GENERAL INFORMATION
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1. Dataset title:
temp_distribution_green_areas [dataset]


2. Authorship:

	Name: Luis Pérez-Urrestarazu
	Institution: Universidad de Sevilla
	Email: lperez@us.es
	ORCID:  0000-0002-3378-9285

Other authors: Rodríguez Gómez, Francisco; Fernández Cañero, Rafael; Pérez, Gabriel; del Campo-Ávila, José; López-Rodríguez, Domingo

DESCRIPTION
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1. Dataset language:
English


2. Abstract:
Dataset acquired for the study published in the article: “Detection of unfavourable urban areas with higher temperatures and lack of green spaces using satellite imagery in sixteen Spanish cities”. This is part of the project “Urban Sustainability using new Data Mining developments (URSUS-DM)” the Spanish R & D Programme for projects addressing the challenges of the society (2018 call), in the framework
of the State Plan of Scientific and Technical Research and Innovation 2017–2020, financed by the Spanish Ministry of Science, Innovation and Universities, grant number RTI2018095097-B-100.
This study aims to identify the most unfavourable areas of a city in terms of high temperatures and the absence of green infrastructure. An automatic methodology based on remote sensing and data analysis has been developed and applied in sixteen Spanish cities with different characteristics. Landsat-8 satellite images were selected for each city from the July-August period of 2019 and 2020 to calculate the spatial variation of land surface temperature (LST). The Normalized Difference Vegetation Index (NDVI) was used to determine the abundance of vegetation across the city. Based on the NDVI and LST maps created, a k-means unsupervised classification clustering was performed to automatically identify the different clusters according to how favourable these areas were in terms of temperature and presence of vegetation. A Disadvantaged Area Index (DAI), combining both variables, was developed to produce a map showing the most unfavourable areas for each city.


3. Keywords: 
Urban greening; Remote sensing; Heat island; Normalized difference vegetation index; Landsat-8

4. Date of data collection:
2019 and 2020

5. Publication Date:
15-12-2023


6. Grant information:

	Grant Agency: Ministerio de Ciencia, Innovación y Universidades
	Grant Number: RTI2018095097-B-100


7. Geographical location/s of data collection:
Madrid, Sevilla, Murcia, Ciudad Real, Alcobendas, Barcelona, Valencia, Málaga, Palma de Mallorca, Bilbao, Vigo, Vitoria, Santiago de Compostela, Zaragoza, Huesca, Lleida (Spain)

ACCESS INFORMATION
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1. Creative Commons License of the dataset:
CC BY-NC-SA

2. Dataset DOI:
https://doi.org/10.12795/11441/152674

3. Related publication:
Rodríguez-Gómez, F., Fernández-Cañero, R., Pérez, G., del Campo-Ávila, J., López-Rodríguez, D., Pérez-Urrestarazu, L. 2022. Detection of unfavourable urban areas with higher temperatures and lack of green spaces using satellite imagery in sixteen Spanish cities. Urban Forestry and Urban Greening 78, 127783. doi: 10.1016/j.ufug.2022.127783
 



VERSIONING AND PROVENANCE
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1. Last modification date:
12-12-2023 


2. Were data derived from another source?:
No 


3. Additional related data not included in this dataset:
No


FILE OVERVIEW 
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Appendix A: maps with the spatial distribution of land surface temperatures (LST) and Normalized Difference Vegetation Index (NDVI)
Appendix B: maps with the most unfavourable areas
Appendix C: maps with the spatial distribution of land surface temperatures (LST), Normalized Difference Vegetation Index (NDVI), and unfavourable areas with the Disadvantaged Area Index (DAI) values presented for Seville and Malaga to compare results in the different seasons of 2020
Appendix D: maps of the spatial distribution of the vegetation derived from the Normalized Difference Vegetation Index compared with the maps of Land Cover/Use classes established in the Urban Atlas of the Copernicus project for Seville and Malaga.
Kmz maps with the distribution of the most unfavourable areas for each city