Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 496018
Title Measuring aeolian sand transport using acoustic sensors
Author(s) Poortinga, Ate; Rheenen, Hans van; Ellis, J.T.; Sherman, D.J.
Source Aeolian Research 16 (2015). - ISSN 1875-9637 - p. 143 - 151.
DOI https://doi.org/10.1016/j.aeolia.2014.12.003
Department(s) Soil Physics and Land Management
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2015
Keyword(s) Aeolian sand transport - Field measurements - Laboratory experiment - Miniphone - Saltation - Saltiphone
Abstract

Acoustic sensors are frequently used to measure aeolian saltation. Different approaches are used to process the signals from these instruments. The goal of this paper is to describe and discuss a method to measure aeolian saltation with acoustic sensors. In a laboratory experiment, we measured the output from an advanced signal processing scheme on the circuit board of the saltiphone. We use a software implementation of this processing scheme to re-analyse data from four miniphones obtained during a field experiment. It is shown that a set of filters remove background noise outside the frequency spectrum of aeolian saltation (at 8. kHz), whereas signals within this frequency spectrum are amplified. The resulting analogue signal is a proxy of the energy. Using an AC pulse convertor, this signal can be converted into a digital and analogue count signal or an analogue energy signal, using a rectifier and integrator. Spatio-temporal correlation between field deployed miniphones increases by using longer integration times for signal processing. To quantify aeolian grain impact, it is suggested to use the analogue energy output, as this mode is able to detect changes in frequency and amplitude. The analogue and digital count signals are able to detect an increase in frequency, but are not able to detect an increase in signal amplitude. We propose a two-stage calibration scheme consisting of (1) a factory calibration, to set the frequency spectrum of the sensor and (2) a standardized drop-test conducted before and after the experiment to evaluate the response of the sensor.

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