View-illumination effects on hyperspectral vegetation indices in the Amazonian tropical forest

Abstract Because of the pointing capability of the Hyperion/Earth Observing-One (EO-1) to improve the revisit time of the scene, temporal series of narrowband vegetation indices (VIs) can be generated to study the phenology of the Amazonian tropical forests. In this study, 10 selected narrowband VIs calculated from Hyperion nadir and off-nadir data and from different view directions (forward scattering and backscattering) were analyzed for their sensitivity to view-illumination effects along the dry season on the Seasonal Semi-deciduous Forest. Data analysis was also supported by PROSAIL modeling to simulate the spectral response of this forest type in both directions. Hyperion and PROSAIL results showed that the Enhanced Vegetation Index (EVI) and Photochemical Reflectance Index (PRI) were the two more anisotropic VIs, whereas the Normalized Difference Vegetation Index (NDVI), Structure Insensitive Pigment Index (SIPI) and the Vogelmann Red Edge Index (VOG) were comparatively less sensitive to view-illumination effects. When compared to the other VIs and because of the greater dependence on the near-infrared (NIR) reflectance, EVI showed a different spectral behavior. EVI increased from forward scattering to backscattering and with decreasing solar zenith angle (SZA) towards the end of the local dry season, due to reduction in shading and enhancement of the illumination effects. On the other hand, PRI was higher with increasing shading in the forward scattering direction, as deduced from the PROSAIL simulation. Results emphasized the importance of taking into account bidirectional effects when analyzing temporal series of VIs collected over tropical forests by imaging spectrometers with pointing capability or even by multispectral sensors with large field-of-view (FOV).

[1]  Robert O. Green,et al.  Temporal and spatial patterns in vegetation and atmospheric properties from AVIRIS , 1997 .

[2]  A. Gitelson,et al.  Novel algorithms for remote estimation of vegetation fraction , 2002 .

[3]  Michael E. Schaepman,et al.  Estimating canopy water content using hyperspectral remote sensing data , 2010, Int. J. Appl. Earth Obs. Geoinformation.

[4]  Elizabeth M. Middleton,et al.  Regional mapping of gross light-use efficiency using MODIS spectral indices , 2008 .

[5]  Kamel Didan,et al.  Assessment of phenologic variability in Amazon tropical rainforests using hyperspectral hyperion and MODIS satellite data , 2008 .

[6]  Lênio Soares Galvão,et al.  Directional effects on NDVI and LAI retrievals from MODIS: A case study in Brazil with soybean , 2011, Int. J. Appl. Earth Obs. Geoinformation.

[7]  W. Verhoef,et al.  PROSPECT+SAIL models: A review of use for vegetation characterization , 2009 .

[8]  F. Baret,et al.  PROSPECT: A model of leaf optical properties spectra , 1990 .

[9]  G. Asner,et al.  Drought stress and carbon uptake in an Amazon forest measured with spaceborne imaging spectroscopy. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[10]  B. Gao NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space , 1996 .

[11]  Gail P. Anderson,et al.  Analysis of Hyperion data with the FLAASH atmospheric correction algorithm , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[12]  J. A. Schell,et al.  Monitoring vegetation systems in the great plains with ERTS , 1973 .

[13]  B. Rock,et al.  Detection of changes in leaf water content using Near- and Middle-Infrared reflectances , 1989 .

[14]  A. Gitelson,et al.  Detection of Red Edge Position and Chlorophyll Content by Reflectance Measurements Near 700 nm , 1996 .

[15]  Wim Bakker,et al.  Imaging Spectrometry: Basic Analytical Techniques , 2002 .

[16]  E. Vermote,et al.  Seasonal and inter-annual variation in view angle effects on MODIS vegetation indices at three forest sites , 2011 .

[17]  Josep Peñuelas,et al.  The photochemical reflectance index (PRI) and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies: A review and meta-analysis , 2011 .

[18]  S. Phinn,et al.  Assessing viewing and illumination geometry effects on the MODIS vegetation index (MOD13Q1) time series: implications for monitoring phenology and disturbances in forest communities in Queensland, Australia , 2011 .

[19]  D. Roberts,et al.  View angle effects on the discrimination of soybean varieties and on the relationships between vegetation indices and yield using off-nadir Hyperion data , 2009 .

[20]  P. Switzer,et al.  A transformation for ordering multispectral data in terms of image quality with implications for noise removal , 1988 .

[21]  Ang P.S.,et al.  Master\'s Dissertation , 2009 .

[22]  R. Rodrigues,et al.  Classificação fitogeográfica das florestas do Alto Rio Xingu , 2008 .

[23]  Hao Chen,et al.  Processing Hyperion and ALI for forest classification , 2003, IEEE Trans. Geosci. Remote. Sens..

[24]  John Shepanski,et al.  Hyperion, a space-based imaging spectrometer , 2003, IEEE Trans. Geosci. Remote. Sens..

[25]  D. M. Moss,et al.  Red edge spectral measurements from sugar maple leaves , 1993 .

[26]  E. Vermote,et al.  Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer , 1997 .

[27]  M. Schaepman,et al.  Angular sensitivity analysis of vegetation indices derived from CHRIS/PROBA data , 2008 .

[28]  Robert O. Green,et al.  On-orbit radiometric and spectral calibration characteristics of EO-1 Hyperion derived with an underflight of AVIRIS and in situ measurements at Salar de Arizaro, Argentina , 2003, IEEE Trans. Geosci. Remote. Sens..

[29]  W. Verhoef Light scattering by leaf layers with application to canopy reflectance modelling: The SAIL model , 1984 .

[30]  J. Boardman Automating spectral unmixing of AVIRIS data using convex geometry concepts , 1993 .

[31]  Fred A. Kruse,et al.  Comparison of airborne hyperspectral data and EO-1 Hyperion for mineral mapping , 2003, IEEE Trans. Geosci. Remote. Sens..

[32]  J. Gamon,et al.  The photochemical reflectance index: an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels , 1997, Oecologia.

[33]  D. Roberts,et al.  On intra-annual EVI variability in the dry season of tropical forest A case study with MODIS and hyperspectral data , 2011 .

[34]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[35]  N. C. Strugnell,et al.  First operational BRDF, albedo nadir reflectance products from MODIS , 2002 .