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Remote Sens. 2014, 6(7), 6266-6282; doi:10.3390/rs6076266

Local Illumination Influence on Vegetation Indices and Plant Area Index (PAI) Relationships

1,* , 1
1 Instituto Nacional de Pesquisas Espaciais, Avenida dos Astronautas, 1758, São José dos Campos 12227, Brazil 2 Departamento de Tecnologia, Universidade Estadual de Maringá, Avenida Colombo, 5790, Jd. Universitário, Maringá 87020, Brazil
* Author to whom correspondence should be addressed.
Received: 19 March 2014 / Revised: 24 June 2014 / Accepted: 25 June 2014 / Published: 3 July 2014
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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.
Keywords: NDVI; NDMI; biophysical parameters; remote sensing data acquisition NDVI; NDMI; biophysical parameters; remote sensing data acquisition
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Ponzoni, F.J.; Silva, C.B.; Santos, S.B.; Montanher, O.C.; Santos, T.B. Local Illumination Influence on Vegetation Indices and Plant Area Index (PAI) Relationships. Remote Sens. 2014, 6, 6266-6282.

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