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Dataset . 2022
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ZENODO
Dataset . 2022
License: CC BY
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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A Google Earth Engine code to analyze e visualize land surface temperature and thermal hot-spot patterns: a Rome (Italy) case study

Authors: Guerri, Giulia; Crisci, Alfonso; Morabito, Marco;

A Google Earth Engine code to analyze e visualize land surface temperature and thermal hot-spot patterns: a Rome (Italy) case study

Abstract

Link to the Google Earth Engine (GEE) code: https://code.earthengine.google.com/cc3ea6593574e321acd7b68c975a9608 You can analyze and visualize the following spatial layers by accessing the GEE link: Daytime summer land surface temperature (raster data, 30 m horizontal resolution, from Landsat-8 remote sensing data, years 2017-2022) The surface thermal hot-spot pattern (raster data,30 m horizontal resolution) was obtained by using a statistical-spatial method based on the Getis-Ord Gi* approach through the ArcGIS tool. Here attached the .txt file from the GEE code. E-mail Giulia Guerri, CNR-IBE, giulia.guerri@ibe.cnr.it Marco Morabito, CNR-IBE, marco.morabito@cnr.it Alfonso Crisci, CNR-IBE, alfonso.crisci@ibe.cnr.it

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Keywords

remote sensing, Roma, thermal hot-spot, surface urban heat island, urban climate, Landsat-8, land surface temperature, temperature superficiali, isola di calore

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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