{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T10:09:43Z","timestamp":1769162983930,"version":"3.49.0"},"reference-count":61,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2021,9,17]],"date-time":"2021-09-17T00:00:00Z","timestamp":1631836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005385","name":"Council for Higher Education","doi-asserted-by":"publisher","award":["postdoctoral scholarship"],"award-info":[{"award-number":["postdoctoral scholarship"]}],"id":[{"id":"10.13039\/501100005385","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>A functional urban area (FUA) is a geographic entity that consists of a densely inhabited city and a less densely populated commuting zone, both highly integrated through labor markets. The delineation of FUAs is important for comparative urban studies and it is commonly performed using census data and data on commuting flows. However, at the national scale, censuses and commuting surveys are performed at low frequency, and, on the global scale, consistent and comparable data are difficult to obtain overall. In this paper, we suggest and test a novel approach based on artificial light at night (ALAN) satellite data to delineate FUAs. As ALAN is emitted by illumination of thoroughfare roads, frequented by commuters, and by buildings surrounding roads, ALAN data can be used, as we hypothesize, for the identification of FUAs. However, as individual FUAs differ by their ALAN emissions, different ALAN thresholds are needed to delineate different FUAs, even those in the same country. To determine such differential thresholds, we use a multi-step approach. First, we analyze the ALAN flux distribution and determine the most frequent ALAN value observed in each FUA. Next, we adjust this value for the FUA\u2019s compactness, and run regressions, in which the estimated ALAN threshold is the dependent variable. In these models, we use several readily available, or easy-to-calculate, characteristics of FUA cores, such as latitude, proximity to the nearest major city, population density, and population density gradient, as predictors. At the next step, we use the estimated models to define optimal ALAN thresholds for individual FUAs, and then compare the boundaries of FUAs, estimated by modelling, with commuting-based delineations. To measure the degree of correspondence between the commuting-based and model-predicted FUAs\u2019 boundaries, we use the Jaccard index, which compares the size of the intersection with the size of the union of each pair of delineations. We apply the proposed approach to two European countries\u2014France and Spain\u2014which host 82 and 72 FUAs, respectively. As our analysis shows, ALAN thresholds, estimated by modelling, fit FUAs\u2019 commuting boundaries with an accuracy of up to 75\u2013100%, being, on the average, higher for large and densely-populated FUAs, than for small, low-density ones. We validate the estimated models by applying them to another European country\u2014Austria\u2014which demonstrates the prediction accuracy of 47\u201357%, depending on the model type used.<\/jats:p>","DOI":"10.3390\/rs13183714","type":"journal-article","created":{"date-parts":[[2021,9,22]],"date-time":"2021-09-22T03:47:35Z","timestamp":1632282455000},"page":"3714","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Delineating Functional Urban Areas Using a Multi-Step Analysis of Artificial Light-at-Night Data"],"prefix":"10.3390","volume":"13","author":[{"given":"Nataliya","family":"Rybnikova","sequence":"first","affiliation":[{"name":"Department of Mathematics, University of Leicester, Leicester LE1 7RH, UK"},{"name":"Department of Natural Resources and Environmental Management, University of Haifa, Haifa 3498838, Israel"},{"name":"Department of Geography and Environmental Studies, University of Haifa, Haifa 3498838, Israel"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1537-0832","authenticated-orcid":false,"given":"Boris","family":"Portnov","sequence":"additional","affiliation":[{"name":"Department of Natural Resources and Environmental Management, University of Haifa, Haifa 3498838, Israel"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8821-8711","authenticated-orcid":false,"given":"Igal","family":"Charney","sequence":"additional","affiliation":[{"name":"Department of Geography and Environmental Studies, University of Haifa, Haifa 3498838, Israel"}]},{"given":"Sviatoslav","family":"Rybnikov","sequence":"additional","affiliation":[{"name":"Institute of Evolution, University of Haifa, Haifa 3498838, Israel"},{"name":"Department of Evolutionary and Environmental Biology, University of Haifa, Haifa 3498838, Israel"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,17]]},"reference":[{"key":"ref_1","unstructured":"(2021, March 08). 68% of the World Population Projected to Live in Urban Areas by 2050, Says UN|UN DESA|United Nations Department of Economic and Social Affairs. Available online: https:\/\/www.un.org\/development\/desa\/en\/news\/population\/2018-revision-of-world-urbanization-prospects.html."},{"key":"ref_2","unstructured":"(2021, March 08). Urban Development Overview. Available online: https:\/\/www.worldbank.org\/en\/topic\/urbandevelopment\/overview."},{"key":"ref_3","first-page":"497","article-title":"Urban growth and water access in sub-Saharan Africa: Progress, challenges, and emerging research directions","volume":"607\u2013608","author":"Adams","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.apgeog.2018.07.002","article-title":"What drives urban growth in China? A multi-scale comparative analysis","volume":"98","author":"Li","year":"2018","journal-title":"Appl. Geogr."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1177\/0969776417694680","article-title":"Urban growth and decline: Europe\u2019s shrinking cities in a comparative perspective 1990\u20132010","volume":"25","author":"Wolff","year":"2018","journal-title":"Eur. Urban Reg. Stud."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.apgeog.2017.12.004","article-title":"Modelling the impact of urban growth on agriculture and natural land in Italy to 2030","volume":"91","author":"Martellozzo","year":"2018","journal-title":"Appl. Geogr."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1038\/s41893-019-0436-6","article-title":"Research gaps in knowledge of the impact of urban growth on biodiversity","volume":"3","author":"McDonald","year":"2020","journal-title":"Nat. Sustain."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1740","DOI":"10.1016\/j.scitotenv.2018.09.331","article-title":"Effects of urban growth spatial pattern (UGSP) on the land surface temperature (LST): A study in the Po Valley (Italy)","volume":"650","author":"Zullo","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.landurbplan.2011.03.017","article-title":"Mapping form and function in urban areas: An approach based on urban metrics and continuous impervious surface data","volume":"102","author":"Jacquet","year":"2011","journal-title":"Landsc. Urban Plan."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.compenvurbsys.2004.05.008","article-title":"An approach for analysis of urban morphology: Methods to derive morphological properties of city blocks by using an urban landscape model and their interpretations","volume":"29","author":"Yoshida","year":"2005","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1478","DOI":"10.1016\/j.buildenv.2008.06.013","article-title":"Policies and technical guidelines for urban planning of high-density cities - air ventilation assessment (AVA) of Hong Kong","volume":"44","author":"Ng","year":"2009","journal-title":"Build. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.landurbplan.2011.01.004","article-title":"Improving the wind environment in high-density cities by understanding urban morphology and surface roughness: A study in Hong Kong","volume":"101","author":"Ng","year":"2011","journal-title":"Landsc. Urban Plan."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.buildenv.2013.10.008","article-title":"Improving air quality in high-density cities by understanding the relationship between air pollutant dispersion and urban morphologies","volume":"71","author":"Yuan","year":"2014","journal-title":"Build. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1016\/j.landurbplan.2017.05.023","article-title":"Mapping urban form and function at city block level using spatial metrics","volume":"167","author":"Vanderhaegen","year":"2017","journal-title":"Landsc. Urban Plan."},{"key":"ref_15","unstructured":"(2021, March 09). Glossary: Functional Urban Area\u2014Statistics Explained. Available online: https:\/\/ec.europa.eu\/eurostat\/statistics-explained\/index.php\/Glossary:Functional_urban_area."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1111\/j.1467-9787.2008.00587.x","article-title":"URBAN CLUSTERS AS GROWTH FOCI*","volume":"49","author":"Portnov","year":"2009","journal-title":"J. Reg. Sci."},{"key":"ref_17","unstructured":"Dijkstra, L., Poelman, H., and Veneri, P. (2019). The EU-OECD definition of a functional urban area. OECD Reg. Dev. Work. Pap., 11."},{"key":"ref_18","first-page":"103275","article-title":"Definition Matters: Metropolitan Areas and Agglomeration Economies in a Large Developing Country","volume":"7","author":"Bosker","year":"2020","journal-title":"J. Urban Econ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.rse.2014.03.004","article-title":"A cluster-based method to map urban area from DMSP\/OLS nightlights","volume":"147","author":"Zhou","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3061","DOI":"10.1080\/01431160010007015","article-title":"Census from Heaven: An estimate of the global human population using night-time satellite imagery","volume":"22","author":"Sutton","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1080\/01431160304982","article-title":"Validation of urban boundaries derived from global night-time satellite imagery","volume":"24","author":"Henderson","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1080\/07420520802694020","article-title":"Global co-distribution of light at night (LAN) and cancers of prostate, colon, and lung in men","volume":"26","author":"Kloog","year":"2009","journal-title":"Chronobiol. Int."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2059","DOI":"10.1007\/s10552-010-9624-4","article-title":"Nighttime light level co-distributes with breast cancer incidence worldwide","volume":"21","author":"Kloog","year":"2010","journal-title":"Cancer Causes Control"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Haim, A., and Portnov, B.A. (2013). Light Pollution as a New Risk Factor for Human Breast and Prostate Cancers, Springer.","DOI":"10.1007\/978-94-007-6220-6"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1038\/ijo.2016.215","article-title":"GDP per capita and obesity prevalence worldwide: An ambiguity of effects modification","volume":"41","author":"Rybnikova","year":"2017","journal-title":"Int. J. Obes."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"047011","DOI":"10.1289\/EHP1837","article-title":"Evaluating the Association between Artificial Light-at-Night Exposure and Breast and Prostate Cancer Risk in Spain (MCC-Spain Study)","volume":"126","author":"Espinosa","year":"2018","journal-title":"Environ. Health Perspect."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"718","DOI":"10.1097\/EDE.0000000000001226","article-title":"Association between outdoor light-at-night exposure and colorectal cancer in Spain","volume":"31","author":"Espinosa","year":"2020","journal-title":"Epidemiology"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1579\/0044-7447-29.3.157","article-title":"Night-time Imagery as a Tool for Global Mapping of Socioeconomic Parameters and Greenhouse Gas Emissions","volume":"29","author":"Doll","year":"2000","journal-title":"AMBIO J. Hum. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1186\/1476-072X-4-5","article-title":"From wealth to health: Modelling the distribution of income per capita at the sub-national level using night-time light imagery","volume":"4","author":"Ebener","year":"2005","journal-title":"Int. J. Health Geogr."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"147","DOI":"10.2174\/1874923201003010147","article-title":"Shedding light on the global distribution of economic activity","volume":"3","author":"Ghosh","year":"2010","journal-title":"Open Geogr. J."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Wu, R., Yang, D., Dong, J., Zhang, L., and Xia, F. (2018). Regional Inequality in China Based on NPP-VIIRS Night-Time Light Imagery. Remote Sens., 10.","DOI":"10.3390\/rs10020240"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1080\/01431160500181861","article-title":"DMSP\/OLS night-time light imagery for urban population estimates in the Brazilian Amazon","volume":"27","author":"Amaral","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1003","DOI":"10.1080\/01431160802430693","article-title":"Modelling the population density of China at the pixel level based on DMSP\/OLS non-radiance-calibrated night-time light images","volume":"30","author":"Zhuo","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"5733","DOI":"10.1080\/01431161.2010.496798","article-title":"Characterizing relationships between population density and nighttime imagery for Denver, Colorado: Issues of scale and representation","volume":"31","author":"Anderson","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Mellander, C., Lobo, J., Stolarick, K., and Matheson, Z. (2015). Night-time light data: A good proxy measure for economic activity?. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0139779"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"472","DOI":"10.1002\/fee.1828","article-title":"Artificial light at night as a driver of evolution across urban-rural landscapes","volume":"16","author":"Hopkins","year":"2018","journal-title":"Front. Ecol. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1016\/j.tree.2010.09.007","article-title":"Light pollution as a biodiversity threat","volume":"25","author":"Wolter","year":"2010","journal-title":"Trends Ecol. Evol."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Narisada, K., and Schreuder, D. (2004). Light Pollution Handbook, Springer.","DOI":"10.1007\/978-1-4020-2666-9"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2715","DOI":"10.3390\/rs70302715","article-title":"Global Trends in Exposure to Light Pollution in Natural Terrestrial Ecosystems","volume":"7","author":"Bennie","year":"2015","journal-title":"Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"109227","DOI":"10.1016\/j.jenvman.2019.06.128","article-title":"Light pollution in USA and Europe: The good, the bad and the ugly","volume":"248","author":"Falchi","year":"2019","journal-title":"J. Environ. Manag."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/S0034-4257(97)00046-1","article-title":"A technique for using composite DMSP\/OLS \u201ccity lights\u201d satellite data to map urban area","volume":"61","author":"Imhoff","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1080\/2150704X.2014.905728","article-title":"Evaluation of NPP-VIIRS night-time light composite data for extracting built-up urban areas","volume":"5","author":"Shi","year":"2014","journal-title":"Remote Sens. Lett."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1614","DOI":"10.1007\/s11434-006-2006-3","article-title":"Restoring urbanization process in China in the 1990s by using non-radiance-calibrated DMSP\/OLS nighttime light imagery and statistical data","volume":"51","author":"He","year":"2006","journal-title":"Chin. Sci. Bull."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.landurbplan.2012.02.013","article-title":"Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008","volume":"106","author":"Liu","year":"2012","journal-title":"Landsc. Urban Plan."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2328","DOI":"10.1080\/13658816.2014.922186","article-title":"Object-based spatial cluster analysis of urban landscape pattern using nighttime light satellite images: A case study of China","volume":"28","author":"Yu","year":"2014","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_46","first-page":"62","article-title":"Why VIIRS data are superior to DMSP for mapping nighttime lights","volume":"35","author":"Elvidge","year":"2013","journal-title":"Proc. Asia-Pac. Adv. Netw."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Dou, Y., Liu, Z., He, C., and Yue, H. (2017). Urban Land Extraction Using VIIRS Nighttime Light Data: An Evaluation of Three Popular Methods. Remote Sens., 9.","DOI":"10.3390\/rs9020175"},{"key":"ref_48","unstructured":"(2021, August 08). Earth Observation Goup. Available online: https:\/\/eogdata.mines.edu\/products\/vnl\/."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"5860","DOI":"10.1080\/01431161.2017.1342050","article-title":"VIIRS night-time lights","volume":"38","author":"Elvidge","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.rse.2018.03.017","article-title":"NASA\u2019s Black Marble nighttime lights product suite","volume":"210","author":"Wang","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_51","unstructured":"(2020, June 03). Functional Urban Areas by Country\u2014OECD. Available online: https:\/\/www.oecd.org\/cfe\/regional-policy\/functionalurbanareasbycountry.htm."},{"key":"ref_52","unstructured":"(2020, March 17). LandScan Datasets|LandScan\u2122, Available online: https:\/\/landscan.ornl.gov\/landscan-datasets."},{"key":"ref_53","unstructured":"(2021, January 24). Measuring Compactness. Available online: https:\/\/fisherzachary.github.io\/public\/r-output.html."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1227","DOI":"10.1080\/13658816.2012.752093","article-title":"An Efficient Measure of Compactness for 2D Shapes and its Application in Regionalization Problems","volume":"27","author":"Li","year":"2013","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_55","first-page":"2","article-title":"The characteristics, causes, and consequences of sprawling development patterns in the United States","volume":"4","author":"Brody","year":"2013","journal-title":"Nat. Educ. Knowl."},{"key":"ref_56","unstructured":"(2021, April 04). SPSS Library: MANOVA and GLM. Available online: https:\/\/stats.idre.ucla.edu\/spss\/library\/spss-librarymanova-and-glm-2\/."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_58","unstructured":"(2021, January 05). Create Bag of Decision Trees\u2014MATLAB. Available online: https:\/\/www.mathworks.com\/help\/stats\/treebagger.html."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1580","DOI":"10.1016\/j.patrec.2012.04.003","article-title":"Dynamic Random Forests","volume":"33","author":"Bernard","year":"2012","journal-title":"Pattern Recognit. Lett."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Chung, N.C., Miasojedow, B., Startek, M., and Gambin, A. (2019). Jaccard\/Tanimoto similarity test and estimation methods. BMC Bioinform., 20.","DOI":"10.1186\/s12859-019-3118-5"},{"key":"ref_61","unstructured":"(2021, June 20). Global Human Settlement\u2014GHS POPULATION GRID\u2014European Commission. Available online: https:\/\/ghsl.jrc.ec.europa.eu\/ghs_pop.php."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/18\/3714\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:01:07Z","timestamp":1760166067000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/18\/3714"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,17]]},"references-count":61,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2021,9]]}},"alternative-id":["rs13183714"],"URL":"https:\/\/doi.org\/10.3390\/rs13183714","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,17]]}}}