scholarly journals Spectral Invariant Provides a Practical Modeling Approach for Future Biophysical Variable Estimations

2018 ◽  
Vol 10 (10) ◽  
pp. 1508 ◽  
Author(s):  
Yelu Zeng ◽  
Baodong Xu ◽  
Gaofei Yin ◽  
Shengbiao Wu ◽  
Guoqing Hu ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Hot Spot ◽  
Canopy Structure ◽  
Radiative Transfer Model ◽  
Leaf Angle ◽  
Transfer Model ◽  
Angle Distribution ◽  
Bidirectional Reflectance Factor ◽  
Spectral Invariant

This paper presents a simple radiative transfer model based on spectral invariant properties (SIP). The canopy structure parameters, including the leaf angle distribution and multi-angular clumping index, are explicitly described in the SIP model. The SIP model has been evaluated on its bidirectional reflectance factor (BRF) in the angular space at the radiation transfer model intercomparison platform, and in the spectrum space by the PROSPECT+SAIL (PROSAIL) model. The simulations of BRF by SIP agreed well with the reference values in both the angular space and spectrum space, with a root-mean-square-error (RMSE) of 0.006. When compared with the widely-used Soil-Canopy Observation of Photochemistry and Energy fluxes (SCOPE) model on fPAR, the RMSE was 0.006 and the R2 was 0.99, which shows a high accuracy. This study also suggests the newly proposed vegetation index, the near-infrared (NIR) reflectance of vegetation (NIRv), was a good linear approximation of the canopy structure parameter, the directional area scattering factor (DASF), with an R2 of 0.99. NIRv was not influenced much by the soil background contribution, but was sensitive to the leaf inclination angle. The sensitivity of NIRv to canopy structure and the robustness of NIRv to the soil background suggest NIRv is a promising index in future biophysical variable estimations with the support of the SIP model, especially for the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) observations near the hot spot directions.

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 Multispectral Pansharpening with Radiative Transfer-Based Detail-Injection Modeling for Preserving Changes in Vegetation Cover

2018 ◽  
Vol 10 (8) ◽  
pp. 1308 ◽  
Author(s):  
Andrea Garzelli ◽  
Bruno Aiazzi ◽  
Luciano Alparone ◽  
Simone Lolli ◽  
Gemine Vivone
Keyword(s):  
Radiative Transfer ◽  
Vegetation Index ◽  
Near Infrared ◽  
Agricultural Landscape ◽  
Resolution Enhancement ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Injection Model ◽  
Phenological Changes ◽  
Imaging Instrument

Whenever vegetated areas are monitored over time, phenological changes in land cover should be decoupled from changes in acquisition conditions, like atmospheric components, Sun and satellite heights and imaging instrument. This especially holds when the multispectral (MS) bands are sharpened for spatial resolution enhancement by means of a panchromatic (Pan) image of higher resolution, a process referred to as pansharpening. In this paper, we provide evidence that pansharpening of visible/near-infrared (VNIR) bands takes advantage of a correction of the path radiance term introduced by the atmosphere, during the fusion process. This holds whenever the fusion mechanism emulates the radiative transfer model ruling the acquisition of the Earth’s surface from space, that is for methods exploiting a multiplicative, or contrast-based, injection model of spatial details extracted from the panchromatic (Pan) image into the interpolated multispectral (MS) bands. The path radiance should be estimated and subtracted from each band before the product by Pan is accomplished. Both empirical and model-based estimation techniques of MS path radiances are compared within the framework of optimized algorithms. Simulations carried out on two GeoEye-1 observations of the same agricultural landscape on different dates highlight that the de-hazing of MS before fusion is beneficial to an accurate detection of seasonal changes in the scene, as measured by the normalized differential vegetation index (NDVI).

scholarly journals Multispectral Pansharpening with Radiative Transfer-Based Detail-Injection Modeling for Preserving Changes in Vegetation Cover

2018 ◽  
Author(s):  
Andrea Garzelli ◽  
Bruno Aiazzi ◽  
Luciano Alparone ◽  
Simone Lolli ◽  
Gemine Vivone
Keyword(s):  
Radiative Transfer ◽  
Vegetation Index ◽  
Near Infrared ◽  
Agricultural Landscape ◽  
Resolution Enhancement ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Injection Model ◽  
Phenological Changes ◽  
Imaging Instrument

Whenever vegetated areas are monitored over time, phenological changes in land cover should be decoupled from changes in acquisition conditions, like atmospheric components, sun and satellite heights, and imaging instrument. This especially holds when the multispectral (MS) bands are sharpened for spatial resolution enhancement by means of a panchromatic (Pan) image of higher resolution, a process referred to as pansharpening. In this paper, we provide evidence that pansharpening of visible/near-infrared (VNIR) bands takes advantage from a correction of the path radiance term introduced by the atmosphere, during the fusion process. This holds whenever the fusion mechanism emulates the radiative transfer model ruling the acquisition of the Earth&rsquo;s surface from space, that is, for methods exploiting a multiplicative, or contrast-based, injection model of spatial details extracted from the panchromatic (Pan) image into the interpolated multispectral (MS) bands. The path radiance should be estimated and subtracted from each band before the product by Pan is accomplished. Both empirical and model-based estimation techniques of MS path radiances are compared within the framework of optimized algorithms. Simulations carried out on two GeoEye-1 observations of the same agricultural landscape at different dates highlight that the de-hazing of MS before fusion is beneficial for an accurate detection of seasonal changes in the scene, as measured by the normalized differential vegetation index (NDVI).

scholarly journals How does leaf functional diversity affect the light environment in forest canopies? An in-silico biodiversity experiment

2021 ◽  
Author(s):  
Elena Plekhanova ◽  
Pascal A. Niklaus ◽  
Jean-Philippe Gastellu-Etchegorry ◽  
Gabriela Schaepman-Strub
Keyword(s):  
Functional Diversity ◽  
In Silico ◽  
Species Interactions ◽  
Shortwave Radiation ◽  
Ecosystem Functions ◽  
Radiative Transfer Model ◽  
Leaf Angle ◽  
Transfer Model ◽  
Angle Distribution ◽  
Area Index

&lt;p&gt;&lt;span&gt;Global change is affecting biodiversity, with consequences on carbon, water, and energy fluxes between the atmosphere, vegetation, and soil. The interaction of shortwave radiation with vegetation drives basic processes of the biosphere, such as primary productivity or species interactions through light competition. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;In our study, we aim to understand the effects of biodiversity on canopy light absorption. We focus on the diversity of three key functional traits that influence the light-canopy interaction: leaf area index, leaf angle distribution and leaf optical properties. Our study is based on the in-silico combination of process-based modelling of radiation (3D radiative transfer model DART) with the well-established design of biodiversity experiments. We used this novel method to study the effects of leaf functional diversity on a light proxy for productivity (the fraction of absorbed photosynthetically active radiation (FAPAR)) and net radiation (shortwave albedo). We found that diverse canopies had lower albedo and higher FAPAR than the average of the corresponding monoculture values. In mixtures, FAPAR was unequally re-distributed between trees with distinct leaf traits and the net biodiversity effect on absorptance was greater when combining plant functional types with more distinct traits. Our results support the mechanistic understanding of overyielding effects in functionally diverse canopies and may partially explain some of the growth-promoting mechanisms in biodiversity-ecosystem functioning experiments. They can further help to account for biodiversity effects in dynamic vegetation and climate models.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;We would like to present this study in the BG3.22 session, because it 1) contributes to the understanding of fundamental ecosystem functions related to light interaction 2) describes a novel in-silico combination of process-based modelling of radiation with the well-established design of biodiversity experiments.&lt;/span&gt;&lt;/p&gt;

scholarly journals Mineralogical and chemical properties inversed from 21-lunar-day VNIS observations taken during the Chang’E-4 mission

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qinghong Zeng ◽  
Shengbo Chen ◽  
Yuanzhi Zhang ◽  
Yongling Mu ◽  
Rui Dai ◽  
...  
Keyword(s):  
Impact Crater ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Chemical Properties ◽  
Landing Site ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Chemical Compositions ◽  
Impact Melt ◽  
And Chemical Properties

AbstractWe report on the mineralogical and chemical properties of materials investigated by the lunar rover Yutu-2, which landed on the Von Kármán crater in the pre-Nectarian South Pole–Aitken (SPA) basin. Yutu-2 carried several scientific payloads, including the Visible and Near-infrared Imaging Spectrometer (VNIS), which is used for mineral identification, offering insights into lunar evolution. We used 86 valid VNIS data for 21 lunar days, with mineral abundance obtained using the Hapke radiative transfer model and sparse unmixing algorithm and chemical compositions empirically estimated. The mineralogical properties of the materials at the Chang’E-4 (CE-4) site referred to as norite/gabbro, based on findings of mineral abundance, indicate that they may be SPA impact melt components excavated by a surrounding impact crater. We find that CE-4 materials are dominated by plagioclase and pyroxene and feature little olivine, with 50 of 86 observations showing higher LCP than HCP in pyroxene. In view of the effects of space weathering, olivine content may be underestimated, with FeO and TiO2 content estimated using the maturity-corrected method. Estimates of chemical content are 7.42–18.82 wt% FeO and 1.48–2.1 wt% TiO2, with a low-medium Mg number (Mg # ~ 55). Olivine-rich materials are not present at the CE-4 landing site, based on the low-medium Mg #. Multi-origin materials at the CE-4 landing site were analyzed with regard to concentrations of FeO and TiO2 content, supporting our conclusion that the materials at CE-4 do not have a single source but rather are likely a mixture of SPA impact melt components excavated by surrounding impact crater and volcanic product ejecta.

scholarly journals Error simulations of uncorrected NDVI and DCVI during remote sensing measurements from UAS

2014 ◽  
Vol 18 (2) ◽  
pp. 35-45 ◽  
Author(s):  
Michał T. Chiliński ◽  
Marek Ostrowski
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Vegetation Index ◽  
Vegetation Mapping ◽  
Radiative Transfer Model ◽  
Unmanned Aerial Systems ◽  
Transfer Model ◽  
Digital Cameras ◽  
Aerial Systems

Abstract Remote sensing from unmanned aerial systems (UAS) has been gaining popularity in the last few years. In the field of vegetation mapping, digital cameras converted to calculate vegetation index (DCVI) are one of the most popular sensors. This paper presents simulations using a radiative transfer model (libRadtran) of DCVI and NDVI results in an environment of possible UAS flight scenarios. The analysis of the results is focused on the comparison of atmosphere influence on both indices. The results revealed uncertainties in uncorrected DCVI measurements up to 25% at the altitude of 5 km, 5% at 1 km and around 1% at 0.15 km, which suggests that DCVI can be widely used on small UAS operating below 0.2 km.

scholarly journals Summertime canopy albedo is sensitive to forest thinning

2013 ◽  
Vol 10 (9) ◽  
pp. 15373-15414 ◽  
Author(s):  
J. Otto ◽  
D. Berveiller ◽  
F.-M. Bréon ◽  
N. Delpierre ◽  
G. Geppert ◽  
...  
Keyword(s):  
Forest Management ◽  
Tree Species ◽  
Structural Changes ◽  
Near Infrared ◽  
Canopy Structure ◽  
Model Parameters ◽  
Transfer Model ◽  
Forest Thinning ◽  
Crown Volume ◽  
The Difference

Abstract. Despite an emerging body of literature linking canopy albedo to forest management, understanding of the process is still fragmented. We combined a stand-level forest gap model with a canopy radiation transfer model and satellite-derived model parameters to quantify the effects of forest thinning, that is removing trees at a certain time during the forest rotation, on summertime canopy albedo. The effects of different forest species (pine, beech, oak) and four thinning strategies (light to intense thinning regimes) were examined. During stand establishment, summertime canopy albedo is driven by tree species. In the later stages of stand development, the effect of tree species on summertime canopy albedo decreases in favour of an increasing influence of forest thinning on summertime canopy albedo. These trends continue until the end of the rotation where thinning explains up to 50% of the variance in near-infrared canopy albedo and up to 70% of the variance in visible canopy albedo. More intense thinning lowers the summertime shortwave albedo in the canopy by as much as 0.02 compared to unthinned forest. The structural changes associated with forest thinning can be described by the change in LAI in combination with crown volume. However, forests with identical canopy structure can have different summertime albedo values due to their location: the further north a forest is situated, the more the solar zenith angle increases and thus the higher is the summertime canopy albedo, independent of the wavelength. Despite the increase of absolute summertime canopy albedo values with latitude, the difference in canopy albedo between managed and unmanaged forest decreases with increasing latitude. Forest management thus strongly altered summertime forest albedo.

scholarly journals Nitrogen dioxide observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument: Retrieval algorithm and measurements during DISCOVER-AQ Texas 2013

2016 ◽  
Vol 9 (6) ◽  
pp. 2647-2668 ◽  
Author(s):  
Caroline R. Nowlan ◽  
Xiong Liu ◽  
James W. Leitch ◽  
Kelly Chance ◽  
Gonzalo González Abad ◽  
...  
Keyword(s):  
Air Quality ◽  
Near Infrared ◽  
Infrared Light ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Test Bed ◽  
Mixing Ratios ◽  
Sensor Optimization

Abstract. The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO2 at 250 m  ×  250 m spatial resolution with a fitting precision of 2.2 × 1015 moleculescm−2. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements and r = 0.74 overall), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.85). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.81, slope = 0.91). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.

scholarly journals Estimation of Multi-Species Leaf Area Index Based on Chinese GF-1 Satellite Data Using Look-Up Table and Gaussian Process Regression Methods

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2460 ◽  
Author(s):  
Yangyang Zhang ◽  
Jian Yang ◽  
Xiuguo Liu ◽  
Lin Du ◽  
Shuo Shi ◽  
...  
Keyword(s):  
Gaussian Process ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Vegetation Index ◽  
Gaussian Process Regression ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Area Index ◽  
Look Up Table ◽  
Band Combinations

Leaf area index (LAI) is an important biophysical parameter, which can be effectively applied in the estimation of vegetation growth status. At present, amounts of studies just focused on the LAI estimation of a single plant type, while plant types are usually mixed rather than single distribution. In this study, the suitability of GF-1 data for multi-species LAI estimation was evaluated by using Gaussian process regression (GPR), and a look-up table (LUT) combined with a PROSAIL radiative transfer model. Then, the performance of the LUT and GPR for multi-species LAI estimation was analyzed in term of 15 different band combinations and 10 published vegetation indices (VIs). Lastly, the effect of the different band combinations and published VIs on the accuracy of LAI estimation was discussed. The results indicated that GF-1 data exhibited a good potential for multi-species LAI retrieval. Then, GPR exhibited better performance than that of LUT for multi-species LAI estimation. What is more, modified soil adjusted vegetation index (MSAVI) was selected based on the GPR algorithm for multi-species LAI estimation with a lower root mean squared error (RMSE = 0.6448 m2/m2) compared to other band combinations and VIs. Then, this study can provide guidance for multi-species LAI estimation.

scholarly journals VIS-NIR, Red-Edge and NIR-Shoulder Based Normalized Vegetation Indices Response to Co-Varying Leaf and Canopy Structural Traits in Heterogeneous Grasslands

2020 ◽  
Vol 12 (14) ◽  
pp. 2254 ◽  
Author(s):  
Hafiz Ali Imran ◽  
Damiano Gianelle ◽  
Duccio Rocchini ◽  
Michele Dalponte ◽  
M. Pilar Martín ◽  
...  
Keyword(s):  
Near Infrared ◽  
Spatial Scales ◽  
Vegetation Indices ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Sharp Change ◽  
Full Potential ◽  
Area Index ◽  
Red Edge ◽  
Temporal And Spatial

Red-edge (RE) spectral vegetation indices (SVIs)—combining bands on the sharp change region between near infrared (NIR) and visible (VIS) bands—alongside with SVIs solely based on NIR-shoulder bands (wavelengths 750–900 nm) have been shown to perform well in estimating leaf area index (LAI) from proximal and remote sensors. In this work, we used RE and NIR-shoulder SVIs to assess the full potential of bands provided by Sentinel-2 (S-2) and Sentinel-3 (S-3) sensors at both temporal and spatial scales for grassland LAI estimations. Ground temporal and spatial observations of hyperspectral reflectance and LAI were carried out at two grassland sites (Monte Bondone, Italy, and Neustift, Austria). A strong correlation (R2 > 0.8) was observed between grassland LAI and both RE and NIR-shoulder SVIs on a temporal basis, but not on a spatial basis. Using the PROSAIL Radiative Transfer Model (RTM), we demonstrated that grassland structural heterogeneity strongly affects the ability to retrieve LAI, with high uncertainties due to structural and biochemical PTs co-variation. The RENDVI783.740 SVI was the least affected by traits co-variation, and more studies are needed to confirm its potential for heterogeneous grasslands LAI monitoring using S-2, S-3, or Gaofen-5 (GF-5) and PRISMA bands.

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