Remote sensing reflectance in the near infrared derived from SeaWiFS: implications for river plume particle size distribution, atmospheric correction, and bio-optical algorithms

2003 ◽  
Author(s):  
Chuanmin Hu
Keyword(s):  
Remote Sensing ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Near Infrared ◽  
Atmospheric Correction ◽  
River Plume ◽  
Remote Sensing Reflectance

Particle size distribution of river-suspended sediments determined by in situ measured remote-sensing reflectance

2015 ◽  
Vol 54 (20) ◽  
pp. 6367 ◽  
Author(s):  
Yuanzhi Zhang ◽  
Zhaojun Huang ◽  
Chuqun Chen ◽  
Yijun He ◽  
Tingchen Jiang
Keyword(s):  
Remote Sensing ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Suspended Sediments ◽  
Remote Sensing Reflectance

scholarly journals Bayesian Retrievals of Vertically Resolved Cloud Particle Size Distribution Properties

2017 ◽  
Vol 56 (3) ◽  
pp. 745-765 ◽  
Author(s):  
Derek J. Posselt ◽  
James Kessler ◽  
Gerald G. Mace
Keyword(s):  
Remote Sensing ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Prior Knowledge ◽  
Unique Solution ◽  
Joint Probability Distribution ◽  
Sufficient Information ◽  
Near Infrared Reflectance ◽  
Cloud Properties

AbstractRetrievals of liquid cloud properties from remote sensing observations by necessity assume sufficient information is contained in the measurements, and in the prior knowledge of the cloudy state, to uniquely determine a solution. Bayesian algorithms produce a retrieval that consists of the joint probability distribution function (PDF) of cloud properties given the measurements and prior knowledge. The Bayesian posterior PDF provides the maximum likelihood estimate, the information content in specific measurements, the effect of observation and forward model uncertainties, and quantitative error estimates. It also provides a test of whether, and in which contexts, a set of observations is able to provide a unique solution. In this work, a Bayesian Markov chain Monte Carlo (MCMC) algorithm is used to sample the joint posterior PDF for retrieved cloud properties in shallow liquid clouds over the remote Southern Ocean. Combined active and passive observations from spaceborne W-band cloud radar and visible and near-infrared reflectance are used to retrieve the parameters of a gamma particle size distribution (PSD) for cloud droplets and drizzle. Combined active and passive measurements are able to distinguish between clouds with and without precipitation; however, unique retrieval of PSD properties requires specification of a scene-appropriate prior estimate. While much of the uncertainty in an unconstrained retrieval can be mitigated by use of information from 94-GHz passive brightness temperature measurements, simply increasing measurement accuracy does not render a unique solution. The results demonstrate the robustness of a Bayesian retrieval methodology and highlight the importance of an appropriately scene-consistent prior constraint in underdetermined remote sensing retrievals.

scholarly journals Normalized particle size distribution for remote sensing application

2014 ◽  
Vol 119 (7) ◽  
pp. 4204-4227 ◽  
Author(s):  
J. M. E. Delanoë ◽  
A. J. Heymsfield ◽  
A. Protat ◽  
A. Bansemer ◽  
R. J. Hogan
Keyword(s):  
Remote Sensing ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Remote Sensing Application ◽  
Sensing Application

Nearfield development of the negatively buoyant Rhône River inflow into Lake Geneva as an interflow: suspended particulate matter and associated fluxes.

2021 ◽  
Author(s):  
Violaine Piton ◽  
Frédéric Soulignac ◽  
Ulrich Lemmin ◽  
Graf Benjamin ◽  
Htet Kyi Wynn ◽  
...  
Keyword(s):  
Particle Size ◽  
Particulate Matter ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Suspended Particulate Matter ◽  
Fine Particles ◽  
River Plume ◽  
Lake Geneva ◽  
Suspended Particulate ◽  
Negatively Buoyant

<p>River inflows have a major influence on lake water quality through their input of sediments, nutrients and contaminants. It is therefore essential to determine their pathways, their mixing with ambient waters and the amount and type of Suspended Particulate Matter (SPM) they carry. Two field campaigns during the stratified period took place in Lake Geneva, Switzerland, in the vicinity of the Rhône River plume, at high and intermediate river discharge. Currents, water and sediment fluxes, temperature, turbidity and particle size distribution were measured along three circular transects located at 400, 800 and 1500 m in front of the river mouth. During the surveys, the lake was thermally stratified, the negatively buoyant Rhône River plume plunged and intruded into the metalimnion as an interflow and flowed out in the streamwise direction. Along the pathway, interflow core velocities, SPM concentrations and volumes of particles progressively decreased with the distance from the mouth (by 2-3 times), while interflow cross sections and plume volume increased by 2-3 times due to entrainment of ambient water. The characteristics of the river outflow determined the characteristics of the interflows: i.e. interflow fluxes and concentrations were the highest at high discharge. Both sediment settling and interflow dilution contributed to the observed decrease of sediment discharge with distance from the mouth. The particle size distribution of the interflow was dominated by fine particles (<32 μm), which were transported up to 1500 m away from the mouth and most likely beyond, while large particles (>62 μm) have almost completely settled out before reaching 1500 m. </p>

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