@InProceedings{BertaniAndeAragWagn:2017:ReSeSo,
author = "Bertani, Gabriel and Anderson, Liana Oighenstein and Arag{\~a}o,
Luiz Eduardo Oliveira e Cruz de and Wagner, Fabien Hubert",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {} and
{Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Remote sensing of solar-induced chlorophyll fluorescence for
describing photosynthesis seasonality in the Amazon forest",
booktitle = "Anais...",
year = "2017",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "2516--2523",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "Recently, a new way of studying photosynthesis by remote sensing
have been discovered, through the solar induced CHolorophyll
Fluorescence (ChlF). In this paper, we review the main concepts
and mechanisms used to retrieve ChlF by remote sensing. This
includes space-based approaches, whose ChlF retrieval is more
difficult to be achieved mainly due to atmospheric and sensors
limitation issues, that can be mitigated with the launch of the
FLEX mission. In addition, a set of ChlF data from the Gome-2
sensor and incident radiation reanalysis data from GLDAS, spanning
the 2007-2015 period, were used to analyze the relationship
between photosynthesis and radiation seasonality in the Amazon
forest by decomposing the original data through the BFAST
algorithm. The maximum incident radiation is observed from August
to October in most part of the Amazon forest. On the other hand,
the maximum photosynthesis activity occurs mainly from September
to December. The photosynthetic activity increased after incident
radiation raised, with a time-lag varying from one to three
months, potentially related to the production of new leaves after
the vegetation perceived the increase in the radiation signal.
Photosynthesis seasonality thus varies spatially and seems to have
a strong relation with radiation signals in the Amazon forest.",
conference-location = "Santos",
conference-year = "28-31 maio 2017",
isbn = "978-85-17-00088-1",
label = "59264",
language = "en",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3PSLQNH",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSLQNH",
targetfile = "59264.pdf",
type = "Floresta e outros tipos de vegeta{\c{c}}{\~a}o",
urlaccessdate = "27 abr. 2024"
}