Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor's radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit

A Semi-Analytic Model for Estimating Total Suspended Sediment Concentration in Turbid Coastal Waters of Northern Western Australia Using MODIS-Aqua 250 m Data

Knowledge of the concentration of total suspended sediment (TSS) in coastal waters is of significance to marine environmental monitoring agencies to determine the turbidity of water that serve as a proxy to estimate the availability of light at depth for benthic habitats. TSS models applicable to data collected by satellite sensors can be used to determine TSS with reasonable accuracy and of adequate spatial and temporal resolution to be of use for coastal water quality monitoring. Thus, a study is presented here where we develop a semi-analytic sediment model (SASM) applicable to any sensor with red and near infrared (NIR) bands. The calibration and validation of the SASM using bootstrap and cross-validation methods showed that the SASM applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua band 1 data retrieved TSS with a root mean square error (RMSE) and mean averaged relative error (MARE) of 5.75 mg/L and 33.33% respectively. The application of the SASM over our study region using MODIS-Aqua band 1 data showed that the SASM can be used to monitor the on-going, post and pre-dredging activities and identify daily TSS anomalies that are caused by natural and anthropogenic processes in coastal waters of northern Western Australia

The atmospherically corrected <i>R</i>_rs (red band) product.

<p>(a) and (b) WV2 and MODIS-Aqua on June 13^th 2014; (c)-(e) Landsat-8 OLI and (f)-(h) MODIS-Aqua on May 23^rd, July 10^th and July 26^th 2014 respectively. The white cross mark on (a), (c)-(e) are the locations of the central pixel of 2.5 km square used in <i>R</i>_rs product validation. The black cross mark are locations corresponding to Dredged Areas (DA and DA2), Spoil Ground (SG), Clean Area (CA), River Plume (RP) and Moderate Turbid Area (MTA) in each image.</p

The TSS model curves for MODIS-Aqua (blue), Landsat-8 OLI (green) and WV2 (red).

<p>The <i>in situ</i> data points are shown by filled circles with the same colour profile as respective TSS model curves. The data for TSS < 10 mg L^-1 and <i>r</i>_rs < 0.025 sr^-1 are also shown in the blow out version of the plot.</p

Inter-satellite <i>R</i>_rs product validation results.

<p>(a) 2014 MODIS-Aqua vs Landsat-8 OLI <i>R</i>_rs product validation from May 23^rd, July 10^th and July 26^th 2014; (b) MODIS-Aqua vs WV2 <i>R</i>_rs product validation for <i>R</i>_rs from June 13^th. The error bars indicate the 17.5 percentile (lower limit) and 82.5 percentile (upper limit) of pixel values from a 2.5 km width box for each respective satellite sensors derived <i>R</i>_rs. Dashed lines indicate the 1: 1 relationship.</p

A semi-analytic model for estimating total suspended sediment concentration in turbid coastal waters of northern Western Australia using MODIS-Aqua 250 m data

© 2016 by the authors. Knowledge of the concentration of total suspended sediment (TSS) in coastal waters is of significance to marine environmental monitoring agencies to determine the turbidity of water that serve as a proxy to estimate the availability of light at depth for benthic habitats. TSS models applicable to data collected by satellite sensors can be used to determine TSS with reasonable accuracy and of adequate spatial and temporal resolution to be of use for coastal water quality monitoring. Thus, a study is presented here where we develop a semi-analytic sediment model (SASM) applicable to any sensor with red and near infrared (NIR) bands. The calibration and validation of the SASM using bootstrap and cross-validation methods showed that the SASM applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua band 1 data retrieved TSS with a root mean square error (RMSE) and mean averaged relative error (MARE) of 5.75 mg/L and 33.33% respectively. The application of the SASM over our study region using MODIS-Aqua band 1 data showed that the SASM can be used to monitor the on-going, post and pre-dredging activities and identify daily TSS anomalies that are caused by natural and anthropogenic processes in coastal waters of northern Western Australia

Assessing an Atmospheric Correction Algorithm for Time Series of Satellite-Based Water-Leaving Reflectance Using Match-Up Sites in Australian Coastal Waters

An atmospheric correction algorithm for medium-resolution satellite data over general water surfaces (open/coastal, estuarine and inland waters) has been assessed in Australian coastal waters. In situ measurements at four match-up sites were used with 21 Landsat 8 images acquired between 2014 and 2017. Three aerosol sources (AERONET, MODIS ocean aerosol and climatology) were used to test the impact of the selection of aerosol optical depth (AOD) and Ångström coefficient on the retrieved accuracy. The initial results showed that the satellite-derived water-leaving reflectance can have good agreement with the in situ measurements, provided that the sun glint is handled effectively. Although the AERONET aerosol data performed best, the contemporary satellite-derived aerosol information from MODIS or an aerosol climatology could also be as effective, and should be assessed with further in situ measurements. Two sun glint correction strategies were assessed for their ability to remove the glint bias. The most successful one used the average of two shortwave infrared (SWIR) bands to represent sun glint and subtracted it from each band. Using this sun glint correction method, the mean all-band error of the retrieved water-leaving reflectance at the Lucinda Jetty Coastal Observatory (LJCO) in north east Australia was close to 4% and unbiased over 14 acquisitions. A persistent bias in the other strategy was likely due to the sky radiance being non-uniform for the selected images. In regard to future options for an operational sun glint correction, the simple method may be sufficient for clear skies until a physically based method has been established

Cross-sectional survey of the disaster preparedness of nurses across the Asia–Pacific region

Healthcare workers who have received disaster preparedness education are more likely to report a greater understanding of disaster preparedness. However, research indicates that current nursing curricula do not adequately prepare nurses to respond to disasters. This is the first study to assess Asia–Pacific nurses' perceptions about their level of disaster knowledge, skills, and preparedness. A cross-sectional survey was conducted with 757 hospital and community nurses in seven Asia–Pacific countries. Data were collected using the modified Disaster Preparedness Evaluation Tool. Participants were found to have overall low-to-moderate levels of disaster knowledge, skills and preparedness, wherein important gaps were identified. A majority of the variance in disaster preparedness scores was located at the level of the individual respondent, not linked to countries or institutions. Multilevel random effects modelling identified disaster experience and education as significant factors of positive perceptions of disaster knowledge, skills, and management. The first step toward disaster preparedness is to ensure frontline health workers are able to respond effectively to disaster events. The outcomes of this study have important policy and education implications