- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Bio-optical Modeling and Remote Sensing of Inland Waters || Atmospheric Correction for Inland Waters
摘要： Light received by a passive Earth-observing remote sensor goes through the Earth’s atmosphere twice—from the Sun to the Earth’s surface and from the surface to the sensor—before it reaches the sensor. As such, the light received at the sensor is invariably affected by absorption and scattering by gaseous molecules and particulate matter in the atmosphere. The process of correcting for the atmospheric effects and retrieving the reflectance of a target on the Earth’s surface is called atmospheric correction. The atmospheric effect on the radiance received by a remote sensor is significantly large over water bodies because water is highly absorptive and contributes to only 20% or less of the total at-sensor radiance (e.g., Hovis and Leung, 1977). Correcting for these atmospheric effects is an essential prerequisite to retrieving accurate estimates of water-leaving radiance, which is the basis for deriving quantitative estimates of biophysical parameters from remotely sensed data.
关键词： remote sensing,biophysical parameters,Atmospheric correction,inland waters,water-leaving radiance
更新于2025-09-09 09:28:46
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Comprehensive Remote Sensing || Inversion of Lumped Parameters Using BRDF Kernels
摘要： Remote sensing applications in the optical domain may require considering different categories of models ranging from exact to approximate modeling. Beyond the targeted objectives, it may be recommended to look after practical radiative transfer models that will offer fast solutions to the question of the inverse problem. However, the computational efficiency of the models is not likely a central question rather than assessing the potential of information that is contained in the satellite imagery. In general, a pixel of a satellite image will be described by a number of characteristics according to the four resolutions: spatial, spectral, angular, and temporal. The choice for the methodology to process the data will pay particular attention to the respective degree of information provided by these different offered resolutions. In a sense, it may be advised to stress some assumptions in order to reduce the physics. For instance, in the case of having a moderate or even a coarse scale resolution, a statistically based approach rather than a physically based approach aiming to provide in theory an exact modeling of the signal would appear preferable. In what it concerns the spectral resolution, the more available narrow bands the more options offered to describe the biogeochemical processes. In this latter case, obviously using physically based models is advised but also a rather high spatial resolution would be necessary. Concerning the temporal resolution, the surface processes generally evolve slowly in time at the exception of snow-covered areas showing rapid metamorphosis, or fortunately more rarely hazards. Thus, the choice for a model with lumped parameters does not necessarily relate to the frequency of observation of a sensor. On the other hand, the quality of the bidirectional reflectance directional function (BRDF) sampling is likely the more important issue. Originally, the BRDF kernel-based approach was implemented to capture most of the directional signatures, which, in a quite large majority is the case. Nonetheless, there exists some cases of directional signatures like the hot spot geometry or the glitter where the use of lumped parameters is unadapted because of the individual influence of individual structural parameters rather than their association. For such reasons, fundamental studies focused on the inclusion of a hot spot module (Wanner et al., 1995; Chen and Cihlar, 1997).
关键词： biophysical parameters,inverse methodology,Kalman filter,BRDF,remote sensing
更新于2025-09-04 15:30:14