Marti Renaud auteur aut IRD Li Z. C. auteur aut IRD Catry Thibault auteur aut IRD Roux Emmanuel auteur aut IRD Mangeas Morgan auteur aut IRD Handschumacher Pascal auteur aut IRD Gaudart J. auteur aut IRD Tran A. auteur aut IRD Demagistri Laurent auteur aut IRD Faure Jean-François auteur aut IRD Carvajal J. J. auteur aut IRD Drumond B. auteur aut IRD Xu L. auteur aut IRD Herbreteau Vincent auteur aut IRD Gurgel H. auteur aut IRD Dessay Nadine auteur aut IRD Gong P. auteur aut IRD text journalArticle eng text/pdf reformatted digital access To date, there is no effective treatment to cure dengue fever, a mosquito-borne disease which has a major impact on human populations in tropical and sub-tropical regions. Although the characteristics of dengue infection are well known, factors associated with landscape are highly scale dependent in time and space, and therefore difficult to monitor. We propose here a mapping review based on 78 articles that study the relationships between landscape factors and urban dengue cases considering household, neighborhood and administrative levels. Landscape factors were retrieved from survey questionnaires, Geographic Information Systems (GIS), and remote sensing (RS) techniques. We structured these into groups composed of land cover, land use, and housing type and characteristics, as well as subgroups referring to construction material, urban typology, and infrastructure level. We mapped the co-occurrence networks associated with these factors, and analyzed their relevance according to a three-valued interpretation (positive, negative, non significant). From a methodological perspective, coupling RS and GIS techniques with field surveys including entomological observations should be systematically considered, as none digital land use or land cover variables appears to be an univocal determinant of dengue occurrences. Remote sensing urban mapping is however of interest to provide a geographical frame to distribute human population and movement in relation to their activities in the city, and as spatialized input variables for epidemiological and entomological models. specialized Dengue Urban landscape environment remote sensing interdisciplinary MONDE 052 050 126 102 12 6 art. 932 [82 ] 2020 https://www.documentation.ird.fr/hor/fdi:010079027 10.3390/rs12060932 [F B010079027] https://www.documentation.ird.fr/hor/fdi:010079027 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers20-05/010079027.pdf IRD - Base Horizon / Pleins textes 2020-06-09 2025-02-24 fdi:010079027 fre