184-8 · DOI
- Stafoggia, 2006, Vulnerability to heat-related mortality: a multicity, population-based, case-crossover analysis, Epidemiology, 17, 315, 10.1097/01.ede.0000208477.36665.34 · DOI
- Stewart, 2011, A systematic review and scientific critique of methodology in urban heat island literature, Int J Climatol, 31, 200, 10.1002/joc.2141 · DOI
- Stewart, 2012, Local climate zones for urban temperature studies, Bull Am Meteorol Soc, 93, 1879, 10.1175/BAMS-D-11-00019.1 · DOI
- Tan, 2010, The urban heat island and its impact on heat waves and human health in Shanghai, Int J Biometeorol, 54, 75, 10.1007/s00484-009-0256-x · DOI · Paper page
- Tomlinson, 2011, Including the urban heat island in spatial heat health risk assessment strategies: a case study for Birmingham, UK, Int J Health Geogr, 10, 42, 10.1186/1476-072X-10-42 · DOI
- Uuemaa, 2009, Landscape metrics and indices: an overview of their use in landscape research, Living Rev Landsc Res, 3, 10.12942/lrlr-2009-1 · DOI
- Walz, 2011, Landscape structure, landscape metrics and biodiversity, Living Rev, 5
- Wang, 2012, Spatio-temporal pattern analysis of land use/cover change trajectories in Xihe watershed, Int JAppl Earth Obs Geoinformation, 14, 12, 10.1016/j.jag.2011.08.007 · DOI
- Weber, 2014, Assessing modelled outdoor traffic-induced noise and air pollution around urban structures using the concept of landscape metrics, Landsc Urban Plan, 125, 105, 10.1016/j.landurbplan.2014.02.018 · DOI
- Whickam, 1997, Sensitivity of landscape metrics to land cover mis-classification and differences in land cover composition, Photogramm Eng Remote Sens, 63, 397
- White-Newsome, 2012, Climate change and health: indoor heat exposure in vulnerable populations, Environ Res, 112, 20, 10.1016/j.envres.2011.10.008 · DOI
Cited by
Sorted by citations
A systematic review of urban heat island and heat waves research (1991–2022)
Cheval, S., Amihăesei, V.-A., Chitu, Z., Dumitrescu, A., Falcescu, V., Irașoc, A., Micu, D. M., Mihulet, E., Ontel, I., Paraschiv, M.-G., et al. (2024) · Climate Risk Management · doi:10.1016/j.crm.2024.100603 · Cited by 156
Heatwaves in South Asia: Characterization, Consequences on Human Health, and Adaptation Strategies
Sharma, A., Andhikaputra, G., & Wang, Y.-C. (2022) · Atmosphere · doi:10.3390/atmos13050734 · Cited by 87
Review of heat wave studies and related urban policies in South Asia
Kotharkar, R., & Ghosh, A. (2021) · Urban Climate · doi:10.1016/j.uclim.2021.100777 · Cited by 76
Metadata
- Authors
- Weber, N., Haase, D., & Franck, U.
- Affiliations
- Humboldt-Universität zu Berlin (DE)
- Helmholtz Centre for Environmental Research (DE)
- Corresponding author
- Haase, Dagmar
- Venue
- Science of The Total Environment
- Publisher
- Elsevier BV
- Published
- 2014-10
- Volume
- 496
- Pages
- 289-298
- ISSN
- 0048-9697 (ISSN-L)
- OpenAlex
- W2075421710
- Cited by
- 69
- References
- 1
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 5 · 2023: 7 · 2022: 9 · 2021: 12 · 2020: 6 · 2019: 3 · 2018: 7 · 2017: 6 · 2016: 2 · 2015: 5 · 2014: 1
- FWCI
- 3.58
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Science of The Total Environment (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Environmental Engineering › Urban Heat Island Mitigation
- Physical Sciences › Environmental Science › Global and Planetary Change › Land Use and Ecosystem Services
- Social Sciences › Urban Studies › Urban Design and Spatial Analysis
- Keywords
- urban heat, Earth surface temperature, urban green structure, landscape metrics, edge density, land use structure, heat waves, climate change adaptation, urban planning, Leipzig
- MeSH terms
- Cities, City Planning, Environmental Exposure, Environmental Monitoring, Germany, Temperature, Urbanization, Climate Change
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review