Monitoring Forest Phenology and Leaf Area Index with the Autonomous, Low-Cost Transmittance Sensor PASTiS-57

Autor: Nicolas Lauret, Jan G. P. W. Clevers, Jean-Philippe Gastellu-Etchegorry, Frédéric Baret, Martin Herold, Benjamin Brede, Jan Verbesselt
Přispěvatelé: Wageningen University and Research Centre (WUR), Université Fédérale Toulouse Midi-Pyrénées, Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), ESA-ESRIN
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Land surface phenology
Canopy
Land Surface Phenology
Leaf Area Index
ground-based
forest
validation
radiative transfer model
DART model
010504 meteorology & atmospheric sciences
Science
[SDV]Life Sciences [q-bio]
0211 other engineering and technologies
Radiative transfer model
02 engineering and technology
Ground-based
01 natural sciences
Atmospheric radiative transfer codes
Laboratory of Geo-information Science and Remote Sensing
capteur optique
hêtraie
Validation
Forest ecology
Radiative transfer
Laboratorium voor Geo-informatiekunde en Remote Sensing
Forest
Leaf area index
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Remote sensing
écosystème forestier
indice de surface verte
Phenology
Vegetation
15. Life on land
PE&RC
phénologie
indice de surface foliaire
Temporal resolution
modèle de transfert radiatif
[SDE]Environmental Sciences
General Earth and Planetary Sciences
Environmental science
capacité photosynthétique
Zdroj: Remote Sensing 7 (10), . (2018)
Remote Sensing
Remote Sensing, MDPI, 2018, 10 (7), ⟨10.3390/rs10071032⟩
BASE-Bielefeld Academic Search Engine
Remote Sensing 10 (2018) 7
Remote Sensing; Volume 10; Issue 7; Pages: 1032
Remote Sensing, Vol 10, Iss 7, p 1032 (2018)
Remote Sensing, 10(7)
ISSN: 2072-4292
DOI: 10.3390/rs10071032⟩
Popis: International audience; Land Surface Phenology (LSP) and Leaf Area Index (LAI) are important variables that describe the photosynthetically active phase and capacity of vegetation. Both are derived on the global scale from optical satellite sensors and require robust validation based on in situ sensors at high temporal resolution. This study assesses the PAI Autonomous System from Transmittance Sensors at 57 degrees (PASTiS-57) instrument as a low-cost transmittance sensor for simultaneous monitoring of LSP and LAI in forest ecosystems. In a field experiment, spring leaf flush and autumn senescence in a Dutch beech forest were observed with PASTiS-57 and illumination independent, multi-temporal Terrestrial Laser Scanning (TLS) measurements in five plots. Both time series agreed to less than a day in Start Of Season (SOS) and End Of Season (EOS). LAI magnitude was strongly correlated with a Pearson correlation coefficient of 0.98. PASTiS-57 summer and winter LAI were on average 0.41 m(2)m(-2) and 1.43 m(2)m(-2) lower than TLS. This can be explained by previously reported overestimation of TLS. Additionally, PASTiS-57 was implemented in the Discrete Anisotropic Radiative Transfer (DART) Radiative Transfer Model (RTM) model for sensitivity analysis. This confirmed the robustness of the retrieval with respect to non-structural canopy properties and illumination conditions. Generally, PASTiS-57 fulfilled the CEOS LPV requirement of 20% accuracy in LAI for a wide range of biochemical and illumination conditions for turbid medium canopies. However, canopy non-randomness in discrete tree models led to strong biases. Overall, PASTiS-57 demonstrated the potential of autonomous devices for monitoring of phenology and LAI at daily temporal resolution as required for validation of satellite products that can be derived from ESA Copernicus' optical missions, Sentinel-2 and -3.
Databáze: OpenAIRE
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