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@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 = "29 nov. 2020"
}


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