Moreno Falcón, MónicaBertolín, C.Ortiz, PilarOrtiz Calderón, Rocío2024-07-302024-07-302022Moreno, M., Bertolín, C., Ortiz, P., & Ortiz, R. (2022). Satellite product to map drought and extreme precipitation trend in Andalusia, Spain: a novel method to assess heritage landscapes at risk. International Journal of Applied Earth Observation and Geoinformation, 110, 102810./10.1016/j.jag.2022.102810https://hdl.handle.net/10433/21582Art-Risk (RETOS project of Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional (FEDER), code: BIA2015-64878-R (MINECO/FEDER, UE)), Art-Risk cooperacion: ´Conservacion ´ preventiva frente a rehabilitacion ´ de urgencia del Patrimonio Arquitectonico ´ mediante Investigacion ´ sobre Riesgos y Vulnerabilidad frente al Cambio Climatico, ´ desastres naturales y antropicos ´ (project of Consejería de Fomento, Infraestructuras y Ordenacion ´ del Territorio, Junta de Andalucía UPO-03), FENIX (project of Ministerio de Ciencia e Innovacion, ´ Programas Estatales de Generacion ´ de Conocimiento y Fortalecimiento Científico y Tecnologico ´ del Sistema de I + D + i, code: PID2019-107257RB-I00), Diagnostico ´ y Catalogacion ´ del Patrimonio Arquitectonico ´ Andaluz mediante Analisis ´de Riesgos y vulnerabilidad (project of Consejería de fomento, infraestructuras y ordenacion ´ del territorio de la Junta de Andalucía UPO.20-01), RESILIENT-TOURISM project of Consejería de Transformacion ´Economica, ´ Industria, Conocimiento y Universidades. Junta de Andalucia (PYC20 RE 034 UPO), the research teams TEP-199 and Sanit-ARTE laboratory. The Art-Risk methodology has been awarded the Europa Nostra 2020 prize. M. Moreno is grateful to the State Program for the Promotion of Talent and its Employability in R + D + i of Ministerio de Ciencia e Innovacion ´ of Spain for his technical fellowship (PTA2019-016882) and for his research stay in the Norwegian University of Science and Technology (Norway).The objective of this work is to develop a methodology for the identification of extreme rain and drought events that have occurred in the last 30 years using products derived from satellite images. Proposed methodology uses statistical reducers such as percentile, drought indexes, and map algebra at a geo big data scale. The daily precipitation data from the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record and Climate Hazards Group InfraRed Precipitation with Station Data were validated by comparison with ground station data. Extreme event maps were obtained from the use of high percentiles. Drought maps were obtained from the standardized precipitation index using low percentiles. The data were migrated to a geographic information system that allows interrelation with other geographic data. Its application to the study of the fortifications preserved in Andalusia classified all structures according to the level of exposure to these dangers and identified two areas of precipitation with different characteristics according to the influence of existing teleconnection patterns. Applied to the study of heritage landscapes, this methodological model minimizes the uncertainty associated with the use of satellite precipitation products, facilitates the planning of preventive conservation activities, and the management of existing resources in occurrence of extreme events.application/pdfenAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Earth fortificationMediterranean areaRemote sensingTorrential rainsDroughtRiskGeo big datajournal articleopen access