BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//talks.osgeo.org//foss4g-it-2023//7GVM9B BEGIN:VTIMEZONE TZID:GMT BEGIN:STANDARD DTSTART:20001029T030000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:GMT TZOFFSETFROM:+0100 TZOFFSETTO:+0000 END:STANDARD BEGIN:DAYLIGHT DTSTART:20000326T020000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:BST TZOFFSETFROM:+0000 TZOFFSETTO:+0100 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:pretalx-foss4g-it-2023-9UWGEF@talks.osgeo.org DTSTART;TZID=GMT:20230616T093000 DTEND;TZID=GMT:20230616T094500 DESCRIPTION:Carlo Barletta\, Alessandra Capolupo\, Eufemia Tarantino\n\nNow adays\, data in an open format\, easily accessible and characterized by th e fact that they can be freely used and shared by anyone and for any purpo se\, play an important role due to the social and economic impact they can produce\, such as\, for instance\, the possibility of fostering the devel opment of new services based on them\, as well as the transparency and the democratic and participatory processes in public policies. In the field o f geographic information and Earth Observation (EO)\, the satellite images collected by Landsat and Sentinel initiatives are the most typical exampl e of open data. The former\, provided by National Aeronautics and Space Ad ministration (NASA) and United States Geological Survey (USGS)\, have a ge ometric resolution of 30m and have been accessible for decades\, whereas t he latter\, released by the European Union's Copernicus program\, have an accuracy of up to 10m and have been available since 2015. According to the literature\, both of them are useful for investigating and monitoring nat ural resources as well as environmental phenomena that occur on the Earth' s surface\, allowing for the assessment of numerous surface environmental variables on a local and regional scale. Among these\, the land surface al bedo\, which represents the capability of a surface to reflect incident so lar radiation\, is a useful parameter for climatic and hydrological studie s\, both in urban and rural contexts. Moreover\, the growing attention to the effects of climate change and urbanization on the environment and terr itory\, such as\, for example\, the Urban Heat Island (UHI) phenomenon\, d esertification\, and drought\, makes it necessary for these aforementioned sources of information to be freely and easily available to citizens\, re searchers and decision-makers.\n\n\nThe objective of this study is to esti mate the broadband land surface albedo and its spatial and temporal variab ility using accessible data from the Landsat 8 and Sentinel-2 satellites o ver two separate study areas: the city of Bari\, in Southern Italy\, and t he city of Berlin\, in North-eastern Germany. Because these two pilot site s have such disparate geomorphological features\, they allow generalizing of the research conclusion independent of environmental context. For this purpose\, various Landsat 8 and Sentinel-2 satellite images\, very close f or acquisition time and date\, and collected in different seasons\, from 2 018 to 2019\, were used. Furthermore\, the performance of the two implemen ted algorithms\, namely the Silva et al. approach for Landsat 8 data and t he Bonafoni et al. technique for Sentinel-2 data was assessed and statisti cally compared. Urban Atlas 2018 land use/land cover (LU/LC) class vector data\, provided in an open format by the Copernicus land monitoring servic e\, were used to better explore the variability of the albedo within each case study. These data were processed in the Google Earth Engine (GEE) pla tform\, which is free-to-use for research and non-commercial use\, and con sists of an integrated data catalogue mainly composed by open raster and v ector data\, e.g. Landsat and Sentinel images. Such catalogue\, daily upda ted\, is directly connected with the interactive programming environment\, on which it is possible to process satellite images by developing own cod es in JavaScript or Python languages. Most of its available tools are in o pen-source format. The statistical analysis\, on the other hand\, was carr ied out using the free and open-source R environment.\n\nFor both case stu dies\, the investigation revealed that the Landsat 8 approach produced som ewhat higher mean albedo values than the Sentinel-2 methodology. So far\, the statistical comparison indicated that\, for the Bari location\, all of the returned Landsat 8 and Sentinel-2 albedo maps were strongly correlate d\, with a correlation coefficient (ρ) higher than 0.84\; for Berlin\, in stead\, a medium-high correlation was discovered (ρ > 0.78). Additionally \, for both sites\, the findings appear to be more correlated when spring and summer scenarios are considered rather than other seasons. Indeed\, th e correlation between Landsat 8 and Sentinel 2 images appears to follow th e same seasonal pattern\, though more satellite images from more years sho uld be investigated for a more accurate interpretation. The dependability of the two approaches will be evaluated in the future through the collecti on of ground control points in field data campaigns. These new data will e nable the most accurate findings to be detected and the other methods to b e calibrated to increase their reliability. DTSTAMP:20260413T211505Z LOCATION:Sala Videoconferenza @ PoliBa SUMMARY:Open multitemporal Earth Observation data for land surface albedo e stimation in urban areas - Alessandra Capolupo\, Carlo Barletta URL:https://talks.osgeo.org/foss4g-it-2023/talk/9UWGEF/ END:VEVENT END:VCALENDAR