Use este identificador para citar ou linkar para este item: https://repositorio.inpa.gov.br/handle/1/17064
Título: Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations
Autor: Moura, Yhasmin Mendes
Galvão, L. S.
Hilker, Thomas
Wu, Jin
Saleska, Scott Reid
Amaral, Cibele Hummel do
Nelson, Bruce Walker
Lopes, Aline Pontes
Wiedeman, Kenia K.
Prohaska, Neill
Oliveira, Raimundo Cosme de
Machado, Carolyne Bueno
Aragao, L. E.O.C.
Palavras-chave: Cameras
Drought
Forestry
Radiometers
Remote Sensing
Satellite Imagery
Spectrum Analysis
Vegetation
Amazon
Dry Seasons
Hyperspectral Remote Sensing
Leaf Flush
Phenology
Seasonality
Tropical Species
Principal Component Analysis
Algorithm
Angiosperm
Dry Season
Leaf
Leaf Area Index
Modis
Ndvi
Phenology
Principal Component Analysis
Remote Sensing
Satellite Data
Seasonality
Spectral Reflectance
Tropical Forest
Videography
Amazonia
Chamaecrista
Erisma
Manilkara Huberi
Nucleopolyhedrovirus
Data do documento: 2017
Revista: ISPRS Journal of Photogrammetry and Remote Sensing
É parte de: Volume 131, Pags. 52-64
Abstract: The association between spectral reflectance and canopy processes remains challenging for quantifying large-scale canopy phenological cycles in tropical forests. In this study, we used a tower-mounted hyperspectral camera in an eastern Amazon forest to assess how canopy spectral signals of three species are linked with phenological processes in the 2012 dry season. We explored different approaches to disentangle the spectral components of canopy phenology processes and analyze their variations over time using 17 images acquired by the camera. The methods included linear spectral mixture analysis (SMA); principal component analysis (PCA); continuum removal (CR); and first-order derivative analysis. In addition, three vegetation indices potentially sensitive to leaf flushing, leaf loss and leaf area index (LAI) were calculated: the Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI) and the entitled Green-Red Normalized Difference (GRND) index. We inspected also the consistency of the camera observations using Moderate Resolution Imaging Spectroradiometer (MODIS) and available phenological data on new leaf production and LAI of young, mature and old leaves simulated by a leaf demography-ontogeny model. The results showed a diversity of phenological responses during the 2012 dry season with related changes in canopy structure and greenness values. Because of the differences in timing and intensity of leaf flushing and leaf shedding, Erisma uncinatum, Manilkara huberi and Chamaecrista xinguensis presented different green vegetation (GV) and non-photosynthetic vegetation (NPV) SMA fractions; distinct PCA scores; changes in depth, width and area of the 681-nm chlorophyll absorption band; and variations over time in the EVI, GRND and NDVI. At the end of dry season, GV increased for Erisma uncinatum, while NPV increased for Chamaecrista xinguensis. For Manilkara huberi, the NPV first increased in the beginning of August and then decreased toward September with new foliage. Variations in red-edge position were not statistically significant between the species and across dates at the 95% confidence level. The camera data were affected by view-illumination effects, which reduced the SMA shade fraction over time. When MODIS data were corrected for these effects using the Multi-Angle Implementation of Atmospheric Correction Algorithm (MAIAC), we observed an EVI increase toward September that closely tracked the modeled LAI of mature leaves (3–5 months). Compared to the EVI, the GRND was a better indicator of leaf flushing because the modeled production of new leaves peaked in August and then declined in September following the GRND closely. While the EVI was more related to changes in mature leaf area, the GRND was more associated with new leaf flushing. © 2017 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS)
DOI: 10.1016/j.isprsjprs.2017.07.006
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