Radiative transfer and viewing geometry considerations for remote sensing as a proxy for carbon uptake in boreal ecosystems

2021 ◽  
Author(s):  
Zoe Pierrat ◽  
Alexander Norton ◽  
Lea Baskin Monk ◽  
Nicholas Parazoo ◽  
Andrew Maguire ◽  
...  
2021 ◽  
Author(s):  
Isabella Pfeil ◽  
Wolfgang Wagner ◽  
Sebastian Hahn ◽  
Raphael Quast ◽  
Susan Steele-Dunne ◽  
...  

<div> <p>Soil moisture (SM) datasets retrieved from the advanced scatterometer (ASCAT) sensor are well established and widely used for various hydro-meteorological, agricultural, and climate monitoring applications. Besides SM, ASCAT is sensitive to vegetation structure and vegetation water content, enabling the retrieval of vegetation optical depth (VOD; 1). The challenge in the retrieval of SM and vegetation products from ASCAT observations is to separate the two effects. As described by Wagner et al. (2), SM and vegetation affect the relation between backscatter and incidence angle differently.  At high incidence angles, the response from bare soil and thus the sensitivity to SM conditions is significantly weaker than at low incidence angles, leading to decreasing backscatter with increasing incidence angle. The presence of vegetation on the other hand decreases the backscatter dependence on the incidence angle. The dependence of backscatter on the incidence angle can be described by a second-order Taylor polynomial based on a slope and a curvature coefficient. It was found empirically that SM conditions have no significant effect on the steepness of the slope, and that therefore, SM and vegetation effects can be separated using the slope (2).  This is a major assumption in the TU Wien soil moisture retrieval algorithm used in several operational soil moisture products. However, recent findings by Quast et al. (3) using a first-order radiative transfer model for the inversion of soil and vegetation parameters from scatterometer observations indicate that SM may influence the slope, as the SM-induced backscatter increase is more pronounced at low incidence angles. </p> </div><div> <div> <p>The aim of this analysis is to revisit the assumption that SM does not affect the slope of the backscatter incidence angle relations by investigating if short-term variability, observed in ASCAT slope timeseries on top of the seasonal vegetation cycle, is caused by SM. We therefore compare timeseries and anomalies of the ASCAT slope to air temperature, rainfall and SM from the ERA5-Land dataset. We carry out the analysis in a humid continental climate (Austria) and a Mediterranean climate study region (Portugal). First results show significant negative correlations between slope and SM anomalies. However, correlations between temperature and slope anomalies are of a similar magnitude, albeit positive, which may reflect temperature-induced vegetation dynamics. The fact that temperature and SM are strongly correlated with each other complicates the interpretation of the results. Thus, our second approach is to investigate daily slope values and their change between dry and wet days. The results of this study shall help to quantify the uncertainties in ASCAT SM products caused by the potentially inadequate assumption of a SM-independent slope. </p> </div> <div> <p> </p> </div> <div> <p>(1) Vreugdenhil, Mariette, et al. "Analyzing the vegetation parameterization in the TU-Wien ASCAT soil moisture retrieval." IEEE Transactions on Geoscience and Remote Sensing 54.6 (2016): 3513-3531.</p> <p><span>(2) Wagner, Wolfgang, et al. "Monitoring soil moisture over the Canadian Prairies with the ERS scatterometer." IEEE Transactions on Geoscience and Remote Sensing 37.1 (1999): 206-216. </span></p> </div> <div> <p>(3) Quast, Raphael, et al. "A Generic First-Order Radiative Transfer Modelling Approach for the Inversion of Soil and Vegetation Parameters from Scatterometer Observations." Remote Sensing 11.3 (2019): 285.</p> </div> </div>


2014 ◽  
Vol 18 (2) ◽  
pp. 35-45 ◽  
Author(s):  
Michał T. Chiliński ◽  
Marek Ostrowski

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.


2020 ◽  
Vol 13 (4) ◽  
pp. 1817-1824
Author(s):  
Kuijun Wu ◽  
Weiwei He ◽  
Yutao Feng ◽  
Yuanhui Xiong ◽  
Faquan Li

Abstract. The O2(a1Δg) emission near 1.27 µm is well-suited for remote sensing of global wind and temperature in near-space by limb-viewing observations to its bright signal and extended altitude coverage. However, vibrational–rotational emission lines of the OH dayglow produced by the hydrogen–ozone reaction (H+O3→OH•+O2) overlap the infrared atmospheric band emission (a1Δg→X3Σg) of O2. The main goal of this paper is to discuss the effect of OH emission on the wind and temperature measurements derived from the 1.27 µm O2 dayglow limb-viewing observations. The O2 dayglow and OH dayglow spectrum over the spectral region and altitude range of interest is calculated by using the line-by-line radiative transfer model and the most recent photochemical model. The method of four-point sampling of the interferogram and sample results of measurement simulations are provided for both O2 dayglow and OH dayglow. It is apparent from the simulations that the presence of OH dayglow as an interfering species decreases the wind and temperature accuracy at all altitudes, but this effect can be reduced considerably by improving OH dayglow knowledge.


2019 ◽  
Vol 36 (2) ◽  
pp. 203-216 ◽  
Author(s):  
Jarred L. Burley ◽  
Steven T. Fiorino ◽  
Brannon J. Elmore ◽  
Jaclyn E. Schmidt

Abstract The ability to quickly and accurately model actual atmospheric conditions is essential to remote sensing analyses. Clouds present a particularly complex challenge, as they cover up to 70% of Earth’s surface, and their highly variable and diverse nature necessitates physics-based modeling. The Laser Environmental Effects Definition and Reference (LEEDR) is a verified and validated atmospheric propagation and radiative transfer code that creates physically realizable vertical and horizontal profiles of meteorological data. Coupled with numerical weather prediction (NWP) model output, LEEDR enables analysis, nowcasts, and forecasts for radiative effects expected for real-world scenarios. A recent development is the inclusion of the U.S. Air Force’s World-Wide Merged Cloud Analysis (WWMCA) cloud data in a new tool set that enables radiance calculations through clouds from UV to radio frequency (RF) wavelengths. This effort details the creation of near-real-time profiles of atmospheric and cloud conditions and the resulting radiative transfer analysis for virtually any wavelength(s) of interest. Calendar year 2015 data are analyzed to establish climatological limits for diffuse transmission in the 300–1300-nm band, and the impacts of various geometry, cloud microphysical, and atmospheric conditions are examined. The results show that 80% of diffuse band transmissions are estimated to fall between 0.248 and 0.889 under the assumptions of cloud homogeneity and maximum overlap and are sufficient for establishing diffuse transmission percentiles. The demonstrated capability provides an efficient way to extend optical wavelength cloud parameters across the spectrum for physics-based multiple-scattering effects modeling through cloudy and clear atmospheres, providing an improvement to atmospheric correction for remote sensing and cloud effects on system performance metrics.


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