681 research outputs found
Do we (need to) care about canopy radiation schemes in DGVMs? Caveats and potential impacts
Dynamic global vegetation models (DGVMs) are an essential part of current state-of-the-art Earth system models. In recent years, the complexity of DGVMs has increased by incorporating new important processes like, e.g., nutrient cycling and land cover dynamics, while biogeophysical processes like surface radiation have not been developed much further. Canopy radiation models are however very important for the estimation of absorption and reflected fluxes and are essential for a proper estimation of surface carbon, energy and water fluxes.
The present study provides an overview of current implementations of canopy radiation schemes in a couple of state-of-the-art DGVMs and assesses their accuracy in simulating canopy absorption and reflection for a variety of different surface conditions. Systematic deviations in surface albedo and fractions of absorbed photosynthetic active radiation (faPAR) are identified and potential impacts are assessed.
The results show clear deviations for both, absorbed and reflected, surface solar radiation fluxes. FaPAR is typically underestimated, which results in an underestimation of gross primary productivity (GPP) for the investigated cases. The deviation can be as large as 25% in extreme cases. Deviations in surface albedo range between â0.15 †Îα †0.36, with a slight positive bias on the order of Îα â 0.04. Potential radiative forcing caused by albedo deviations is estimated at â1.25 †RF †â0.8 (W mâ2), caused by neglect of the diurnal cycle of surface albedo.
The present study is the first one that provides an assessment of canopy RT schemes in different currently used DGVMs together with an assessment of the potential impact of the identified deviations. The paper illustrates that there is a general need to improve the canopy radiation schemes in DGVMs and provides different perspectives for their improvement
Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems
The global carbon cycle is an important component of the Earth system and it interacts with the hydrology, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation and systematic and well error-characterised observations relevant to the carbon cycle. Relevant observations for assimilation include various in situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties). We briefly review the different existing data assimilation techniques and contrast them to model benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al.(2005), emphasising the rapid advance in relevant space-based observations
Global Estimation of Biophysical Variables from Google Earth Engine Platform
This paper proposes a processing chain for the derivation of global Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fraction Vegetation Cover (FVC), and Canopy water content (CWC) maps from 15-years of MODIS data exploiting the capabilities of the Google Earth Engine (GEE) cloud platform. The retrieval chain is based on a hybrid method inverting the PROSAIL radiative transfer model (RTM) with Random forests (RF) regression. A major feature of this work is the implementation of a retrieval chain exploiting the GEE capabilities using global and climate data records (CDR) of both MODIS surface reflectance and LAI/FAPAR datasets allowing the global estimation of biophysical variables at unprecedented timeliness. We combine a massive global compilation of leaf trait measurements (TRY), which is the baseline for more realistic leaf parametrization for the considered RTM, with large amounts of remote sensing data ingested by GEE. Moreover, the proposed retrieval chain includes the estimation of both FVC and CWC, which are not operationally produced for the MODIS sensor. The derived global estimates are validated over the BELMANIP2.1 sites network by means of an inter-comparison with the MODIS LAI/FAPAR product available in GEE. Overall, the retrieval chain exhibits great consistency with the reference MODIS product (R2 role= presentation \u3e2 = 0.87, RMSE = 0.54 m2 role= presentation \u3e2/m2 role= presentation \u3e2 and ME = 0.03 m2 role= presentation \u3e2/m2 role= presentation \u3e2 in the case of LAI, and R2 role= presentation \u3e2 = 0.92, RMSE = 0.09 and ME = 0.05 in the case of FAPAR). The analysis of the results by land cover type shows the lowest correlations between our retrievals and the MODIS reference estimates (R2 role= presentation \u3e2 = 0.42 and R2 role= presentation \u3e2 = 0.41 for LAI and FAPAR, respectively) for evergreen broadleaf forests. These discrepancies could be attributed mainly to different product definitions according to the literature. The provided results proof that GEE is a suitable high performance processing tool for global biophysical variable retrieval for a wide range of applications
New Methods for Measurements of Photosynthesis from Space
Our ability to close the Earth's carbon budget and predict feedbacks in a warming climate
depends critically on knowing where, when, and how carbon dioxide (CO2) is exchanged
between the land and atmosphere. In particular, determining the rate of carbon fixation by
the Earth's biosphere (commonly referred to as gross primary productivity, or GPP) and the
dependence of this productivity on climate is a central goal. Historically, GPP has been
inferred from spectral imagery of the land and ocean. Assessment of GPP from the color of
the land and ocean requires, however, additional knowledge of the types of plants in the
scene, their regulatory mechanisms, and climate variables such as soil moistureâjust the
independent variables of interest!
Sunlight absorbed by chlorophyll in photosynthetic organisms is mostly used to drive
photosynthesis, but some can also be dissipated as heat or reâradiated at longer wavelengths
(660â800 nm). This nearâinfrared light reâemitted from illuminated plants is termed solarinduced
fluorescence (SIF), and it has been found to strongly correlate with GPP. To advance
our understanding of SIF and its relation to GPP and environmental stress at the planetary
scale, the Keck Institute for Space Studies (KISS) convened a workshopâheld in Pasadena,
California, in August 2012âto focus on a newly developed capacity to monitor chlorophyll
fluorescence from terrestrial vegetation by satellite. This revolutionary approach for
retrieving global observations of SIF promises to provide direct and spatially resolved
information on GPP, an ideal bottomâup complement to the atmospheric net CO2 exchange
inversions.
Workshop participants leveraged our efforts on previous studies and workshops related to
the European Space Agencyâs FLuorescence EXplorer (FLEX) mission concept, which had
already targeted SIF for a possible satellite mission and had developed a vibrant research
community with many important publications. These studies, mostly focused on landscape,
canopy, and leafâlevel interpretation, provided the groundâwork for the workshop, which
focused on the global carbon cycle and synergies with atmospheric net flux inversions.
Workshop participants included key members of several communities: plant physiologists
with experience using active fluorescence methods to quantify photosynthesis; ecologists
and radiative transfer experts who are studying the challenge of scaling from the leaf to
regional scales; atmospheric scientists with experience retrieving photometric information
from spaceâborne spectrometers; and carbon cycle experts who are integrating new
observations into models that describe the exchange of carbon between the atmosphere,
land and ocean. Together, the participants examined the link between âpassiveâ fluorescence
observed from orbiting spacecraft and the underlying photochemistry, plant physiology and
biogeochemistry of the land and ocean.
This report details the opportunity for forging a deep connection between scientists doing
basic research in photosynthetic mechanisms and the more applied community doing
research on the Earth System. Too often these connections have gotten lost in empiricism
associated with the coarse scale of global models. Chlorophyll fluorescence has been a major
tool for basic research in photosynthesis for nearly a century. SIF observations from space,
although sensing a large footprint, probe molecular events occurring in the leaves below.
This offers an opportunity for direct mechanistic insight that is unparalleled for studies of
biology in the Earth System.
A major focus of the workshop was to review the basic mechanisms that underlie this
phenomenon, and to explore modeling tools that have been developed to link the biophysical
and biochemical knowledge of photosynthesis with the observableâin this case, the
radiance of SIFâseen by the satellite. Discussions led to the identification of areas where
knowledge is still lacking. For example, the inability to do controlled illumination
observations from space limits the ability to fully constrain the variables that link
fluorescence and photosynthesis.
Another focus of the workshop explored a âtopâdownâ view of the SIF signal from space.
Early studies clearly identified a strong correlation between the strength of this signal and
our best estimate of the rate of photosynthesis (GPP) over the globe. New studies show that
this observation provides improvements over conventional reflectanceâbased remote
sensing in detecting seasonal and environmental (particularly drought related) modulation
of photosynthesis. Apparently SIF responds much more quickly and with greater dynamic
range than typical greenness indices when GPP is perturbed. However, discussions at the
workshop also identified areas where topâdown analysis seemed to be âout in frontâ of
mechanistic studies. For example, changes in SIF based on changes in canopy light
interception and the light use efficiency of the canopy, both of which occur in response to
drought, are assumed equivalent in the topâdown analysis, but the mechanistic justification
for this is still lacking from the bottomâup side.
Workshop participants considered implications of these mechanistic and empirical insights
for largeâscale models of the carbon cycle and biogeochemistry, and also made progress
toward incorporating SIF as a simulated output in land surface models used in global and
regionalâscale analysis of the carbon cycle. Comparison of remotely sensed SIF with modelsimulated
SIF may open new possibilities for model evaluation and data assimilation,
perhaps leading to better modeling tools for analysis of the other retrieval from GOSAT
satellite, atmospheric CO2 concentration. Participants also identified another application for
SIF: a linkage to the physical climate system arising from the ability to better identify
regional development of plant water stress. Decreases in transpiration over large areas of a
continent are implicated in the development and âlockingâinâ of drought conditions. These
discussions also identified areas where current land surface models need to be improved in
order to enable this research. Specifically, the radiation transport treatments need dramatic
overhauls to correctly simulate SIF.
Finally, workshop participants explored approaches for retrieval of SIF from satellite and
groundâbased sensors. The difficulty of resolving SIF from the overwhelming flux of reflected
sunlight in the spectral region where fluorescence occurs was once a major impediment to
making this measurement. Placement of very high spectral resolution spectrometers on
GOSAT (and other greenhouse gasâsensing satellites) has enabled retrievals based on infilling
of solar Fraunhofer lines, enabling accurate fluorescence measurements even in the
presence of moderately thick clouds. Perhaps the most interesting challenge here is that
there is no readily portable groundâbased instrumentation that even approaches the
capability of GOSAT and other planned greenhouse gas satellites. This strongly limits scientistsâ ability to conduct groundâbased studies to characterize the footprint of the GOSAT
measurement and to conduct studies of radiation transport needed to interpret SIF
measurement.
The workshop results represent a snapshot of the state of knowledge in this area. New
research activities have sprung from the deliberations during the workshop, with
publications to follow. The introduction of this new measurement technology to a wide slice
of the community of Earth System Scientists will help them understand how this new
technology could help solve problems in their research, address concerns about the
interpretation, identify future research needs, and elicit support of the wider community for
research needed to support this observation.
Somewhat analogous to the original discovery that vegetation indices could be derived from
satellite measurements originally intended to detect clouds, the GOSAT observations are a
rare case in which a (fortuitous) global satellite dataset becomes available before the
research community had a consolidated understanding on how (beyond an empirical
correlation) it could be applied to understanding the underlying processes. Vegetation
indices have since changed the way we see the global biosphere, and the workshop
participants envision that fluorescence can perform the next indispensable step by
complementing these measurements with independent estimates that are more indicative of
actual (as opposed to potential) photosynthesis. Apart from the potential FLEX mission, no
dedicated satellite missions are currently planned. OCOâ2 and â3 will provide much more
data than GOSAT, but will still not allow for regional studies due to the lack of mapping
capabilities. Geostationary observations may even prove most useful, as they could track
fluorescence over the course of the day and clearly identify stressârelated downâregulation of
photosynthesis. Retrieval of fluorescence on the global scale should be recognized as a
valuable tool; it can bring the same quantum leap in our understanding of the global carbon
cycle as vegetation indices once did
Coupling SAR C-band and optical data for soil moisture and leaf area index retrieval over irrigated grasslands
International audienceThe objective of this study was to develop an approach for estimating soil moisture and vegetation parameters in irrigated grasslands by coupling C-band polarimetric Synthetic Aperture Radar (SAR) and optical data. A huge dataset of satellite images acquired from RADARSAT-2 and LANDSAT-7/8, and in situ measurements were used to assess the relevance of several inversion configurations. A neural network (NN) inversion technique was used. The approach for this study was to use RADARSAT-2 and LANDSAT-7/8 images to investigate the potential for the combined use of new data from the new SAR sensor SENTINEL-1 and the new optical sensors LANDSAT-8 and SENTINEL-2. First, the impact of SAR polarization (mono-, dual- and full-polarizations configurations) and the Normalized Difference Vegetation Index (NDVI) calculated from optical data for the estimation error of soil moisture and vegetation parameters was studied. Next, the effect of some polarimetric parameters (Shannon entropy and Pauli components) on the inversion technique was also analyzed. Finally, configurations using in situ measurements of the fraction of absorbed photosynthetically active radiation (FAPAR) and the fraction of green vegetation cover (FCover) were also tested.The results showed that HH polarization is the SAR polarization most relevant to soil moisture estimates. An RMSE for soil moisture estimates of approximately 6 vol.% was obtained even for dense grassland cover. The use of in situ FAPAR and FCover only improved the estimate of the leaf area index (LAI) with an RMSE of approximately 0.37 mÂČ/mÂČ. The use of polarimetric parameters did not improve the estimate of soil moisture and vegetation parameters. Good results were obtained for the biomass (BIO) and vegetation water content (VWC) estimates for BIO and VWC values lower than 2 and 1.5 kg/mÂČ, respectively (RMSE is of 0.38 kg/mÂČ for BIO and 0.32 kg/mÂČ for VWC). In addition, a high under-estimate was observed for BIO and VWC higher than 2 and 1.5 kg/mÂČ, respectively (a bias of -0.65 kg/mÂČ on BIO estimates and -0.49 kg/mÂČ on VWC estimates). Finally, the estimation of vegetation height (VEH) was carried out with an RMSE of 13.45 cm
Remote Sensing of Biophysical Parameters
Vegetation plays an essential role in the study of the environment through plant respiration and photosynthesis. Therefore, the assessment of the current vegetation status is critical to modeling terrestrial ecosystems and energy cycles. Canopy structure (LAI, fCover, plant height, biomass, leaf angle distribution) and biochemical parameters (leaf pigmentation and water content) have been employed to assess vegetation status and its dynamics at scales ranging from kilometric to decametric spatial resolutions thanks to methods based on remote sensing (RS) data.Optical RS retrieval methods are based on the radiative transfer processes of sunlight in vegetation, determining the amount of radiation that is measured by passive sensors in the visible and infrared channels. The increased availability of active RS (radar and LiDAR) data has fostered their use in many applications for the analysis of land surface properties and processes, thanks to their insensitivity to weather conditions and the ability to exploit rich structural and texture information. Optical and radar data fusion and multi-sensor integration approaches are pressing topics, which could fully exploit the information conveyed by both the optical and microwave parts of the electromagnetic spectrum.This Special Issue reprint reviews the state of the art in biophysical parameters retrieval and its usage in a wide variety of applications (e.g., ecology, carbon cycle, agriculture, forestry and food security)
Assessing uncertainties of in situ FAPAR measurements across different forest ecosystems
Carbon balances are important for understanding global climate change. Assessing such balances on a local scale depends on accurate measurements of material flows to calculate the productivity of the ecosystem. The productivity of the Earth's biosphere, in turn, depends on the ability of plants to absorb sunlight and assimilate biomass. Over the past decades, numerous Earth observation missions from satellites have created new opportunities to derive so-called âessential climate variablesâ (ECVs), including important variables of the terrestrial biosphere, that can be used to assess the productivity of our Earth's system. One of these ECVs is the âfraction of absorbed photosynthetically active radiationâ (FAPAR) which is needed to calculate the global carbon balance. FAPAR relates the available photosynthetically active radiation (PAR) in the wavelength range between 400 and 700 nm to the absorption of plants and thus quantifies the status and temporal development of vegetation. In order to ensure accurate datasets of global FAPAR, the UN/WMO institution âGlobal Climate Observing Systemâ (GCOS) declared an accuracy target of 10% (or 0.05) as acceptable for FAPAR products. Since current satellite derived FAPAR products still fail to meet this accuracy target, especially in forest ecosystems, in situ FAPAR measurements are needed to validate FAPAR products and improve them in the future. However, it is known that in situ FAPAR measurements can be affected by significant systematic as well as statistical errors (i.e., âbiasâ) depending on the choice of measurement method and prevailing environmental conditions. So far, uncertainties of in situ FAPAR have been reproduced theoretically in simulations with radiation transfer models (RTMs), but the findings have been validated neither in field experiments nor in different forest ecosystems. However, an uncertainty assessment of FAPAR in field experiments is essential to develop practicable measurement protocols.
This work investigates the accuracy of in situ FAPAR measurements and sources of uncertainties based on multi-year, 10-minute PAR measurements with wireless sensor networks (WSNs) at three sites on three continents to represent different forest ecosystems: a mixed spruce forest at the site âGraswangâ in Southern Germany, a boreal deciduous forest at the site âPeace Riverâ in Northern Alberta, Canada and a tropical dry forest (TDF) at the site âSanta Rosaâ, Costa Rica. The main statements of the research results achieved in this thesis are briefly summarized below:
Uncertainties of instantaneous FAPAR in forest ecosystems can be assessed with Wireless Sensor Networks and additional meteorological and phenological observations. In this thesis, two methods for a FAPAR bias assessment have been developed. First, for assessing the bias of the so-called two-flux FAPAR estimate, the difference between FAPAR acquired under diffuse light conditions and two-flux FAPAR acquired during clear-sky conditions can be investigated. Therefore, measurements of incoming and transmitted PAR are required to calculate the two-flux FAPAR estimate as well as observations of the ratio of diffuse-to-total incident radiation. Second, to assess the bias of not only the two- but also the three-flux FAPAR estimate, four-flux FAPAR observations must be carried out, i.e. measurements of top-of-canopy (TOC) PAR albedo and PAR albedo of the forest background. Then, to quantify the bias of the two and three-flux estimate, the difference with the four-flux estimate can be calculated.
Main sources of uncertainty of in situ FAPAR measurements are high solar zenith angle, occurrence of colored leaves and increased wind speed. At all sites, FAPAR observations exhibited considerable seasonal variability due to the phenological development of the forests (Graswang: 0.89 to 0.99 ±0.02; Peace River: 0.55 to 0.87 ±0.03; Santa Rosa: 0.45 to 0.97 ±0.06). Under certain environmental conditions, FAPAR was affected by systemic errors, i.e. bias that go beyond phenologically explainable fluctuations. The in situ observations confirmed a significant overestimation of FAPAR by up to 0.06 at solar zenith angles above 60° and by up to 0.05 under the occurrence of colored leaves of deciduous trees. The results confirm theoretical findings from radiation transfer simulations, which could now for the first time be quantified under field conditions. As a new finding, the influence of wind speed could be shown, which was particularly evident at the boreal location with a significant bias of FAPAR values at wind speeds above 5 ms-1.
The uncertainties of the two-flux FAPAR estimate are acceptable under typical summer conditions. Three-flux or four-flux FAPAR measurements do not necessarily increase the accuracy of the estimate. The highest average relative bias of different FAPAR estimates were 2.1% in Graswang, 8.4% in Peace River and -4.5% in Santa Rosa. Thus, the GCOS accuracy threshold of 10% set by the GCOS was generally not exceeded. The two-flux FAPAR estimate was only found to be biased during high wind speeds, as changes in the TOC PAR albedo are not considered in two-flux FAPAR measurements. Under typical summer conditions, i.e. low wind speed, small solar zenith angle and green leaves, two-flux FAPAR measurements can be recommended for the validation of satellite-based FAPAR products. Based on the results obtained, it must be emphasized that the three-flux FAPAR estimate, which has often been preferred in previous studies, is not necessarily more accurate, which was particularly evident in the tropical location.
The discrepancies between ground measurements and the current Sentinel-2 FAPAR product still largely exceed the GCOS target accuracy at the respective study sites, even when considering uncertainties of FAPAR ground measurements. It was found that the Sentinel-2 (S2) FAPAR product systematically underestimated the ground observations at all three study sites (i.e. negative values for the mean relative bias in percent). The highest agreement was observed at the boreal site Peace River with a mean relative deviation of -13% (RÂČ=0.67). At Graswang and Santa Rosa, the mean relative deviations were -20% (RÂČ=0.68) and -25% (RÂČ=0.26), respectively. It was argued that these high discrepancies resulted from both the generic nature of the algorithm and the higher ecosystem complexity of the sites Graswang and Santa Rosa. It was also found that the temporal aggregation method of FAPAR ground data should be well considered for comparison with the S2 FAPAR product, which refers to daily averages, as overestimation of FAPAR during high solar zenith angles could distort validation results. However, considering uncertainties of ground measurements, the S2 FAPAR product met the GCOS accuracy requirements only at the boreal study site. Overall, it has been shown that the S2 FAPAR product is already well suited to assess the temporal variability of FAPAR, but due to the low accuracy of the absolute values, the possibilities to feed global production efficiency models and evaluate global carbon balances are currently limited.
The accuracy of satellite derived FAPAR depends on the complexity of the observed forest ecosystem. The highest agreement between satellite derived FAPAR product and ground measurements, both in terms of absolute values and spatial variability, was achieved at the boreal site, where the complexity of the ecosystem is lowest considering forest structure variables and species richness.
These results have been elaborated and presented in three publications that are at the center of this cumulative thesis. In sum, this work closes a knowledge gap by displaying the interplay of different environmental conditions on the accuracy of situ FAPAR measurements. Since the uncertainties of FAPAR are now quantifiable under field conditions, they should also be considered in future validation studies. In this context, the practical recommendations for the implementation of ground observations given in this thesis can be used to prepare sampling protocols, which are urgently needed to validate and improve global satellite derived FAPAR observations in the future.Projektionen zukĂŒnftiger Kohlenstoffbilanzen sind wichtig fĂŒr das VerstĂ€ndnis des globalen Klimawandels und sind auf genaue Messungen von StoffflĂŒssen zur Berechnung der ProduktivitĂ€t des Erdökosystems angewiesen. Die ProduktivitĂ€t der BiosphĂ€re unserer Erde wiederum ist abhĂ€ngig von der Eigenschaft von Pflanzen, Sonnenlicht zu absorbieren und Biomasse zu assimilieren. Ăber die letzten Jahrzehnte haben zahlreiche Erdbeobachtungsmissionen von Satelliten neue Möglichkeiten geschaffen, sogenannte âessentielle Klimavariablenâ (ECVs), darunter auch wichtige Variablen der terrestrischen BiosphĂ€re, aus Satellitendaten abzuleiten, mit deren Hilfe man die ProduktivitĂ€t unseres Erdsystems computergestĂŒtzt berechnen kann. Eine dieser âessenziellen Klimavariablenâ ist der Anteil der absorbierten photosynthetisch aktiven Strahlung (FAPAR) die man zur Berechnung der globalen Kohlenstoffbilanz benötigt. FAPAR bezieht die verfĂŒgbare photosynthetisch aktive Strahlung (PAR) im WellenlĂ€ngenbereich zwischen 400 und 700 nm auf die Absorption von Pflanzen und quantifiziert somit Status und die zeitliche Entwicklung von Vegetation. Um möglichst prĂ€zise Informationen aus dem globalen FAPAR zu gewĂ€hrleisten, erklĂ€rte die UN/WMO-Institution zur globalen Klimabeobachtung, das âGlobal Climate Observing Systemâ (GCOS), ein Genauigkeitsziel von 10% (bzw. 0.05) FAPAR-Produkte als akzeptabel. Da aktuell satellitengestĂŒtzte FAPAR-Produkte dieses Genauigkeitsziel besonders in Waldökosystemen immer noch verfehlen, werden dringen in situ FAPAR-Messungen benötigt, um die FAPAR-Produkte validieren und in Zukunft verbessern zu können. Man weiĂ jedoch, dass je nach Auswahl des Messsystems und vorherrschenden Umweltbedingungen in situ FAPAR-Messungen mit erheblichen sowohl systematischen als auch statistischen Fehlern beeinflusst sein können. Bisher wurden diese Fehler in Simulationen mit Strahlungstransfermodellen zwar theoretisch nachvollzogen, aber die dadurch abgeleiteten Befunde sind bisher weder in Feldversuchen noch in unterschiedlichen Waldökosystemen validiert worden. Eine UnsicherheitsabschĂ€tzung von FAPAR im Feldversuch ist allerdings essenziell, um praxistaugliche Messprotokolle entwickeln zu können.
Die vorliegende Arbeit untersucht die Genauigkeit von in situ FAPAR-Messungen und Ursachen von Unsicherheit basierend auf mehrjĂ€hrigen, 10-minĂŒtigen PAR-Messungen mit drahtlosen Sensornetzwerken (WSNs) an drei verschiedenen Waldstandorten auf drei Kontinenten: der Standort âGraswangâ in SĂŒddeutschland mit einem Fichten-Mischwald, der Standort âPeace Riverâ in Nord-Alberta, Kanada mit einem borealen Laubwald und der Standort âSanta Rosaâ, Costa Rica mit einem tropischen Trockenwald. Die Hauptaussagen der in dieser Arbeit erzielten Forschungsergebnisse werden im Folgenden kurz zusammengefasst:
Unsicherheiten von FAPAR in Waldökosystemen können mit drahtlosen Sensornetzwerken und zusĂ€tzlichen meteorologischen und phĂ€nologischen Beobachtungen quantifiziert werden. In dieser Arbeit wurden zwei Methoden fĂŒr die Bewertung von Unsicherheiten entwickelt. Erstens, um den systematischen Fehler der sogenannten âtwo-fluxâ FAPAR-Messung zu beurteilen, kann die Differenz zwischen FAPAR, das unter diffusen LichtverhĂ€ltnissen aufgenommen wurde, und FAPAR, das unter klaren Himmelsbedingungen aufgenommen wurde, untersucht werden. FĂŒr diese Methode sind Messungen des einfallenden und transmittierten PAR sowie Beobachtungen des VerhĂ€ltnisses von diffuser zur gesamten einfallenden Strahlung erforderlich. Zweitens, um den systematischen Fehler nicht nur der âtwo-fluxâ FAPAR-Messung, sondern auch der âthree-fluxâ FAPAR-Messung zu beurteilen, mĂŒssen âfour-fluxâ FAPAR-Messungen durchgefĂŒhrt werden, d.h. zusĂ€tzlich Messungen der PAR Albedo des BlĂ€tterdachs sowie des Waldbodens. Zur Quantifizierung des Fehlers der âtwo-fluxâ und âthree-fluxâ FAPAR-Messung kann die Differenz zur âfour-fluxâ FAPAR-Messung herangezogen werden.
Die Hauptquellen fĂŒr die Unsicherheit von in situ FAPAR-Messungen sind ein hoher Sonnenzenitwinkel, BlattfĂ€rbung und erhöhte Windgeschwindigkeit. An allen drei Untersuchungsstandorten zeigten die FAPAR-Beobachtungen natĂŒrliche saisonale Schwankungen aufgrund der phĂ€nologischen Entwicklung der WĂ€lder (Graswang: 0,89 bis 0,99 ±0,02; Peace River: 0,55 bis 0,87 ±0,03; Santa Rosa: 0,45 bis 0,97 ±0,06). Unter bestimmten Umweltbedingungen war FAPAR von systematischen Fehlern, d.h. Verzerrungen betroffen, die ĂŒber phĂ€nologisch erklĂ€rbare Schwankungen hinausgehen. So bestĂ€tigten die in situ Beobachtungen eine signifikante ĂberschĂ€tzung von FAPAR um bis zu 0,06 bei Sonnenzenitwinkeln von ĂŒber 60° und um bis zu 0,05 bei Vorkommen gefĂ€rbter BlĂ€tter der LaubbĂ€ume. Die Ergebnisse bestĂ€tigen theoretische Erkenntnisse aus Strahlungstransfersimulationen, die nun erstmalig unter Feldbedingungen quantifiziert werden konnten. Als eine neue Erkenntnis konnte der Einfluss der Windgeschwindigkeit gezeigt werden, der sich besonders am borealen Standort mit einer signifikanten Verzerrung der FAPAR-Werte bei Windgeschwindigkeiten ĂŒber 5 ms-1 Ă€uĂerte.
Die Unsicherheiten der âtwo-fluxâ FAPAR-Messung sind unter typischen Sommerbedingungen akzeptabel. âThree-fluxâ oder âfour-fluxâ FAPAR-Messungen erhöhen nicht unbedingt die Genauigkeit der AbschĂ€tzung. Die höchsten durchschnittlichen relativen systematischen Fehler verschiedener Methoden zur FAPAR-Messung betrugen 2,1% in Graswang, 8,4% in Peace River und -4,5% in Santa Rosa. Damit wurde der durch GCOS festgelegte Genauigkeitsschwellenwert von 10% im Allgemeinen nicht ĂŒberschritten. Die âtwo-fluxâ FAPAR-Messung wurde nur als fehleranfĂ€llig bei hohe Windgeschwindigkeiten befunden, da Ănderungen der PAR-Albedo des BlĂ€tterdachs bei der âtwo-fluxâ FAPAR-Messung nicht berĂŒcksichtigt werden. Unter typischen Sommerbedingungen, also geringe Windgeschwindigkeit, kleiner Sonnenzenitwinkel und grĂŒne BlĂ€tter, kann die âtwo-fluxâ FAPAR-Messung fĂŒr die Validierung von satellitengestĂŒtzten FAPAR-Produkten empfohlen werden. Auf Basis der gewonnenen Ergebnisse muss betont werden, dass die âthree-fluxâ FAPAR-Messung, die in bisherigen Studien hĂ€ufig bevorzugt wurde, nicht unbedingt weniger fehlerbehaftet sind, was sich insbesondere am tropischen Standort zeigte.
Die Abweichungen zwischen Bodenmessungen und dem aktuellen Sentinel-2 FAPAR-Produkt ĂŒberschreiten auch unter BerĂŒcksichtigung von Unsicherheiten in der Messmethodik immer noch weitgehend die GCOS-Zielgenauigkeit an den jeweiligen Untersuchungsstandorten. So zeigte sich, dass das S2 FAPAR-Produkt die Bodenbeobachtungen an allen drei Studienstandorten systematisch unterschĂ€tzte (d.h. negative Werte fĂŒr die mittlere relative Abweichung in Prozent). Die höchste Ăbereinstimmung wurde am borealen Standort Peace River mit einer mittleren relativen Abweichung von -13% (RÂČ=0,67) beobachtet. An den Standorten Graswang und Santa Rosa betrugen die mittleren relativen Abweichungen jeweils -20% (RÂČ=0,68) bzw. -25% (RÂČ=0,26). Es wurde argumentiert, dass diese hohen Abweichungen auf eine Kombination sowohl des generisch ausgerichteten Algorithmus als auch der höheren KomplexitĂ€t beider Ăkosysteme zurĂŒckgefĂŒhrt werden können. Es zeigte sich auĂerdem, dass die zeitlichen Aggregierung der FAPAR-Bodendaten zum Vergleich mit S2 FAPAR-Produkt, das sich auf Tagesmittelwerte bezieht, gut ĂŒberlegt sein sollte, da die ĂberschĂ€tzung von FAPAR wĂ€hrend eines hohen Sonnenzenitwinkels in den Bodendaten die Validierungsergebnisse verzerren kann. Unter BerĂŒcksichtigung der Unsicherheiten der Bodendaten erfĂŒllte das S2 FAPAR Produkt jedoch nur am boreale Untersuchungsstandort die Genauigkeitsanforderungen des GCOS. Insgesamt hat sich gezeigt, dass das S2 FAPAR-Produkt bereits gut zur Beurteilung der zeitlichen VariabilitĂ€t von FAPAR geeignet ist, aber aufgrund der geringen Genauigkeit der absoluten Werte sind die Möglichkeiten, globale Produktionseffizienzmodelle zu speisen und globale Kohlenstoffbilanzen zu bewerten, derzeit begrenzt.
Die Genauigkeit von satellitengestĂŒtzten FAPAR-Produkten ist abhĂ€ngig von der KomplexitĂ€t des beobachteten Waldökosystems. Die höchste Ăbereinstimmung zwischen satellitengestĂŒtztem FAPAR und Bodenmessungen, sowohl hinsichtlich der Darstellung von absolutem Werten als auch der rĂ€umlichen VariabilitĂ€t, wurde am borealen Standort erzielt, fĂŒr den die KomplexitĂ€t des Ăkosystems unter BerĂŒcksichtigung von Waldstrukturvariablen und Artenreichtum am geringsten ausfĂ€llt.
Die dargestellten Ergebnisse wurden in drei Publikationen dieser kumulativen Arbeit erarbeitet. Insgesamt schlieĂt diese Arbeit eine WissenslĂŒcke in der Darstellung des Zusammenspiels verschiedener Umgebungsbedingungen auf die Genauigkeit von situ FAPAR-Messungen. Da die Unsicherheiten von FAPAR nun unter Feldbedingungen quantifizierbar sind, sollten sie in zukĂŒnftigen Validierungsstudien auch berĂŒcksichtigt werden. In diesem Zusammenhang können die in dieser Arbeit genannten praktische Empfehlungen fĂŒr die DurchfĂŒhrung von Bodenbeobachtungen zur Erstellung von Messprotokollen herangezogen werden, die dringend erforderlich sind, um globale satellitengestĂŒtzte FAPAR-Beobachten validieren und zukĂŒnftig verbessern zu können
Assessing uncertainties of in situ FAPAR measurements across different forest ecosystems
Carbon balances are important for understanding global climate change. Assessing such balances on a local scale depends on accurate measurements of material flows to calculate the productivity of the ecosystem. The productivity of the Earth's biosphere, in turn, depends on the ability of plants to absorb sunlight and assimilate biomass. Over the past decades, numerous Earth observation missions from satellites have created new opportunities to derive so-called âessential climate variablesâ (ECVs), including important variables of the terrestrial biosphere, that can be used to assess the productivity of our Earth's system. One of these ECVs is the âfraction of absorbed photosynthetically active radiationâ (FAPAR) which is needed to calculate the global carbon balance. FAPAR relates the available photosynthetically active radiation (PAR) in the wavelength range between 400 and 700 nm to the absorption of plants and thus quantifies the status and temporal development of vegetation. In order to ensure accurate datasets of global FAPAR, the UN/WMO institution âGlobal Climate Observing Systemâ (GCOS) declared an accuracy target of 10% (or 0.05) as acceptable for FAPAR products. Since current satellite derived FAPAR products still fail to meet this accuracy target, especially in forest ecosystems, in situ FAPAR measurements are needed to validate FAPAR products and improve them in the future. However, it is known that in situ FAPAR measurements can be affected by significant systematic as well as statistical errors (i.e., âbiasâ) depending on the choice of measurement method and prevailing environmental conditions. So far, uncertainties of in situ FAPAR have been reproduced theoretically in simulations with radiation transfer models (RTMs), but the findings have been validated neither in field experiments nor in different forest ecosystems. However, an uncertainty assessment of FAPAR in field experiments is essential to develop practicable measurement protocols.
This work investigates the accuracy of in situ FAPAR measurements and sources of uncertainties based on multi-year, 10-minute PAR measurements with wireless sensor networks (WSNs) at three sites on three continents to represent different forest ecosystems: a mixed spruce forest at the site âGraswangâ in Southern Germany, a boreal deciduous forest at the site âPeace Riverâ in Northern Alberta, Canada and a tropical dry forest (TDF) at the site âSanta Rosaâ, Costa Rica. The main statements of the research results achieved in this thesis are briefly summarized below:
Uncertainties of instantaneous FAPAR in forest ecosystems can be assessed with Wireless Sensor Networks and additional meteorological and phenological observations. In this thesis, two methods for a FAPAR bias assessment have been developed. First, for assessing the bias of the so-called two-flux FAPAR estimate, the difference between FAPAR acquired under diffuse light conditions and two-flux FAPAR acquired during clear-sky conditions can be investigated. Therefore, measurements of incoming and transmitted PAR are required to calculate the two-flux FAPAR estimate as well as observations of the ratio of diffuse-to-total incident radiation. Second, to assess the bias of not only the two- but also the three-flux FAPAR estimate, four-flux FAPAR observations must be carried out, i.e. measurements of top-of-canopy (TOC) PAR albedo and PAR albedo of the forest background. Then, to quantify the bias of the two and three-flux estimate, the difference with the four-flux estimate can be calculated.
Main sources of uncertainty of in situ FAPAR measurements are high solar zenith angle, occurrence of colored leaves and increased wind speed. At all sites, FAPAR observations exhibited considerable seasonal variability due to the phenological development of the forests (Graswang: 0.89 to 0.99 ±0.02; Peace River: 0.55 to 0.87 ±0.03; Santa Rosa: 0.45 to 0.97 ±0.06). Under certain environmental conditions, FAPAR was affected by systemic errors, i.e. bias that go beyond phenologically explainable fluctuations. The in situ observations confirmed a significant overestimation of FAPAR by up to 0.06 at solar zenith angles above 60° and by up to 0.05 under the occurrence of colored leaves of deciduous trees. The results confirm theoretical findings from radiation transfer simulations, which could now for the first time be quantified under field conditions. As a new finding, the influence of wind speed could be shown, which was particularly evident at the boreal location with a significant bias of FAPAR values at wind speeds above 5 ms-1.
The uncertainties of the two-flux FAPAR estimate are acceptable under typical summer conditions. Three-flux or four-flux FAPAR measurements do not necessarily increase the accuracy of the estimate. The highest average relative bias of different FAPAR estimates were 2.1% in Graswang, 8.4% in Peace River and -4.5% in Santa Rosa. Thus, the GCOS accuracy threshold of 10% set by the GCOS was generally not exceeded. The two-flux FAPAR estimate was only found to be biased during high wind speeds, as changes in the TOC PAR albedo are not considered in two-flux FAPAR measurements. Under typical summer conditions, i.e. low wind speed, small solar zenith angle and green leaves, two-flux FAPAR measurements can be recommended for the validation of satellite-based FAPAR products. Based on the results obtained, it must be emphasized that the three-flux FAPAR estimate, which has often been preferred in previous studies, is not necessarily more accurate, which was particularly evident in the tropical location.
The discrepancies between ground measurements and the current Sentinel-2 FAPAR product still largely exceed the GCOS target accuracy at the respective study sites, even when considering uncertainties of FAPAR ground measurements. It was found that the Sentinel-2 (S2) FAPAR product systematically underestimated the ground observations at all three study sites (i.e. negative values for the mean relative bias in percent). The highest agreement was observed at the boreal site Peace River with a mean relative deviation of -13% (RÂČ=0.67). At Graswang and Santa Rosa, the mean relative deviations were -20% (RÂČ=0.68) and -25% (RÂČ=0.26), respectively. It was argued that these high discrepancies resulted from both the generic nature of the algorithm and the higher ecosystem complexity of the sites Graswang and Santa Rosa. It was also found that the temporal aggregation method of FAPAR ground data should be well considered for comparison with the S2 FAPAR product, which refers to daily averages, as overestimation of FAPAR during high solar zenith angles could distort validation results. However, considering uncertainties of ground measurements, the S2 FAPAR product met the GCOS accuracy requirements only at the boreal study site. Overall, it has been shown that the S2 FAPAR product is already well suited to assess the temporal variability of FAPAR, but due to the low accuracy of the absolute values, the possibilities to feed global production efficiency models and evaluate global carbon balances are currently limited.
The accuracy of satellite derived FAPAR depends on the complexity of the observed forest ecosystem. The highest agreement between satellite derived FAPAR product and ground measurements, both in terms of absolute values and spatial variability, was achieved at the boreal site, where the complexity of the ecosystem is lowest considering forest structure variables and species richness.
These results have been elaborated and presented in three publications that are at the center of this cumulative thesis. In sum, this work closes a knowledge gap by displaying the interplay of different environmental conditions on the accuracy of situ FAPAR measurements. Since the uncertainties of FAPAR are now quantifiable under field conditions, they should also be considered in future validation studies. In this context, the practical recommendations for the implementation of ground observations given in this thesis can be used to prepare sampling protocols, which are urgently needed to validate and improve global satellite derived FAPAR observations in the future.Projektionen zukĂŒnftiger Kohlenstoffbilanzen sind wichtig fĂŒr das VerstĂ€ndnis des globalen Klimawandels und sind auf genaue Messungen von StoffflĂŒssen zur Berechnung der ProduktivitĂ€t des Erdökosystems angewiesen. Die ProduktivitĂ€t der BiosphĂ€re unserer Erde wiederum ist abhĂ€ngig von der Eigenschaft von Pflanzen, Sonnenlicht zu absorbieren und Biomasse zu assimilieren. Ăber die letzten Jahrzehnte haben zahlreiche Erdbeobachtungsmissionen von Satelliten neue Möglichkeiten geschaffen, sogenannte âessentielle Klimavariablenâ (ECVs), darunter auch wichtige Variablen der terrestrischen BiosphĂ€re, aus Satellitendaten abzuleiten, mit deren Hilfe man die ProduktivitĂ€t unseres Erdsystems computergestĂŒtzt berechnen kann. Eine dieser âessenziellen Klimavariablenâ ist der Anteil der absorbierten photosynthetisch aktiven Strahlung (FAPAR) die man zur Berechnung der globalen Kohlenstoffbilanz benötigt. FAPAR bezieht die verfĂŒgbare photosynthetisch aktive Strahlung (PAR) im WellenlĂ€ngenbereich zwischen 400 und 700 nm auf die Absorption von Pflanzen und quantifiziert somit Status und die zeitliche Entwicklung von Vegetation. Um möglichst prĂ€zise Informationen aus dem globalen FAPAR zu gewĂ€hrleisten, erklĂ€rte die UN/WMO-Institution zur globalen Klimabeobachtung, das âGlobal Climate Observing Systemâ (GCOS), ein Genauigkeitsziel von 10% (bzw. 0.05) FAPAR-Produkte als akzeptabel. Da aktuell satellitengestĂŒtzte FAPAR-Produkte dieses Genauigkeitsziel besonders in Waldökosystemen immer noch verfehlen, werden dringen in situ FAPAR-Messungen benötigt, um die FAPAR-Produkte validieren und in Zukunft verbessern zu können. Man weiĂ jedoch, dass je nach Auswahl des Messsystems und vorherrschenden Umweltbedingungen in situ FAPAR-Messungen mit erheblichen sowohl systematischen als auch statistischen Fehlern beeinflusst sein können. Bisher wurden diese Fehler in Simulationen mit Strahlungstransfermodellen zwar theoretisch nachvollzogen, aber die dadurch abgeleiteten Befunde sind bisher weder in Feldversuchen noch in unterschiedlichen Waldökosystemen validiert worden. Eine UnsicherheitsabschĂ€tzung von FAPAR im Feldversuch ist allerdings essenziell, um praxistaugliche Messprotokolle entwickeln zu können.
Die vorliegende Arbeit untersucht die Genauigkeit von in situ FAPAR-Messungen und Ursachen von Unsicherheit basierend auf mehrjĂ€hrigen, 10-minĂŒtigen PAR-Messungen mit drahtlosen Sensornetzwerken (WSNs) an drei verschiedenen Waldstandorten auf drei Kontinenten: der Standort âGraswangâ in SĂŒddeutschland mit einem Fichten-Mischwald, der Standort âPeace Riverâ in Nord-Alberta, Kanada mit einem borealen Laubwald und der Standort âSanta Rosaâ, Costa Rica mit einem tropischen Trockenwald. Die Hauptaussagen der in dieser Arbeit erzielten Forschungsergebnisse werden im Folgenden kurz zusammengefasst:
Unsicherheiten von FAPAR in Waldökosystemen können mit drahtlosen Sensornetzwerken und zusĂ€tzlichen meteorologischen und phĂ€nologischen Beobachtungen quantifiziert werden. In dieser Arbeit wurden zwei Methoden fĂŒr die Bewertung von Unsicherheiten entwickelt. Erstens, um den systematischen Fehler der sogenannten âtwo-fluxâ FAPAR-Messung zu beurteilen, kann die Differenz zwischen FAPAR, das unter diffusen LichtverhĂ€ltnissen aufgenommen wurde, und FAPAR, das unter klaren Himmelsbedingungen aufgenommen wurde, untersucht werden. FĂŒr diese Methode sind Messungen des einfallenden und transmittierten PAR sowie Beobachtungen des VerhĂ€ltnisses von diffuser zur gesamten einfallenden Strahlung erforderlich. Zweitens, um den systematischen Fehler nicht nur der âtwo-fluxâ FAPAR-Messung, sondern auch der âthree-fluxâ FAPAR-Messung zu beurteilen, mĂŒssen âfour-fluxâ FAPAR-Messungen durchgefĂŒhrt werden, d.h. zusĂ€tzlich Messungen der PAR Albedo des BlĂ€tterdachs sowie des Waldbodens. Zur Quantifizierung des Fehlers der âtwo-fluxâ und âthree-fluxâ FAPAR-Messung kann die Differenz zur âfour-fluxâ FAPAR-Messung herangezogen werden.
Die Hauptquellen fĂŒr die Unsicherheit von in situ FAPAR-Messungen sind ein hoher Sonnenzenitwinkel, BlattfĂ€rbung und erhöhte Windgeschwindigkeit. An allen drei Untersuchungsstandorten zeigten die FAPAR-Beobachtungen natĂŒrliche saisonale Schwankungen aufgrund der phĂ€nologischen Entwicklung der WĂ€lder (Graswang: 0,89 bis 0,99 ±0,02; Peace River: 0,55 bis 0,87 ±0,03; Santa Rosa: 0,45 bis 0,97 ±0,06). Unter bestimmten Umweltbedingungen war FAPAR von systematischen Fehlern, d.h. Verzerrungen betroffen, die ĂŒber phĂ€nologisch erklĂ€rbare Schwankungen hinausgehen. So bestĂ€tigten die in situ Beobachtungen eine signifikante ĂberschĂ€tzung von FAPAR um bis zu 0,06 bei Sonnenzenitwinkeln von ĂŒber 60° und um bis zu 0,05 bei Vorkommen gefĂ€rbter BlĂ€tter der LaubbĂ€ume. Die Ergebnisse bestĂ€tigen theoretische Erkenntnisse aus Strahlungstransfersimulationen, die nun erstmalig unter Feldbedingungen quantifiziert werden konnten. Als eine neue Erkenntnis konnte der Einfluss der Windgeschwindigkeit gezeigt werden, der sich besonders am borealen Standort mit einer signifikanten Verzerrung der FAPAR-Werte bei Windgeschwindigkeiten ĂŒber 5 ms-1 Ă€uĂerte.
Die Unsicherheiten der âtwo-fluxâ FAPAR-Messung sind unter typischen Sommerbedingungen akzeptabel. âThree-fluxâ oder âfour-fluxâ FAPAR-Messungen erhöhen nicht unbedingt die Genauigkeit der AbschĂ€tzung. Die höchsten durchschnittlichen relativen systematischen Fehler verschiedener Methoden zur FAPAR-Messung betrugen 2,1% in Graswang, 8,4% in Peace River und -4,5% in Santa Rosa. Damit wurde der durch GCOS festgelegte Genauigkeitsschwellenwert von 10% im Allgemeinen nicht ĂŒberschritten. Die âtwo-fluxâ FAPAR-Messung wurde nur als fehleranfĂ€llig bei hohe Windgeschwindigkeiten befunden, da Ănderungen der PAR-Albedo des BlĂ€tterdachs bei der âtwo-fluxâ FAPAR-Messung nicht berĂŒcksichtigt werden. Unter typischen Sommerbedingungen, also geringe Windgeschwindigkeit, kleiner Sonnenzenitwinkel und grĂŒne BlĂ€tter, kann die âtwo-fluxâ FAPAR-Messung fĂŒr die Validierung von satellitengestĂŒtzten FAPAR-Produkten empfohlen werden. Auf Basis der gewonnenen Ergebnisse muss betont werden, dass die âthree-fluxâ FAPAR-Messung, die in bisherigen Studien hĂ€ufig bevorzugt wurde, nicht unbedingt weniger fehlerbehaftet sind, was sich insbesondere am tropischen Standort zeigte.
Die Abweichungen zwischen Bodenmessungen und dem aktuellen Sentinel-2 FAPAR-Produkt ĂŒberschreiten auch unter BerĂŒcksichtigung von Unsicherheiten in der Messmethodik immer noch weitgehend die GCOS-Zielgenauigkeit an den jeweiligen Untersuchungsstandorten. So zeigte sich, dass das S2 FAPAR-Produkt die Bodenbeobachtungen an allen drei Studienstandorten systematisch unterschĂ€tzte (d.h. negative Werte fĂŒr die mittlere relative Abweichung in Prozent). Die höchste Ăbereinstimmung wurde am borealen Standort Peace River mit einer mittleren relativen Abweichung von -13% (RÂČ=0,67) beobachtet. An den Standorten Graswang und Santa Rosa betrugen die mittleren relativen Abweichungen jeweils -20% (RÂČ=0,68) bzw. -25% (RÂČ=0,26). Es wurde argumentiert, dass diese hohen Abweichungen auf eine Kombination sowohl des generisch ausgerichteten Algorithmus als auch der höheren KomplexitĂ€t beider Ăkosysteme zurĂŒckgefĂŒhrt werden können. Es zeigte sich auĂerdem, dass die zeitlichen Aggregierung der FAPAR-Bodendaten zum Vergleich mit S2 FAPAR-Produkt, das sich auf Tagesmittelwerte bezieht, gut ĂŒberlegt sein sollte, da die ĂberschĂ€tzung von FAPAR wĂ€hrend eines hohen Sonnenzenitwinkels in den Bodendaten die Validierungsergebnisse verzerren kann. Unter BerĂŒcksichtigung der Unsicherheiten der Bodendaten erfĂŒllte das S2 FAPAR Produkt jedoch nur am boreale Untersuchungsstandort die Genauigkeitsanforderungen des GCOS. Insgesamt hat sich gezeigt, dass das S2 FAPAR-Produkt bereits gut zur Beurteilung der zeitlichen VariabilitĂ€t von FAPAR geeignet ist, aber aufgrund der geringen Genauigkeit der absoluten Werte sind die Möglichkeiten, globale Produktionseffizienzmodelle zu speisen und globale Kohlenstoffbilanzen zu bewerten, derzeit begrenzt.
Die Genauigkeit von satellitengestĂŒtzten FAPAR-Produkten ist abhĂ€ngig von der KomplexitĂ€t des beobachteten Waldökosystems. Die höchste Ăbereinstimmung zwischen satellitengestĂŒtztem FAPAR und Bodenmessungen, sowohl hinsichtlich der Darstellung von absolutem Werten als auch der rĂ€umlichen VariabilitĂ€t, wurde am borealen Standort erzielt, fĂŒr den die KomplexitĂ€t des Ăkosystems unter BerĂŒcksichtigung von Waldstrukturvariablen und Artenreichtum am geringsten ausfĂ€llt.
Die dargestellten Ergebnisse wurden in drei Publikationen dieser kumulativen Arbeit erarbeitet. Insgesamt schlieĂt diese Arbeit eine WissenslĂŒcke in der Darstellung des Zusammenspiels verschiedener Umgebungsbedingungen auf die Genauigkeit von situ FAPAR-Messungen. Da die Unsicherheiten von FAPAR nun unter Feldbedingungen quantifizierbar sind, sollten sie in zukĂŒnftigen Validierungsstudien auch berĂŒcksichtigt werden. In diesem Zusammenhang können die in dieser Arbeit genannten praktische Empfehlungen fĂŒr die DurchfĂŒhrung von Bodenbeobachtungen zur Erstellung von Messprotokollen herangezogen werden, die dringend erforderlich sind, um globale satellitengestĂŒtzte FAPAR-Beobachten validieren und zukĂŒnftig verbessern zu können
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