BIBLIOS

  Ciências References Management System

Visitor Mode (Login)
Need help?


Back

Publication details

Document type
Journal articles

Document subtype
Full paper

Title
Contribution of Land Surface Temperature (TCI) to Vegetation Health Index: A Comparative Study Using Clear Sky and All-Weather Climate Data Records

Participants in the publication
Virgílio A. Bento (Author)
IDL - Instituto Dom Luiz
Isabel Trigo (Author)
Instituto Dom Luiz (IDL), Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749–016, Lisboa, Portugal
Célia Gouveia (Author)
Dep. Engenharia Geográfica, Geofísica e Energia
IDL - Instituto Dom Luiz
Carlos DaCamara (Author)
Dep. Engenharia Geográfica, Geofísica e Energia
IDL - Instituto Dom Luiz

Date of Publication
2018-08-21

Where published
Remote Sensing

Publication Identifiers
ISSN - 2072-4292

Publisher
MDPI AG

Volume
10
Number
9

Starting page
1324

Document Identifiers
DOI - https://doi.org/10.3390/rs10091324
URL - http://dx.doi.org/10.3390/rs10091324

Rankings
SCIMAGO Q1 (2018) - 1.43 - Earth and Planetary Sciences (miscellaneous)
SCOPUS Q1 (2017) - 1.386 - General Earth and Planetary Sciences
Web Of Science Q1 (2018) - 4.118 - REMOTE SENSING - SCIE


Export

APA
Virgílio A. Bento, Isabel Trigo, Célia Gouveia, Carlos DaCamara, (2018). Contribution of Land Surface Temperature (TCI) to Vegetation Health Index: A Comparative Study Using Clear Sky and All-Weather Climate Data Records. Remote Sensing, 10, ISSN 2072-4292. eISSN . http://dx.doi.org/10.3390/rs10091324

IEEE
Virgílio A. Bento, Isabel Trigo, Célia Gouveia, Carlos DaCamara, "Contribution of Land Surface Temperature (TCI) to Vegetation Health Index: A Comparative Study Using Clear Sky and All-Weather Climate Data Records" in Remote Sensing, vol. 10, 2018. 10.3390/rs10091324

BIBTEX
@article{37394, author = {Virgílio A. Bento and Isabel Trigo and Célia Gouveia and Carlos DaCamara}, title = {Contribution of Land Surface Temperature (TCI) to Vegetation Health Index: A Comparative Study Using Clear Sky and All-Weather Climate Data Records}, journal = {Remote Sensing}, year = 2018, volume = 10 }