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

Remote Sensing

卷:10

Mirco Migliavacca¹  TianaW. Hammer¹  TarekS. El-Madany¹  Yunpeng Luo¹  Xuanlong Ma¹  Oscar Perez-Priego¹  Javier Pacheco-Labrador¹  Bernhard Ahrens¹  Markus Reichstein¹  Rosario Gonzalez-Cascon²  AndrewD. Richardson³  Gianluca Filippa⁴  Edoardo Cremonese⁴  Marta Galvagno⁴  M.Pilar Martín⁵  Arnaud Carrara⁶  Gerardo Moreno⁷  Christine Römermann⁸ 

[1] Department for Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, 07745 Jena, Germany;

[2] Department of Environment, National Institute for Agriculture and Food Research and Technology (INIA), 28040 Madrid, Spain;

[3] Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA;

[4] Environmental Protection Agency of Aosta Valley, ARPA Valle d’Aosta, 11020 Aosta, Italy;

[5] Environmental Remote Sensing and Spectroscopy Laboratory (SpecLab), Spanish National Research Council (CSIC), 28037 Madrid, Spain;

[6] Fundación Centro de Estudios Ambientales del Mediterráneo (CEAM), 46980 Paterna, Spain;

[7] Institute for Dehesa Research, University of Extremadura, 10600 Plasencia, Spain;

[8] Institute of Ecology and Evolution, Plant Biodiversity Group, Friedrich Schiller University Jena, 07743 Jena, Germany;

关键词: phenology;    tree–grass ecosystem;    Dehesa;    PhenoCam;    near-infrared-enabled digital repeat photography;    phenological transition date (PTD);    growing season length (GSL);   

DOI  :  10.3390/rs10081293

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown