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Remote Sens. 2018, 10(8), 1293; https://doi.org/10.3390/rs10081293

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

1
Department for Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, 07745 Jena, Germany
2
Environmental Protection Agency of Aosta Valley, ARPA Valle d’Aosta, 11020 Aosta, Italy
3
Fundación Centro de Estudios Ambientales del Mediterráneo (CEAM), 46980 Paterna, Spain
4
Department of Environment, National Institute for Agriculture and Food Research and Technology (INIA), 28040 Madrid, Spain
5
Environmental Remote Sensing and Spectroscopy Laboratory (SpecLab), Spanish National Research Council (CSIC), 28037 Madrid, Spain
6
Institute for Dehesa Research, University of Extremadura, 10600 Plasencia, Spain
7
Michael-Stifel-Center Jena for Data-Driven and Simulation Science, 07743 Jena, Germany
8
Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
9
School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, AZ 86011, USA
10
Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ 86011, USA
11
Institute of Ecology and Evolution, Plant Biodiversity Group, Friedrich Schiller University Jena, 07743 Jena, Germany
12
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig, Germany
*
Author to whom correspondence should be addressed.
Received: 16 July 2018 / Revised: 8 August 2018 / Accepted: 13 August 2018 / Published: 15 August 2018
(This article belongs to the Section Land Surface Fluxes)
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Abstract

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 Full-Text
Keywords: phenology; tree–grass ecosystem; Dehesa; PhenoCam; near-infrared-enabled digital repeat photography; phenological transition date (PTD); growing season length (GSL) phenology; tree–grass ecosystem; Dehesa; PhenoCam; near-infrared-enabled digital repeat photography; phenological transition date (PTD); growing season length (GSL)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Luo, Y.; El-Madany, T.S.; Filippa, G.; Ma, X.; Ahrens, B.; Carrara, A.; Gonzalez-Cascon, R.; Cremonese, E.; Galvagno, M.; Hammer, T.W.; Pacheco-Labrador, J.; Martín, M.P.; Moreno, G.; Perez-Priego, O.; Reichstein, M.; Richardson, A.D.; Römermann, C.; Migliavacca, M. Using Near-Infrared-Enabled Digital Repeat Photography to Track Structural and Physiological Phenology in Mediterranean Tree–Grass Ecosystems. Remote Sens. 2018, 10, 1293.

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