High-Resolution Far-Infrared Observations and Radiative-Transfer Models of W3 IRS 4 and IRS 5

1995 ◽  
Vol 454 ◽  
pp. 831 ◽  
Author(s):  
M. F. Campbell ◽  
H. M. Butner ◽  
P. M. Harvey ◽  
N. J., II Evans ◽  
M. B. Campbell ◽  
...  
Keyword(s):  
High Resolution ◽  
Radiative Transfer ◽  
Far Infrared ◽  
Infrared Observations ◽  
Radiative Transfer Models ◽  
Transfer Models

An inter-comparison of far-infrared line-by-line radiative transfer models

2005 ◽  
Vol 90 (3-4) ◽  
pp. 323-341 ◽  
Author(s):  
David P. Kratz ◽  
Martin G. Mlynczak ◽  
Christopher J. Mertens ◽  
Helen Brindley ◽  
Larry L. Gordley ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Far Infrared ◽  
Radiative Transfer Models ◽  
Transfer Models

scholarly journals Quantitative estimation of vegetation traits and temporal dynamics using 3-D radiative transfer models, high-resolution hyperspectral images and satellite imagery

2021 ◽  
Author(s):  
◽  
Alberto Hornero Luque
Keyword(s):  
High Resolution ◽  
Radiative Transfer ◽  
Temporal Dynamics ◽  
Phytophthora Cinnamomi ◽  
Abiotic Factors ◽  
Specific Response ◽  
Substantial Impact ◽  
Radiative Transfer Models ◽  
Vegetation Health ◽  
Transfer Models

Large-scale monitoring of vegetation dynamics by remote sensing is key to detecting early signs of vegetation decline. Spectral-based indicators of phys-iological plant traits (PTs) have the potential to quantify variations in pho-tosynthetic pigments, chlorophyll fluorescence emission, and structural changes of vegetation as a function of stress. However, the specific response of PTs to disease-induced decline in heterogeneous canopies remains largely unknown, which is critical for the early detection of irreversible damage at different scales. Four specific objectives were defined in this research: i) to assess the feasibility of modelling the incidence and severity of Phytophthora cinnamomi and Xylella fastidiosa based on PTs and biophysical properties of vegetation; ii) to assess non-visual early indicators, iii) to retrieve PT using radiative transfer models (RTM), high-resolution imagery and satellite observations; and iv) to establish the basis for scaling up PTs at different spatial resolutions using RTM for their retrieval in different vegetation co-vers. This thesis integrates different approaches combining field data, air- and space-borne imagery, and physical and empirical models that allow the retrieval of indicators and the evaluation of each component’s contribution to understanding temporal variations of disease-induced symptoms in heter-ogeneous canopies. Furthermore, the effects associated with the understory are introduced, showing not only their impact but also providing a compre-hensive model to account for it. Consequently, a new methodology has been established to detect vegetation health processes and the influence of biotic and abiotic factors, considering different components of the canopy and their impact on the aggregated signal. It is expected that, using the presented methods, existing remote sensors and future developments, the ability to detect and assess vegetation health globally will have a substantial impact not only on socio-economic factors, but also on the preservation of our eco-system as a whole.

Inference over radiative transfer models using variational and expectation maximization methods

2021 ◽  
Author(s):  
Daniel Heestermans Svendsen ◽  
Daniel Hernández-Lobato ◽  
Luca Martino ◽  
Valero Laparra ◽  
Álvaro Moreno-Martínez ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Expectation Maximization ◽  
Radiative Transfer Models ◽  
Transfer Models

scholarly journals Comparisons of Ocean Radiative Transfer Models With SMAP and AMSR2 Observations

2019 ◽  
Vol 124 (11) ◽  
pp. 7683-7699 ◽  
Author(s):  
Lise Kilic ◽  
Catherine Prigent ◽  
Jacqueline Boutin ◽  
Thomas Meissner ◽  
Stephen English ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Radiative Transfer Models ◽  
Transfer Models
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