{"type": "FeatureCollection", "features": [{"id": "10.1016/j.envsoft.2017.09.020", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:15:52Z", "type": "Journal Article", "created": "2017-10-27", "title": "Urban Multi-scale Environmental Predictor (UMEP): An integrated tool for city-based climate services", "description": "UMEP (Urban Multi-scale Environmental Predictor), a city-based climate service tool, combines models and tools essential for climate simulations. Applications are presented to illustrate UMEP's potential in the identification of heat waves and cold waves; the impact of green infrastructure on runoff; the effects of buildings on human thermal stress; solar energy production; and the impact of human activities on heat emissions. UMEP has broad utility for applications related to outdoor thermal comfort, wind, urban energy consumption and climate change mitigation. It includes tools to enable users to input atmospheric and surface data from multiple sources, to characterise the urban environment, to prepare meteorological data for use in cities, to undertake simulations and consider scenarios, and to compare and visualise different combinations of climate indicators. An open-source tool, UMEP is designed to be easily updated as new data and tools are developed, and to be accessible to researchers, decision-makers and practitioners.", "keywords": ["Urban climate services", "MEAN RADIANT TEMPERATURE", "THERMAL COMFORT", "FLUXES", "SURFACE COVER", "CITIES", "Heat risk", "BALANCE SCHEME SUEWS", "Green infrastructure", "01 natural sciences", "7. Clean energy", "LOCAL CLIMATE", "MODEL", "Physical sciences", "Environmental sciences", "Solar energy", "13. Climate action", "11. Sustainability", "ANTHROPOGENIC HEAT", "ENERGY-BALANCE", "QGIS", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://centaur.reading.ac.uk/73171/2/1-s2.0-S1364815217304140-main.pdf"}, {"href": "https://doi.org/10.1016/j.envsoft.2017.09.020"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Modelling%20%26amp%3B%20Software", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.envsoft.2017.09.020", "name": "item", "description": "10.1016/j.envsoft.2017.09.020", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.envsoft.2017.09.020"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-01-01T00:00:00Z"}}, {"id": "10.1109/JURSE.2017.7924591", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:18:22Z", "type": "Journal Article", "created": "2017-05-12", "title": "ANthropogenic heat FLUX estimation from Space", "description": "The H2020-Space project URBANFLUXES (URBan ANthrpogenic heat FLUX from Earth observation Satellites) investigates the potential of Copernicus Sentinels to retrieve anthropogenic heat flux, as a key component of the Urban Energy Budget (UEB). URBANFLUXES advances the current knowledge of the impacts of UEB fluxes on urban heat island and consequently on energy consumption in cities. This will lead to the development of tools and strategies to mitigate these effects, improving thermal comfort and energy efficiency. In URBANFLUXES, the anthropogenic heat flux is estimated as a residual of UEB. Therefore, the rest UEB components, namely, the net all-wave radiation (Q*), the net change in heat storage (\u0394Qs) and the turbulent sensible (Q H ) and latent (Q E ) heat fluxes are independently estimated from Earth Observation (EO), whereas the advection term is included in the error of the anthropogenic heat flux estimation from the UEB closure. The project exploits Sentinels observations, which provide improved data quality, coverage and revisit times and increase the value of EO data for scientific work and future emerging applications. These observations can reveal novel scientific insights for the detection and monitoring of the spatial distribution of the urban energy budget fluxes in cities, thereby generating new EO opportunities. URBANFLUXES thus exploits the European capacity for space-borne observations to enable the development of operational services in the field of urban environmental monitoring and energy efficiency in cities.", "keywords": ["[SDU] Sciences of the Universe [physics]", "13. Climate action", "Copernicus Sentinels", "11. Sustainability", "0211 other engineering and technologies", "Earth Observation", "02 engineering and technology", "01 natural sciences", "7. Clean energy", "Urban Climate", "Urban Energy Budget", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://xplorestaging.ieee.org/ielx7/7919506/7924526/07924591.pdf?arnumber=7924591"}, {"href": "https://doi.org/10.1109/JURSE.2017.7924591"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2017%20Joint%20Urban%20Remote%20Sensing%20Event%20%28JURSE%29", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1109/JURSE.2017.7924591", "name": "item", "description": "10.1109/JURSE.2017.7924591", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1109/JURSE.2017.7924591"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-03-01T00:00:00Z"}}, {"id": "10.24057/2071-9388-2019-10", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-26T16:20:21Z", "type": "Journal Article", "created": "2019-11-26", "title": "Simultaneous assessment of the summer urban heat island in Moscow megacity based on in situ observations, thermal satellite images and mesoscale modeling", "description": "<p>This study compares three popular approaches to quantify the urban heat island (UHI) effect in Moscow megacity in a summer season (June-August 2015). The first approach uses the measurements of the near-surface air temperature obtained from weather stations, the second is based on remote sensing from thermal imagery of MODIS satellites, and the third is based on the numerical simulations with the mesoscale atmospheric model COSMO-CLM coupled with the urban canopy scheme TERRA_URB. The first approach allows studying the canopy-layer UHI (CLUHI, or anomaly of a near- surface air temperature), while the second allows studying the surface UHI (SUHI, or anomaly of a land surface temperature), and both types of the UHI could be simulated by the atmospheric model. These approaches were compared in the daytime, evening and nighttime conditions. The results of the study highlight a substantial difference between the SUHI and CLUHI in terms of the diurnal variation and spatial structure. The strongest differences are found at the daytime, at which the SUHI reaches the maximal intensity (up to 10\uffc2\uffb0\uffd0\uffa1) whereas the CLUHI reaches the minimum intensity (1.5\uffc2\uffb0\uffd0\uffa1). However, there is a stronger consistency between CLUHU and SUHI at night, when their intensities converge to 5\uffe2\uff80\uff936\uffc2\uffb0\uffd0\uffa1. In addition, the nighttime CLUHI and SUHI have similar monocentric spatial structure with a temperature maximum in the city center. The presented findings should be taken into account when interpreting and comparing the results of UHI studies, based on the different approaches. The mesoscale model reproduces the CLUHI-SUHI relationships and provides good agreement with in situ observations on the CLUHI spatiotemporal variations (with near-zero biases for daytime and nighttime CLUHI intensity and correlation coefficients more than 0.8 for CLUHI spatial patterns). However, the agreement of the simulated SUHI with the remote sensing data is lower than agreement of the simulated CLUHI with in situ measurements. Specifically, the model tends to overestimate the daytime SUHI intensity. These results indicate a need for further in-depth investigation of the model behavior and SUHI\uffe2\uff80\uff93CLUHI relationships in general.</p>", "keywords": ["modis", "Geography (General)", "COSMO", "suhi", "0207 environmental engineering", "uhi", "land surface temperature", "UHI", "urban heat island", "moscow", "02 engineering and technology", "Moscow", "01 natural sciences", "thermal satellite images", "remote sensing", "MODIS", "13. Climate action", "Earth and Environmental Sciences", "SUHI", "cosmo", "urban climate", "11. 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