Document
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Continuant
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IOP Conference Series: Earth and Environmental Science
publication venue for: Analysing the land use/land cover influence on land surface temperature in San Luis Potosí Basin, México using remote sensing techniques
type: Book
type: Document
type: Continuant
type: Proceedings
type: Entity
type: Generically Dependent Continuant
type: Thing
type: Information Content Entity

Generically Dependent Continuant
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individual
rights: termsOfUse
date: 2026-08-27T05:31:25
publisher: vivo
type: Document
label: RDF description of Analysing the land use/land cover influence on land surface temperature in San Luis Potosí Basin, México using remote sensing techniques - http://orbis.uaslp.mx/vivo/individual/scopus9657

Analysing the land use/land cover influence on land surface temperature in San Luis Potosí Basin, México using remote sensing techniques
date time value: conference paper date 9658
type: Article
crisid: 9658
issue: 1
most specific type: Conference Paper
type: Conference Paper
related by: authorship_66940
abstract: Changes in Land Use/Land Cover (LULC) generate several impacts which affect the energy balance of the Earth and, consequently, modifying the climate of a region. Accordingly, one of the most important indicators of this modification is the Land Surface Temperature (LST). The present work aims to analyze the relationship between LULC and LST, determining the influence of LULC on LST using Geographical Information Systems (GIS) and Remote Sensing (RS) techniques. The selected study area was the San Luis Potosí Basin, México (SLPB). A temporal analysis has been developed for 2007 and 2020. Satellite images from Landsat 5 TM and 8 OLI/TIRS has been used to calculate LST through a single-channel algorithm for winter and spring. LULC has been determined from a supervised classification with neural network algorithm. Finally, change rates for LULC and LST were assessed. The results indicate that an LST increase of 11 C from 2007 to 2020 has been detected in the region. Also, results showed that covers with spare vegetation or without vegetation have the highest temperatures (29 C to 32 C). In comparison, the covers with dense vegetation and water showed the lowest temperatures (23 C to 25 C). This type of research allows addressing the LULC effects on LST, as well as prove its importance in improving land use planning systems. © Published under licence by IOP Publishing Ltd.
accesstype: All Open Access, Bronze
type: Generically Dependent Continuant
freetext keyword: Agriculture; Atmospheric temperature; Land use; Remote sensing; Surface measurement; Surface properties; Vegetation; Energy balance of the earth; Highest temperature; Land Use Planning; Land use/land cover; Neural network algorithm; Remote sensing techniques; Single-channel algorithms; Supervised classification; Land surface temperature
type: Thing
artnum: 12029
related by: authorship_66941
doi: 10.1088/1755-1315/686/1/012029
type: Document
volume: 686
most specific type: Document
type: Information Content Entity
type: Continuant
EI dscopus: 2-s2.0-85104199581
type: Entity
origen: scopus
estado: published
has publication venue: IOP Conference Series: Earth and Environmental Science

Article
type: Class

Information Content Entity
type: Class

Conference Paper
type: Class