Exploring continuous time series of vegetation hyperspectral reflectance and solar-induced fluorescence through radiative transfer model inversion

2020 ◽  
Author(s):  
Marco Celesti ◽  
Khelvi Biriukova ◽  
Petya K. E. Campbell ◽  
Ilaria Cesana ◽  
Sergio Cogliati ◽  
...  
Keyword(s):  
Time Series ◽  
Radiative Transfer ◽  
Near Infrared ◽  
Plant Traits ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Optimization Approach ◽  
Ancillary Data ◽  
Full Spectrum ◽  
Retrieval Scheme

<p>Remote sensing of solar-induced chlorophyll fluorescence (SIF) is of growing interest for the scientific community due to the inherent link of SIF with vegetation photosynthetic activity. An increasing number of in situ and airborne fluorescence spectrometers has been deployed worldwide to advance the understanding and usage of SIF for ecosystem studies. Particularly, a number of sites has been instrumented with the FloX (J&B Hyperspectral Devices, Germany), an automated instrument that houses two high resolution spectrometers covering the visible and near infrared spectral regions, one specifically optimized for fluorescence retrieval, the other for plant trait estimation.</p><p>In this contribution we explore the feasibility to consistently retrieve plant traits and SIF from canopy level FloX measurements through the numerical inversion of a light version of the SCOPE model. The optimization approach was specifically adapted to work with the high- frequency time series produced by the FloX. In this context, a strategy for optimal retrieval of plant traits at daily scale is discussed, together with the implementation of an emulator of the radiative transfer model in the retrieval scheme. The retrieval strategy was applied to site measurements across Europe and the US that span a variety of natural and agricultural ecosystems.</p><p>The full spectrum of canopy SIF, the fluorescence quantum efficiency, and main plant traits controlling light absorption and reabsorption were retrieved concurrently and evaluated over the growing season in comparison with site-specific ancillary data. Improvements and challenges of this method compared to other retrievals are discussed, together with the potential of applying a similar retrieval scheme to airborne datasets acquired with e.g. the HyPlant sensor, or the reconfigured “FLEX mode” data acquired with the recently launched Sentinel-3B during its commissioning phase.</p>

scholarly journals Analysis of Sentinel-2 and RapidEye for Retrieval of Leaf Area Index in a Saltmarsh Using a Radiative Transfer Model

2019 ◽  
Vol 11 (6) ◽  
pp. 671 ◽  
Author(s):  
Roshanak Darvishzadeh ◽  
Tiejun Wang ◽  
Andrew Skidmore ◽  
Anton Vrieling ◽  
Brian O’Connor ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Leaf Area Index ◽  
Plant Traits ◽  
Remote Sensing Data ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Area Index ◽  
Field Campaigns ◽  
Sentinel 2

The Sentinel satellite fleet of the Copernicus Programme offers new potential to map and monitor plant traits at fine spatial and temporal resolutions. Among these traits, leaf area index (LAI) is a crucial indicator of vegetation growth and an essential variable in biodiversity studies. Numerous studies have shown that the radiative transfer approach has been a successful method to retrieve LAI from remote-sensing data. However, the suitability and adaptability of this approach largely depend on the type of remote-sensing data, vegetation cover and the ecosystem studied. Saltmarshes are important wetland ecosystems threatened by sea level rise among other human- and animal-induced changes. Therefore, monitoring their vegetation status is crucial for their conservation, yet few LAI assessments exist for these ecosystems. In this study, the retrieval of LAI in a saltmarsh ecosystem is examined using Sentinel-2 and RapidEye data through inversion of the PROSAIL radiative transfer model. Field measurements of LAI and some other plant traits were obtained during two succeeding field campaigns in July 2015 and 2016 on the saltmarsh of Schiermonnikoog, a barrier island of the Netherlands. RapidEye (2015) and Sentinel-2 (2016) data were acquired concurrent to the time of the field campaigns. The broadly employed PROSAIL model was inverted using two look-up tables (LUTs) generated in the spectral band’s settings of the two sensors and in which each contained 500,000 records. Different solutions from the LUTs, as well as, different Sentinel-2 spectral subsets were considered to examine the LAI retrieval. Our results showed that generally the LAI retrieved from Sentinel-2 had higher accuracy compared to RapidEye-retrieved LAI. Utilising the mean of the first 10 best solutions from the LUTs resulted in higher R2 (0.51 and 0.59) and lower normalised root means square error (NRMSE) (0.24 and 0.16) for both RapidEye and Sentinel-2 data respectively. Among different Sentinel-2 spectral subsets, the one comprised of the four near-infrared (NIR) and shortwave infrared (SWIR) spectral bands resulted in higher estimation accuracy (R2 = 0.44, NRMSE = 0.21) in comparison to using other studied spectral subsets. The results demonstrated the feasibility of broadband multispectral sensors, particularly Sentinel-2 for retrieval of LAI in the saltmarsh ecosystem via inversion of PROSAIL. Our results highlight the importance of proper parameterisation of radiative transfer models and capacity of Sentinel-2 spectral range and resolution, with impending high-quality global observation aptitude, for retrieval of plant traits at a global scale.

scholarly journals MAPPING OF FOLIAR CONTENT USING RADIATIVE TRANSFER MODELING AND VIS-NIR HYPERSPECTRAL CLOSE-RANGE REMOTE-SENSING

2015 ◽  
Vol XL-3/W3 ◽  
pp. 467-472 ◽  
Author(s):  
S. Jay ◽  
R. Bendoula ◽  
X. Hadoux ◽  
N. Gorretta
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Spatial Resolution ◽  
Near Infrared ◽  
Hyperspectral Data ◽  
Hyperspectral Images ◽  
Radiative Transfer Model ◽  
Integrating Sphere ◽  
Leaf Angle ◽  
Transfer Model

Most methods for retrieving foliar content from hyperspectral data are well adapted either to remote-sensing scale, for which each spectral measurement has a spatial resolution ranging from a few dozen centimeters to a few hundred meters, or to leaf scale, for which an integrating sphere is required to collect the spectral data. In this study, we present a method for estimating leaf optical properties from hyperspectral images having a spatial resolution of a few millimeters or centimeters. In presence of a single light source assumed to be directional, it is shown that leaf hyperspectral measurements can be related to the directional hemispherical reflectance simulated by the PROSPECT radiative transfer model using two other parameters. The first one is a multiplicative term that is related to local leaf angle and illumination zenith angle. The second parameter is an additive specular-related term that models BRDF effects. <br><br> Our model was tested on visible and near infrared hyperspectral images of leaves of various species, that were acquired under laboratory conditions. Introducing these two additional parameters into the inversion scheme leads to improved estimation results of PROSPECT parameters when compared to original PROSPECT. In particular, the RMSE for local chlorophyll content estimation was reduced by 21% (resp. 32%) when tested on leaves placed in horizontal (resp. sloping) position. Furthermore, inverting this model provides interesting information on local leaf angle, which is a crucial parameter in classical remote-sensing.

scholarly journals Carbon dioxide retrieval of Argus 1000 space data by using GENSPECT line-by-line radiative transfer model

2019 ◽  
Vol 9 (3) ◽  
pp. 77
Author(s):  
R. K. Jagpal ◽  
R. Siddiqui ◽  
S. M. Abrarov ◽  
B. M. Quine
Keyword(s):  
Carbon Dioxide ◽  
Radiative Transfer ◽  
Greenhouse Effect ◽  
Near Infrared ◽  
Trace Gases ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Major Contributor ◽  
Sources And Sinks ◽  
Space Data

The micro-spectrometer Argus 1000 being in space continuously monitors the sources and sinks of the trace gases. It is commonly believed that among other gases CO_2 is the major contributor causing the greenhouse effect. Argus 1000 along its orbit gathers the valuable spectral data that can be analyzed and retrieved. In this paper we present the retrieval of CO_2 gas in the near infrared window 1580 to 1620 nm by using line-by-line code GENSPECT. The retrieved Argus 1000 space data taken over British Columbia on May 31, 2010 indicates an enhancement of CO_2 by about 30%.

scholarly journals Spatial segregation of dust grains in transition disks

2019 ◽  
Vol 624 ◽  
pp. A7 ◽  
Author(s):  
M. Villenave ◽  
M. Benisty ◽  
W. R. F. Dent ◽  
F. Ménard ◽  
A. Garufi ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Near Infrared ◽  
Scattered Light ◽  
Radiative Transfer Model ◽  
Occurrence Rate ◽  
Transfer Model ◽  
Star Forming ◽  
Spatially Resolved ◽  
Wide Range ◽  
Transition Disks

Context. The mechanisms governing the opening of cavities in transition disks are not fully understood. Several processes have been proposed, but their occurrence rate is still unknown. Aims. We present spatially resolved observations of two transition disks, and aim at constraining their vertical and radial structure using multiwavelength observations that probe different regions of the disks and can help understanding the origin of the cavities. Methods. We have obtained near-infrared scattered light observations with VLT/SPHERE of the transition disks 2MASS J16083070-3828268 (J1608) and RXJ1852.3-3700 (J1852), located in the Lupus and Corona Australis star-forming regions respectively. We complement our datasets with archival ALMA observations, and with unresolved photometric observations covering a wide range of wavelengths. We performed radiative transfer modeling to analyze the morphology of the disks, and then compare the results with a sample of 20 other transition disks observed with both SPHERE and ALMA. Results. We detect scattered light in J1608 and J1852 up to a radius of 0.54′′ and 0.4′′ respectively. The image of J1608 reveals a very inclined disk (i ~ 74°), with two bright lobes and a large cavity. We also marginally detect the scattering surface from the rear-facing side of the disk. J1852 shows an inner ring extending beyond the coronagraphic radius up to 15 au, a gap and a second ring at 42 au. Our radiative transfer model of J1608 indicates that the millimeter-sized grains are less extended vertically and radially than the micron-sized grains, indicating advanced settling and radial drift. We find good agreement with the observations of J1852 with a similar model, but due to the low inclination of the system, the model remains partly degenerate. The analysis of 22 transition disks shows that, in general, the cavities observed in scattered light are smaller than the ones detected at millimeter wavelengths. Conclusions. The analysis of a sample of transition disks indicates that the small grains, well coupled to the gas, can flow inward of the region where millimeter grains are trapped. While 15 out of the 22 cavities in our sample could be explained by a planet of less than 13 Jupiter masses, the others either require the presence of a more massive companion or of several low-mass planets.

Characterization of Bias of Advanced Himawari Imager Infrared Observations from NWP Background Simulations Using CRTM and RTTOV

2016 ◽  
Vol 33 (12) ◽  
pp. 2553-2567 ◽  
Author(s):  
X. Zou ◽  
X. Zhuge ◽  
F. Weng
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Land Surface ◽  
Near Infrared ◽  
Weather Prediction ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Brightness Temperatures ◽  
Emissivity Model ◽  
New Generation

AbstractStarting in 2014, the new generation of Japanese geostationary meteorological satellites carries an Advanced Himawari Imager (AHI) to provide the observations of visible, near infrared, and infrared with much improved spatial and temporal resolutions. For applications of the AHI measurements in numerical weather prediction (NWP) data assimilation systems, the biases of the AHI brightness temperatures at channels 7–16 from the model simulations are first characterized and evaluated using both the Community Radiative Transfer Model (CRTM) and the Radiative Transfer for the TIROS Operational Vertical Sounder (RTTOV). It is found that AHI biases under a clear-sky atmosphere are independent of satellite zenith angle except for channel 7. The biases of three water vapor channels increase with scene brightness temperatures and are nearly constant except at high brightness temperatures for the remaining infrared channels. The AHI biases at all the infrared channels are less than 0.6 and 1.2 K over ocean and land, respectively. The differences in biases between RTTOV and CRTM with the land surface emissivity model used in RTTOV are small except for the upper-tropospheric water vapor channels 8 and 9 and the low-tropospheric carbon dioxide channel 16. Since the inputs used for simulations are the same for CRTM and RTTOV, the differential biases at the water vapor channels may be associated with subtle differences in forward models.

Radiative Transfer Modeling for the CLAMS Experiment

2005 ◽  
Vol 62 (4) ◽  
pp. 1053-1071 ◽  
Author(s):  
Zhonghai Jin ◽  
Thomas P. Charlock ◽  
Ken Rutledge ◽  
Glenn Cota ◽  
Ralph Kahn ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Near Infrared ◽  
Radiant Energy ◽  
Energy System ◽  
Temporal Variations ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Near Surface ◽  
Validation Experiment ◽  
Surface Measurements

Abstract Spectral and broadband radiances and irradiances (fluxes) were measured from surface, airborne, and spaceborne platforms in the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) campaign. The radiation data obtained on the 4 clear days over ocean during CLAMS are analyzed here with the Coupled Ocean–Atmosphere Radiative Transfer (COART) model. The model is successively compared with observations of broadband fluxes and albedos near the ocean surface from the Clouds and the Earth's Radiant Energy System (CERES) Ocean Validation Experiment (COVE) sea platform and a low-level OV-10 aircraft, of near-surface spectral albedos from COVE and OV-10, of broadband radiances at multiple angles and inferred top-of-atmosphere (TOA) fluxes from CERES, and of spectral radiances at multiple angles from Airborne Multiangle Imaging Spectroradiometer (MISR), or “AirMISR,” at 20-km altidude. The radiation measurements from different platforms are shown to be consistent with each other and with model results. The discrepancies between the model and observations at the surface are less than 10 W m−2 for downwelling and 2 W m−2 for upwelling fluxes. The model–observation discrepancies for shortwave ocean albedo are less than 8%; some discrepancies in spectral albedo are larger but less than 20%. The discrepancies between low-altitude aircraft and surface measurements are somewhat larger than those between the model and the surface measurements; the former are due to the effects of differences in height, aircraft pitch and roll, and the noise of spatial and temporal variations of atmospheric and oceanic properties. The discrepancy between the model and the CERES observations for the upwelling radiance is 5.9% for all angles; this is reduced to 4.9% if observations within 15° of the sun-glint angle are excluded. The measurements and model agree on the principal impacts that ocean optical properties have on upwelling radiation at low levels in the atmosphere. Wind-driven surface roughness significantly affects the upwelling radiances measured by aircraft and satellites at small sun-glint angles, especially in the near-infrared channel of MISR. Intercomparisons of various measurements and the model show that most of the radiation observations in CLAMS are robust, and that the coupled radiative transfer model used here accurately treats scattering and absorption processes in both the air and the water.

scholarly journals Metamorphism of Arctic marine snow during the melt season. Impact on albedo

2019 ◽  
Author(s):  
Gauthier Verin ◽  
Florent Dominé ◽  
Marcel Babin ◽  
Ghislain Picard ◽  
Laurent Arnaud
Keyword(s):  
Radiative Transfer ◽  
Sea Ice ◽  
Snow Cover ◽  
Near Infrared ◽  
Surface Melting ◽  
Arctic Sea Ice ◽  
Phase Iii ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Snow Layer

Abstract. The energy budget of Arctic sea ice is strongly affected by the snow cover. Intensive sampling of snow properties was conducted near Qikiqtarjuak in Baffin Bay on typical landfast sea ice during two melt seasons in 2015 and 2016. The sampling included stratigraphy, vertical profiles of snow specific surface area (SSA), density and surface spectral albedo. Both seasons feature four main phases: I) dry snow cover, II) surface melting, III) ripe snowpack and IV) melt pond formation. Each of them was characterized by distinctive physical and optical properties. Highest SSA of 49.3 m2 kg−1 was measured during phase I on surface windslab together with a high broadband albedo of 0.87. The next phase was marked by alternative episodes of surface melting which dramatically decreased the SSA below 3 m2 kg−1 and episodes of snowfall reestablishing the pre-melt conditions. Albedo was highly time variable especially in the near-infrared with minimum values around 0.45 at 1000 nm. At some point, the melt progressed leading to a fully ripe snowpack composed of clustered rounded grains in phase III. Albedo began to decrease in the visible as snow thickness decreased but remained steady at longer wavelengths. Moreover, its spatial variability clearly appeared for the first time following snow depth heterogeneity. The impacts on albedo of both snow SSA and thickness were quantitatively investigated using a radiative transfer model. Comparisons between albedo measurements and simulations show that our data on snow physical properties are relevant for radiative transfer modeling. They also point out to the importance of the properties of the very surface snow layer for albedo computation, especially during phase II when several distinctive layers of snow superimposed following snowfalls, melt or diurnal cycles.

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