631 research outputs found

    Estimation of Incident Photosynthetically Active Radiation From Moderate Resolution Imaging Spectrometer Data

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    Incident photosynthetically active radiation (PAR) is a key variable needed by almost all terrestrial ecosystem models. Unfortunately, the current incident PAR products estimated from remotely sensed data at spatial and temporal resolutions are not sufficient for carbon cycle modeling and various applications. In this study, the authors develop a new method based on the look-up table approach for estimating instantaneous incident PAR from the polar-orbiting Moderate Resolution Imaging Spectrometer (MODIS) data. Since the top-of-atmosphere (TOA) radiance depends on both surface reflectance and atmospheric properties that largely determine the incident PAR, our first step is to estimate surface reflectance. The approach assumes known aerosol properties for the observations with minimum blue reflectance from a temporal window of each pixel. Their inverted surface reflectance is then interpolated to determine the surface reflectance of other observations. The second step is to calculate PAR by matching the computed TOA reflectance from the look-up table with the TOA values of the satellite observations. Both the direct and diffuse PAR components, as well as the total shortwave radiation, are determined in exactly the same fashion. The calculation of a daily average PAR value from one or two instantaneous PAR values is also explored. Ground measurements from seven FLUXNET sites are used for validating the algorithm. The results indicate that this approach can produce reasonable PAR product at 1 km resolution and is suitable for global applications, although more quantitative validation activities are still needed

    Boreaalisen metsän lehtialaindeksin ja sen sitoman fotosynteettisesti aktiivisen säteilyn arviointi

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    The aim of this dissertation is to assess the accuracy of different ground reference methods used to validate satellite based leaf area index (LAI) and the fraction of absorbed photosynthetically active radiation (fPAR) products. LAI and fPAR are strongly linked, although they principally and practically measure different properties: LAI quantifies the areal interphase between soil and atmosphere, whereas fPAR quantifies the energy available for photosynthesis. Until now, the development of remote sensing based methods to estimate LAI and fPAR in a boreal forest has been hindered by the scarcity of ground data, which is required to validate and develop existing algorithms. The aim of the first part of this dissertation was to assess the impacts of different methodological approaches to estimate LAI in boreal forests, and to validate satellite based LAI products. Results showed that the accuracy of ground based LAI estimates is sensitive to both the retrieval methods and sampling scheme used to collect the optical LAI data. The satellite based measurements of LAI demonstrated a large temporal variability in LAI. The second part of the dissertation focused on measuring and modeling fPAR in a boreal forest. A new scheme for measuring and modeling ground reference fPAR based on photon recollision probability was presented in this dissertation. Ground reference fPAR is usually estimated only for the forest canopy layer. This study is among the first ones to validate the new global satellite based fPAR product called GEOV1 using data of both the forest canopy and understory layers from boreal forests. Results showed that satellite based fPAR products may correspond better with the total fPAR, instead of only the forest canopy fPAR as has often been presumed.Tämän väitöskirjan tarkoituksena oli kehittää LAI:n ja fPAR:in maastomittausmenetelmiä ja arvioida nykyisten satelliittipohjaisten LAI- ja fPAR-tuotteiden toimivuutta boreaalisissa metsissä. Lehtialaindeksi (leaf area index, LAI) kuvaa lehtien toispuolista pinta-alaa maapinta-alaa kohden (m2/m2). Akronyymi fPAR on lyhennelmä sanoista fraction of absorbed photosynthetically active radiation (PAR) ja se kuvaa kasvillisuuden kykyä sitoa auringosta saapuvaa säteilyä. fPAR määräytyy LAI:n ja auringon kulman perusteella. LAI:ta ja fPAR:ia voidaan arvioida avaruudesta tehtävällä kaukokartoituksella ja mielenkiinnon kohteena voi olla esimerkiksi globaali ympäristön seuranta. Tällä hetkellä kaukokartoitusmenetelmien kehittymistä hidastaa maastoaineistojen puute, sillä maastoaineistot ovat välttämättömiä mallien tarkkuuden arvioinnissa. Koska LAI on yksi tärkeimpiä fPAR:iin vaikuttavia muuttujia, väitöskirjan ensimmäinen osio keskittyi LAI:n maastomittausmenetelmien tarkkuuden arviointiin. Ensimmäisen osan tarkoituksena oli selvittää, kuinka erilaiset LAI:n arviointitavat ja otanta-asetelmat toimivat boreaalisissa metsissä. Satelliitista mitattujen LAI-arvojen kelpoisuutta arvioitiin vertaamalla niitä maastossa mitattuihin arvoihin. Tulosten mukaan erilaiset LAI:n arviointitavat tuottavat systemaattisesti poikkeavia arvioita ja arvioiden tarkkuus riippuu paitsi käytetystä menetelmästä, myös maastomittausten otanta-asetelmasta. Tutkimuksessa havaittiin, että satelliitista mitattuihin LAI-arvoihin sisältyy paljon ajallista ja paikallista vaihtelua, joka johtuu osin satelliitin mittaaman signaalin saturoitumisesta. Väitöskirjan toinen osa keskittyi fPAR:in mittaamiseen ja mallintamiseen. Tutkimuksen aluksi esiteltiin uusi fPAR-malli, joka soveltuu laajojen alueiden fPAR-arviointiin. Mallin toimivuutta arvioitiin vertaamalla mitattuja ja mallinnettuja fPAR-arvoja toisiinsa. fPAR-mallin todettiin toimivan hyvin. Tämän jälkeen tutkittiin, kuinka hyvin nykyiset satelliittimittauksiin perustuvat fPAR-tuotteet vastaavat maastomittauksiin perustuvaa fPARia. Yleensä satelliittituotteiden toimivuutta arvioitaessa on keskitytty vain metsän latvuskerroksen sitoman säteilymäärän arviointiin, mutta tässä tutkimuksessa huomioitiin myös aluskasvillisuuden sitoma säteily. Tulokset osoittivat, että satelliittimittauksiin perustuva fPAR voi vastata paremmin metsikön latvuksen ja aluskasvillisuuden yhteenlaskettua fPAR:ia kuin pelkän latvuskerroksen fPAR:ia

    How does the global Moderate Resolution Imaging Spectroradiometer (MODIS) Fraction of Photosynthetically Active Radiation (FPAR) product relate to regionally developed land cover and vegetation products in a semi-arid Australian savanna?

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    Spatio-temporally variable information on total vegetation cover is highly relevant to water quality and land management in river catchments adjacent to the Great Barrier Reef, Australia. A time series of the global Moderate Resolution Imaging Spectroradiometer (MODIS) Fraction of Photosynthetically Active Radiation (FPAR; 2000-2006) and its underlying biome classification (MOD12Q1) were compared to national land cover and regional, remotely sensed products in the dry-tropical Burdekin River. The MOD12Q1 showed reasonable agreement with a classification of major vegetation groups for 94% of the study area. We then compared dry-seasonal, quality controlled MODIS FPAR observations to (i) Landsat-based woody foliage projective cover (wFPC) (2004) and (ii) MODIS bare ground index (BGI) observations (2001-2003). Statistical analysis of the MODIS FPAR revealed a significant sensitivity to Landsat wFPC-based Vegetation Structural Categories (VSC) and VSC-specific temporal variability over the 2004 dry season. The MODIS FPAR relation to 20 coinciding MODIS BGI dry-seasonal observations was significant (ρ < 0.001) for homogeneous areas of low wFPC. Our results show that the global MODIS FPAR can be used to identify VSC, represent VSC-specific variability of PAR absorption, and indicate that the amount, structure, and optical properties of green and non-green vegetation components contribute to the MODIS FPAR signal

    Higher absorbed solar radiation partly offset the negative effects of water stress on the photosynthesis of Amazon forests during the 2015 drought

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    Amazon forests play an important role in the global carbon cycle and Earth\u27s climate. The vulnerability of Amazon forests to drought remains highly controversial. Here we examine the impacts of the 2015 drought on the photosynthesis of Amazon forests to understand how solar radiation and precipitation jointly control forest photosynthesis during the severe drought. We use a variety of gridded vegetation and climate datasets, including solar-induced chlorophyll fluorescence (SIF), photosynthetic active radiation (PAR), the fraction of absorbed PAR (APAR), leaf area index (LAI), precipitation, soil moisture, cloud cover, and vapor pressure deficit (VPD) in our analysis. Satellite-derived SIF observations provide a direct diagnosis of plant photosynthesis from space. The decomposition of SIF to SIF yield (SIFyield) and APAR (the product of PAR and fPAR) reveals the relative effects of precipitation and solar radiation on photosynthesis. We found that the drought significantly reduced SIFyield, the emitted SIF per photon absorbed. The higher APAR resulting from lower cloud cover and higher LAI partly offset the negative effects of water stress on the photosynthesis of Amazon forests, leading to a smaller reduction in SIF than in SIFyield and precipitation. We further found that SIFyield anomalies were more sensitive to precipitation and VPD anomalies in the southern regions of the Amazon than in the central and northern regions. Our findings shed light on the relative and combined effects of precipitation and solar radiation on photosynthesis, and can improve our understanding of the responses of Amazon forests to drought

    Radiative transfer modelling reveals why canopy reflectance follows function

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    Optical remote sensing is potentially highly informative to track Earth’s plant functional diversity. Yet, causal explanations of how and why plant functioning is expressed in canopy reflectance remain limited. Variation in canopy reflectance can be described by radiative transfer models (here PROSAIL) that incorporate plant traits affecting light transmission in canopies. To establish causal links between canopy reflectance and plant functioning, we investigate how two plant functional schemes, i.e. the Leaf Economic Spectrum (LES) and CSR plant strategies, are related to traits with relevance to reflectance. These traits indeed related to both functional schemes, whereas only traits describing leaf properties correlated with the LES. In contrast, traits related to canopy structure showed no correlation to the LES, but to CSR strategies, as the latter integrates both plant economics and size traits, rather than solely leaf economics. Multiple optically relevant traits featured comparable or higher correspondence to the CSR space than those traits originally used to allocate CSR scores. This evidences that plant functions and strategies are directly expressed in reflectance and entails that canopy ‘reflectance follows function’. This opens up new possibilities to understand differences in plant functioning and to harness optical remote sensing data for monitoring Earth´s functional diversity

    On the growth performance of two competing species in an Andean pasture of southern Ecuador - monitoring and simulations

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    The megadiverse tropical mountain forests in the southeastern Andes of Ecuador, including their biodiversity and ecosystem services, are severely threatened due to climate warming and the clearing of forests to produce pasture land. The common local practice of recurrent burning for pasture rejuvenation has proven to be non-sustainable, since it enables bracken fern to invade pastures, causing farmers to abandon heavily infested pastures and instead clear new tracts of natural forest. No quantitative information on the growth potential of pasture grass and bracken fern under current and future environmental conditions has yet been available for the Andes of Ecuador. The scientific basis required to understand bracken invasion has yet to be established. This scientific basis would enable the development of sustainable pasture management strategies. Such strategies would, in turn, help protect the remnants of natural forest. Consequently, the present work aims at investigating the growth potential of two competing species under current and future climate conditions. Outcomes provide new knowledge and methodological developments concerning pasture invasion by bracken fern in southern Ecuador. The method entails the development of a new model, the Southern Bracken Competition Model (SoBraCoMo), realistically parameterized and validated. The model code is based on existing Soil Vegetation Atmosphere Transfer (SVAT) and vegetation dynamic models to calculate the potential growth of two main competitors, the southern bracken fern (Pteridium arachnoideum) and the pasture grass (Setaria sphacelata). Extensive field measurements and proper meteorological forcing delivered new site and species-specific parameters for realistic productivity simulations of both species. An experimental site was established to observe pasture and bracken fern development under the practice of recurrent burning, and to provide atmospheric data for a realistic forcing of the developed model. A novel balloon-borne monitoring system was developed to detect species cover and provided new insights into post-fire canopy recovery. The main results demonstrate that, under current environmental conditions, Setaria has a slightly higher competitive growth potential under undisturbed conditions (no grazing, trampling, or light competition). Furthermore, this growth advantage of Setaria should most likely increase due to global warming. Because field observations show bracken infestation, however, other factors than those investigated should be responsible for the bracken fern’s current success. The most likely cause of bracken success to be investigated in the future is cattle browsing; although browsing continuously removes aboveground biomass, this disruption of the upper soil does not affect deep roots and rhizomes of bracken plants. The newly developed SoBraCoMo can now provide an excellent basis to implement new mechanisms like browsing for future simulations

    Extracting ecological and biophysical information from AVHRR optical data: An integrated algorithm based on inverse modeling

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    Satellite remote sensing provides the only means of directly observing the entire surface of the Earth at regular spatial and temporal intervals

    Extracting ecological and biophysical information from AVHRR optical data: An integrated algorithm based on inverse modeling

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    Satellite remote sensing provides the only means of directly observing the entire surface of the Earth at regular spatial and temporal intervals

    Integration of remotely sensed data with stand-scale vegetation models

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