Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations

de Moura, Yhasmin Mendes; Galvão, Lênio Soares; Hilker, Thomas; Wu, Jin; Saleska, Scott; do Amaral, Cibele Hummel; Nelson, Bruce Walker; Lopes, Aline Pontes; Wiedeman, Kenia K.; Prohaska, Neill; de Oliveira, Raimundo Cosme; Machado, Carolyne Bueno; Aragão, Luiz E. O. C.

doi:10.1016/j.isprsjprs.2017.07.006

Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations

Journal Article · Fri Sep 01 00:00:00 EDT 2017 · ISPRS Journal of Photogrammetry and Remote Sensing

DOI:https://doi.org/10.1016/j.isprsjprs.2017.07.006· OSTI ID:1392262

de Moura, Yhasmin Mendes ^[1]; Galvão, Lênio Soares ^[1]; Hilker, Thomas ^[2]; Wu, Jin ^[3]; Saleska, Scott ^[4]; do Amaral, Cibele Hummel ^[5]; Nelson, Bruce Walker ^[6]; Lopes, Aline Pontes ^[1]; Wiedeman, Kenia K. ^[7]; Prohaska, Neill ^[4]; de Oliveira, Raimundo Cosme ^[8]; Machado, Carolyne Bueno ^[1]; Aragão, Luiz E. O. C. ^[9]

National Inst. for Space Research (INPE), Sao Jose dos Campos (Brazil)
Univ. of Southampton (United Kingdom)
Univ. of Arizona, Tucson, AZ (United States); Brookhaven National Lab. (BNL), Upton, NY (United States)
Univ. of Arizona, Tucson, AZ (United States)
Federal Univ. of Vicosa (UFV) (Brazil)
National Inst. of Amazonian Research (INPA), Manaus (Brazil)
Univ. of Arizona, Tucson, AZ (United States); Harvard Univ., Cambridge, MA (United States)
Brazilian Agricultural Research Corporation (EMBRAPA), Belem (Brazil)
National Inst. for Space Research (INPE), Sao Jose dos Campos (Brazil); Univ. of Exeter (United Kingdom)

The association between spectral reflectance and canopy processes remains challenging for quantifying large-scale canopy phenological cycles in tropical forests. In this paper, 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. Finally, while the EVI was more related to changes in mature leaf area, the GRND was more associated with new leaf flushing.

View Accepted Manuscript (DOE)

Research Organization:: Brookhaven National Lab. (BNL), Upton, NY (United States); National Inst. for Space Research (INPE), Sao Jose dos Campos (Brazil)

Sponsoring Organization:: Foundation for Research Support of the State of Amazonas (FAPEAM) (Brazil); National Council for Scientific and Technological Development (CNPq) (Brazil); Sao Paulo Research Foundation (FAPESP) (Brazil); USDOE; USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)

Grant/Contract Number:: SC0008383; SC0012704

OSTI ID:: 1392262

Alternate ID(s):: OSTI ID: 1549771

Report Number(s):: BNL--114312-2017-JA; YN0100000

Journal Information:: ISPRS Journal of Photogrammetry and Remote Sensing, Journal Name: ISPRS Journal of Photogrammetry and Remote Sensing Vol. 131; ISSN 0924-2716

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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54 ENVIRONMENTAL SCIENCES
59 BASIC BIOLOGICAL SCIENCES
Amazon
dry season
hyperspectral remote sensing
leaf flush
phenology
seasonality
tropical species

Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations

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