@Article{PonzoniSilSanSanMon:2014:LoIlIn,
author = "Ponzoni, Fl{\'a}vio Jorge and Silva, Clayton Borges da and
Santos, Sandra Benfica dos and Santos, Thiago Batista dos and
Montanher, Ot{\'a}vio Cristiano",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Universidade Estadual de Maring{\'a}
(UEM)}",
title = "Local illumination influence on Vegetation Indices and Plant Area
index (PAI) relationships",
journal = "Remote Sensing",
year = "2014",
volume = "6",
pages = "6266--6282",
month = "July",
keywords = "NDVI, NDMI, biophysical parameters, remote sensing data
acquisition.",
abstract = "Relationships between biophysical parameters and radiometric data
have been tested and evaluated by several professionals using
empirical and/or physical approaches. Remote sensing data
collected from airborne or orbital platforms are, of course,
influenced by different factors, such as illumination/observation
geometry (data collection geometry), atmospheric effects, etc.,
rather than by target spectral properties. Besides that, the
target topographic positioning actually defines the amount of
incident energy, as well as the amount of energy that is reflected
toward the sensor. The sum of both data collection geometry and
topographic positioning defines the so-called local illumination.
The objective of this paper was to evaluate the influence of local
illumination on empirical relationships between a biophysical
variable (plant area index, PAI) and two vegetation indices
calculated from Resourcesat/Linear Imaging Self-Scanner sensor
(LISS-3) orbital data. Local illumination was expressed by the
cosine factor (Fcos) and calculated from topographic and solar
position data at three different dates. The study area was based
on a typical Brazilian southeastern forest fragment located in the
Augusto Ruschi municipal preservation park dispersed on roughhouse
topography. PAI was estimated by hemispherical photographs taken
under the forest canopy from sample points arbitrarily dispersed
on the forest fragment. Results confirmed a stronger relationship
between vegetation indices and local illumination conditions.",
doi = "10.3390/rs6076266",
url = "http://dx.doi.org/10.3390/rs6076266",
issn = "2072-4292",
label = "self-archiving-INPE-MCTI-GOV-BR",
language = "en",
targetfile = "remotesensing-06-06266.pdf",
urlaccessdate = "27 abr. 2024"
}