Paper
17 March 2005 Inverse problems of state parameters assessment for natural formations using satellite and ground-based observations
Vladimir V. Kozoderov
Author Affiliations +
Proceedings Volume 5829, 13th International Workshop on Lidar Multiple Scattering Experiments; (2005) https://doi.org/10.1117/12.617391
Event: 13th International Workshop on Lidar Multiple Scattering Experiments, 2004, St. Petersburg, Russian Federation
Abstract
Models of remote sensing (RS) and ground-based (GB) data formation are considered together with numerical/computational (NC) modeling for climate and biosphere research. Multispectral RS imagery processing, GB data mapping representation and a testing stage for specified NC experimentation are analyzed in conjunction with modeling procedures of temporal data series analysis for the RS/GB information products and for the NC outputs. Integrated assessment models are the final stage of the relevant (RS, GB, NC) applications. Models of interpretation of multispectral images in visual, infrared and microwave spectral bands are initial to solve the inverse problems of quantitative parameters assessment (the biomass amount, in particular, for forest and other ecosystems). Each pixel of the images under processing are represented in terms of the listed parameters retrieved from space in accordance with the proposed mathematical procedures. These parameters are invariant (not depending on) to angular coordinates of the related targets observation, Sun illumination conditions and the current state of the atmosphere. Basic principles of ecosystems management are derived from the outlined stages of monitoring and modeling.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vladimir V. Kozoderov "Inverse problems of state parameters assessment for natural formations using satellite and ground-based observations", Proc. SPIE 5829, 13th International Workshop on Lidar Multiple Scattering Experiments, (17 March 2005); https://doi.org/10.1117/12.617391
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KEYWORDS
Data modeling

Remote sensing

Atmospheric modeling

Mathematical modeling

Data processing

Image processing

Multispectral imaging

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