Using Near-Infrared-Enabled Digital Repeat Photography to Track Structural and Physiological Phenology in Mediterranean Tree–Grass Ecosystems

Luo, Yunpeng; El-Madany, Tarek S.; Filippa, Gianluca; Ma, Xuanlong; Ahrens, Bernhard; Carrara, Arnaud; Gonzalez-Cascon, Rosario; Cremonese, Edoardo; Galvagno, Marta; Hammer, Tiana W.; Pacheco-Labrador, Javier; Martín, M. Pilar; Moreno, Gerardo; Perez-Priego, Oscar; Reichstein, Markus; Richardson, Andrew D.; Römermann, Christine; Migliavacca, Mirco

doi:10.3390/rs10081293

Using Near-Infrared-Enabled Digital Repeat Photography to Track Structural and Physiological Phenology in Mediterranean Tree–Grass Ecosystems

Journal Article · Wed Aug 15 00:00:00 EDT 2018 · Remote Sensing

DOI:https://doi.org/10.3390/rs10081293· OSTI ID:1499900

Luo, Yunpeng ^[1]; El-Madany, Tarek S. ^[2]; Filippa, Gianluca ^[3]; Ma, Xuanlong ^[2]; Ahrens, Bernhard ^[2]; Carrara, Arnaud ^[4]; Gonzalez-Cascon, Rosario ^[5]; Cremonese, Edoardo ^[3]; Galvagno, Marta ^[3]; Hammer, Tiana W. ^[2]; Pacheco-Labrador, Javier ^[6]; Martín, M. Pilar ^[7]; Moreno, Gerardo ^[8]; Perez-Priego, Oscar ^[2]; Reichstein, Markus ^[9]; Richardson, Andrew D. ^[10]; ^[11]; Migliavacca, Mirco ^[2]

Max-Planck-Inst. for Biogeochemistry, Jena (Germany). Dept. for Biogeochemical Integration; OSTI
Max-Planck-Inst. for Biogeochemistry, Jena (Germany). Dept. for Biogeochemical Integration
Environmental Protection Agency of Aosta Valley, Aosta (Italy)
Fundación Centro de Estudios Ambientales del Mediterráneo (CEAM), Paterna (Spain)
National Inst. for Agriculture and Food Research and Technology (INIA), Madrid (Spain). Dept. of Environment
Max-Planck-Inst. for Biogeochemistry, Jena (Germany). Dept. for Biogeochemical Integration; Spanish National Research Council (CSIC), Madrid (Spain). Environmental Remote Sensing and Spectroscopy Lab. (SpecLab)
Spanish National Research Council (CSIC), Madrid (Spain). Environmental Remote Sensing and Spectroscopy Lab. (SpecLab)
Univ. of Extremadura, Plasencia (Spain). Inst. for Dehesa Research
Max-Planck-Inst. for Biogeochemistry, Jena (Germany). Dept. for Biogeochemical Integration; Michael-Stifel-Center Jena for Data-Driven and Simulation Science, Jena (Germany)
Harvard Univ., Cambridge, MA (United States). Dept. of Organismic and Evolutionary Biology; Northern Arizona Univ., Flagstaff, AZ (United States). School of Informatics, Computing and Cyber Systems; Northern Arizona Univ., Flagstaff, AZ (United States). Center for Ecosystem Science and Society
Friedrich Schiller Univ., Jena (Germany). Inst. of Ecology and Evolution, Plant Biodiversity Group; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig (Germany)

Tree–grass ecosystems are widely distributed. However, their phenology has not yet been fully characterized. The technique of repeated digital photographs for plant phenology monitoring (hereafter referred as PhenoCam) provide opportunities for long-term monitoring of plant phenology, and extracting phenological transition dates (PTDs, e.g., start of the growing season). Here, we aim to evaluate the utility of near-infrared-enabled PhenoCam for monitoring the phenology of structure (i.e., greenness) and physiology (i.e., gross primary productivity—GPP) at four tree–grass Mediterranean sites. We computed four vegetation indexes (VIs) from PhenoCams: (1) green chromatic coordinates (GCC), (2) normalized difference vegetation index (CamNDVI), (3) near-infrared reflectance of vegetation index (CamNIRv), and (4) ratio vegetation index (CamRVI). GPP is derived from eddy covariance flux tower measurement. Then, we extracted PTDs and their uncertainty from different VIs and GPP. The consistency between structural (VIs) and physiological (GPP) phenology was then evaluated. CamNIRv is best at representing the PTDs of GPP during the Green-up period, while CamNDVI is best during the Dry-down period. Moreover, CamNIRv outperforms the other VIs in tracking growing season length of GPP. In summary, the results show it is promising to track structural and physiology phenology of seasonally dry Mediterranean ecosystem using near-infrared-enabled PhenoCam. We suggest using multiple VIs to better represent the variation of GPP.

View Accepted Manuscript (DOE)

Research Organization:: Princeton Univ., NJ (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: SC0016011

OSTI ID:: 1499900

Journal Information:: Remote Sensing, Journal Name: Remote Sensing Journal Issue: 8 Vol. 10; ISSN 2072-4292

Publisher:: MDPICopyright Statement

Country of Publication:: United States

Language:: English

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Tracking seasonal rhythms of plants in diverse ecosystems with digital camera imagery Richardson, Andrew D. New Phytologist, Vol. 222, Issue 4 https://doi.org/10.1111/nph.15591	journal	December 2018
Improving the Performance of 3-D Radiative Transfer Model FLIGHT to Simulate Optical Properties of a Tree-Grass Ecosystem Melendo-Vega, José; Martín, M.; Pacheco-Labrador, Javier Remote Sensing, Vol. 10, Issue 12 https://doi.org/10.3390/rs10122061	journal	December 2018
Correction: Luo, Y.P. et al., Using Near-Infrared Enabled Digital Repeat Photography to Track Structural and Physiological Phenology in Mediterranean Tree-Grass Ecosystems. Remote Sens. 2018, 10, 1293. Luo, Yunpeng; El-Madany, Tarek; Filippa, Gianluca Remote Sensing, Vol. 11, Issue 6 https://doi.org/10.3390/rs11060726	journal	March 2019
Radiometric Calibration of ‘Commercial off the Shelf’ Cameras for UAV-Based High-Resolution Temporal Crop Phenotyping of Reflectance and NDVI Holman, Fenner H.; Riche, Andrew B.; Castle, March Remote Sensing, Vol. 11, Issue 14 https://doi.org/10.3390/rs11141657	journal	July 2019
N : P stoichiometry and habitat effects on Mediterranean savanna seasonal root dynamics Nair, Richard K. F.; Morris, Kendalynn A.; Hertel, Martin Biogeosciences, Vol. 16, Issue 9 https://doi.org/10.5194/bg-16-1883-2019	journal	January 2019

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Using Near-Infrared-Enabled Digital Repeat Photography to Track Structural and Physiological Phenology in Mediterranean Tree–Grass Ecosystems

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