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Article ; Online: Subtidal seagrass detector

Lucas A. Langlois / Catherine J. Collier / Len J. McKenzie

Frontiers in Marine Science, Vol

development of a deep learning seagrass detection and classification model for seagrass presence and density in diverse habitats from underwater photoquadrats

2023 Volume 10

Abstract: This paper presents the development and evaluation of a Subtidal Seagrass Detector (the Detector). Deep learning models were used to detect most forms of seagrass occurring in a diversity of habitats across the northeast Australian seascape from ... ...

Abstract	This paper presents the development and evaluation of a Subtidal Seagrass Detector (the Detector). Deep learning models were used to detect most forms of seagrass occurring in a diversity of habitats across the northeast Australian seascape from underwater images and classify them based on how much the cover of seagrass was present. Images were collected by scientists and trained contributors undertaking routine monitoring using drop-cameras mounted over a 50 x 50 cm quadrat. The Detector is composed of three separate models able to perform the specific tasks of: detecting the presence of seagrass (Model #1); classify the seagrass present into three broad cover classes (low, medium, high) (Model #2); and classify the substrate or image complexity (simple of complex) (Model #3). We were able to successfully train the three models to achieve high level accuracies with 97%, 80.7% and 97.9%, respectively. With the ability to further refine and train these models with newly acquired images from different locations and from different sources (e.g. Automated Underwater Vehicles), we are confident that our ability to detect seagrass will improve over time. With this Detector we will be able rapidly assess a large number of images collected by a diversity of contributors, and the data will provide invaluable insights about the extent and condition of subtidal seagrass, particularly in data-poor areas.
Keywords	seagrass ; Great Barrier Reef ; deep learning ; image classification ; underwater ; Science ; Q ; General. Including nature conservation ; geographical distribution ; QH1-199.5
Subject code	551
Language	English
Publishing date	2023-07-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Effect of Environmental Heterogeneity and Trophic Status in Sampling Strategy on Estimation of Small-Scale Regional Biodiversity of Microorganisms

Changyu Zhu / Gaytha A. Langlois / Yan Zhao

Microorganisms, Vol 10, Iss 2119, p

2022 Volume 2119

Abstract: Microorganisms are diverse and play key roles in lake ecosystems, therefore, a robust estimation of their biodiversity and community structure is crucial for determining their ecological roles in lakes. Conventionally, molecular surveys of microorganisms ...

Abstract	Microorganisms are diverse and play key roles in lake ecosystems, therefore, a robust estimation of their biodiversity and community structure is crucial for determining their ecological roles in lakes. Conventionally, molecular surveys of microorganisms in lakes are primarily based on equidistant sampling. However, this sampling strategy overlooks the effects of environmental heterogeneity and trophic status in lake ecosystems, which might result in inaccurate biodiversity assessments of microorganisms. Here, we conducted equidistant sampling from 10 sites in two regions with different trophic status within East Lake (Wuhan, China), to verify the reliability of this sampling strategy and assess the influence of environmental heterogeneity and trophic status on this strategy. Rarefaction curves showed that the species richness of microbial communities in the region of the lake with higher eutrophication failed to reach saturation compared with that in lower trophic status. The microbial compositions of samples from the region with higher trophic status differed significantly ( P < 0.05) from those in the region with lower trophic status. The result of this pattern may be explained by complex adaptations of lake microorganisms in high eutrophication regions with environmental conditions, where community differentiation can be viewed as adaptations to these environmental selection forces. Therefore, when conducting surveys of microbial biodiversity in a heterogeneous environment, investigators should incorporate intensive sampling to assess the variability in microbial distribution in response to a range of factors in the local microenvironment.
Keywords	equidistant sampling ; environmental heterogeneity ; trophic status ; high-throughput sequencing ; microbial diversity ; Biology (General) ; QH301-705.5
Subject code	333
Language	English
Publishing date	2022-10-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Investigation into percolation and liquid water content in a multi-layered snow model for wet snow instabilities in Glacier National Park, Canada

J-B. Madore / C. Fierz / A. Langlois

Frontiers in Earth Science, Vol

2022 Volume 10

Abstract: Water percolation in snow plays a crucial role in the avalanche risk assessment. Liquid water content and wetting front are hard to measure in the field; hence, accurate simulation of the phenomena can be of great help to forecasters. This study was the ... ...

Abstract	Water percolation in snow plays a crucial role in the avalanche risk assessment. Liquid water content and wetting front are hard to measure in the field; hence, accurate simulation of the phenomena can be of great help to forecasters. This study was the first to evaluate water percolation simulations with the SNOWPACK model using Richards’ scheme on Mount Fidelity, Glacier National Park, Canada. The study highlights that, at this site, an updated configuration on precipitation phase transition and new snow density can significantly improve simulations of the snow cover, and water percolation in particular, which can be relevant in an era of an increased occurrence of rain-on-snow (ROS) events. More specifically, emphasis was put on the quality of the input data and parameters. The analysis of the precipitation phase temperature threshold showed that a value of 1.4°C was the best suited to track the rain/snow transition on site. A 10-year analysis of 24-h precipitation measured using the rain gauge and 24-h new snow water equivalent showed an excellent correlation. New snow density sub-models were evaluated using the 24-h new snow density values taken by the park technicians. The BELLAIRE model performed best and was used to drive the snow simulations. Two SNOWPACK snow simulations were evaluated using 1) rain gauge precipitation amount (PCPM) and 2) automatic snow height measurement (HS) at the same site. Both runs simulated the main snowpack layers observed during the dry season (i.e., before spring percolation was observed), and both simulated the snow properties with good accuracy. The water equivalent of snow cover, used as a proxy for a first-order characterization of the simulations generated by both simulations, was slightly underestimated compared with four manual measurements taken on-site during the winter. Nevertheless, the comparison of both measured density and modeled bulk density showed great correspondence. The percolation timing and wetting front depth were evaluated using field measurements ...
Keywords	water percolation ; snow simulation ; liquid water content ; Richards’ equation ; parameterization ; Science ; Q
Subject code	551
Language	English
Publishing date	2022-11-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Review article

A. Royer / A. Roy / S. Jutras / A. Langlois

The Cryosphere, Vol 15, Pp 5079-

Performance assessment of radiation-based field sensors for monitoring the water equivalent of snow cover (SWE)

2021 Volume 5098

Abstract: Continuous and spatially distributed data of snow mass (water equivalent of snow cover, SWE) from automatic ground-based measurements are increasingly required for climate change studies and for hydrological applications (snow hydrological-model ... ...

Abstract	Continuous and spatially distributed data of snow mass (water equivalent of snow cover, SWE) from automatic ground-based measurements are increasingly required for climate change studies and for hydrological applications (snow hydrological-model improvement and data assimilation). We present and compare four new-generation sensors, now commercialized, that are non-invasive and based on different radiations that interact with snow for SWE monitoring: cosmic-ray neutron probe (CRNP), gamma ray monitoring (GMON) scintillator, frequency-modulated continuous-wave radar (FMCW radar) at 24 GHz and global navigation satellite system (GNSS) receivers (GNSSr). All four techniques have relatively low power requirements, provide continuous and autonomous SWE measurements, and can be easily installed in remote areas. A performance assessment of their advantages, drawbacks and uncertainties is discussed from experimental comparisons and a literature review. Relative uncertainties are estimated to range between 9 % and 15 % when compared to manual in situ snow surveys that are also discussed. Results show the following. (1) CRNP can be operated in two modes of functioning: beneath the snow, it is the only system able to measure very deep snowpacks ( > 2000 mm w.e.) with reasonable uncertainty across a wide range of measurements; CRNP placed above the snow allows for SWE measurements over a large footprint ( ∼ 20 ha) above a shallow snowpack. In both cases, CRNP needs ancillary atmospheric measurements for SWE retrieval. (2) GMON is the most mature instrument for snowpacks that are typically up to 800 mm w.e. Both CRNP (above snow) and GMON are sensitive to surface soil moisture. (3) FMCW radar needs auxiliary snow-depth measurements for SWE retrieval and is not recommended for automatic SWE monitoring (limited to dry snow). FMCW radar is very sensitive to wet snow, making it a very useful sensor for melt detection (e.g., wet avalanche forecasts). (4) GNSSr allows three key snowpack parameters to be estimated simultaneously: ...
Keywords	Environmental sciences ; GE1-350 ; Geology ; QE1-996.5
Subject code	551
Language	English
Publishing date	2021-11-01T00:00:00Z
Publisher	Copernicus Publications
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Characterization of influenza A virus induced transposons reveals a subgroup of transposons likely possessing the regulatory role as eRNAs

Steven S. Shen / Hezkiel Nanda / Constantin Aliferis / Ryan A. Langlois

Scientific Reports, Vol 12, Iss 1, Pp 1-

2022 Volume 12

Abstract: Abstract Although many studies have observed genome-wide host transposon expression alteration during viral infection, the mechanisms of induction and the impact on the host remain unclear. Utilizing recently published influenza A virus (IAV) time series ...

Abstract	Abstract Although many studies have observed genome-wide host transposon expression alteration during viral infection, the mechanisms of induction and the impact on the host remain unclear. Utilizing recently published influenza A virus (IAV) time series data and ENCODE functional genomics data, we characterized virus induced host differentially expressed transposons (virus-induced-TE) by investigating genome-wide spatial and functional relevance between the virus-induced-TEs and epigenomic markers (e.g. histone modification and chromatin remodelers). We found that a significant fraction of virus-induced-TEs are derived from host enhancer regions, where CHD4 binding and/or H3K27ac occupancy is high or H3K9me3 occupancy is low. By overlapping virus-induced-TEs to human enhancer RNAs (eRNAs), we discovered that a proportion of virus-induced-TEs are either eRNAs or part of enhancer RNAs. Upon further analysis of the eRNA targeted genes, we found that the virus-induced-TE related eRNA targets are overrepresented in differentially expressed host genes of IAV infected samples. Our results suggest that changing chromatin accessibility from repressive to permissive in the transposon docked enhancer regions to regulate host downstream gene expression is potentially one of the virus and host cell interaction mechanisms, where transposons are likely important regulatory genomic elements. Our study provides a new insight into the mechanisms of virus-host interaction and may lead to novel strategies for prevention and therapeutics of IAV and other virus infectious diseases.
Keywords	Medicine ; R ; Science ; Q
Subject code	570
Language	English
Publishing date	2022-02-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Improving Approaches to Mapping Seagrass within the Great Barrier Reef

Len J. McKenzie / Lucas A. Langlois / Chris M. Roelfsema

Remote Sensing, Vol 14, Iss 2604, p

From Field to Spaceborne Earth Observation

2022 Volume 2604

Abstract: Seagrass meadows are a key ecosystem of the Great Barrier Reef World Heritage Area, providing one of the natural heritage attributes underpinning the reef’s outstanding universal value. We reviewed approaches employed to date to create maps of seagrass ... ...

Abstract	Seagrass meadows are a key ecosystem of the Great Barrier Reef World Heritage Area, providing one of the natural heritage attributes underpinning the reef’s outstanding universal value. We reviewed approaches employed to date to create maps of seagrass meadows in the optically complex waters of the Great Barrier Reef and explored enhanced mapping approaches with a focus on emerging technologies, and key considerations for future mapping. Our review showed that field-based mapping of seagrass has traditionally been the most common approach in the GBRWHA, with few attempts to adopt remote sensing approaches and emerging technologies. Using a series of case studies to harness the power of machine- and deep-learning, we mapped seagrass cover with PlanetScope and UAV-captured imagery in a variety of settings. Using a machine-learning pixel-based classification coupled with a bootstrapping process, we were able to significantly improve maps of seagrass, particularly in low cover, fragmented and complex habitats. We also used deep-learning models to derive enhanced maps from UAV imagery. Combined, these lessons and emerging technologies show that more accurate and efficient seagrass mapping approaches are possible, producing maps of higher confidence for users and enabling the upscaling of seagrass mapping into the future.
Keywords	seagrass ; Great Barrier Reef ; mapping ; earth observing ; machine-learning ; deep-learning ; Science ; Q
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Potential of X-band polarimetric synthetic aperture radar co-polar phase difference for arctic snow depth estimation

J. Voglimacci-Stephanopoli / A. Wendleder / H. Lantuit / A. Langlois / S. Stettner / A. Schmitt / J.-P. Dedieu / A. Roth / A. Royer

The Cryosphere, Vol 16, Pp 2163-

2022 Volume 2181

Abstract: Changes in snowpack associated with climatic warming has drastic impacts on surface energy balance in the cryosphere. Yet, traditional monitoring techniques, such as punctual measurements in the field, do not cover the full snowpack spatial and temporal ... ...

Abstract	Changes in snowpack associated with climatic warming has drastic impacts on surface energy balance in the cryosphere. Yet, traditional monitoring techniques, such as punctual measurements in the field, do not cover the full snowpack spatial and temporal variability, which hampers efforts to upscale measurements to the global scale. This variability is one of the primary constraints in model development. In terms of spatial resolution, active microwaves (synthetic aperture radar – SAR) can address the issue and outperform methods based on passive microwaves. Thus, high-spatial-resolution monitoring of snow depth (SD) would allow for better parameterization of local processes that drive the spatial variability of snow. The overall objective of this study is to evaluate the potential of the TerraSAR-X (TSX) SAR sensor and the wave co-polar phase difference (CPD) method for characterizing snow cover at high spatial resolution. Consequently, we first (1) investigate SD and depth hoar fraction (DHF) variability between different vegetation classes in the Ice Creek catchment (Qikiqtaruk/Herschel Island, Yukon, Canada) using in situ measurements collected over the course of a field campaign in 2019; (2) evaluate linkages between snow characteristics and CPD distribution over the 2019 dataset; and (3) determine CPD seasonality considering meteorological data over the 2015–2019 period. SD could be extracted using the CPD when certain conditions are met. A high incidence angle ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" display="inline" overflow="scroll" dspmath="mathml"><mrow><mo>></mo><mn mathvariant="normal">30</mn><msup><mi/><mo>∘</mo></msup></mrow></math> <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="608b9cd09c1afe778032015dc6acba8e"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="tc-16-2163-2022-ie00001.svg" width="29pt" ...<br />
Keywords	Environmental sciences ; GE1-350 ; Geology ; QE1-996.5
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	Copernicus Publications
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Characterizing tundra snow sub-pixel variability to improve brightness temperature estimation in satellite SWE retrievals

J. Meloche / A. Langlois / N. Rutter / A. Royer / J. King / B. Walker / P. Marsh / E. J. Wilcox

The Cryosphere, Vol 16, Pp 87-

2022 Volume 101

Abstract: Topography and vegetation play a major role in sub-pixel variability of Arctic snowpack properties but are not considered in current passive microwave (PMW) satellite SWE retrievals. Simulation of sub-pixel variability of snow properties is also ... ...

Abstract	Topography and vegetation play a major role in sub-pixel variability of Arctic snowpack properties but are not considered in current passive microwave (PMW) satellite SWE retrievals. Simulation of sub-pixel variability of snow properties is also problematic when downscaling snow and climate models. In this study, we simplified observed variability of snowpack properties (depth, density, microstructure) in a two-layer model with mean values and distributions of two multi-year tundra dataset so they could be incorporated in SWE retrieval schemes. Spatial variation of snow depth was parameterized by a log-normal distribution with mean ( μ sd ) values and coefficients of variation (CV sd ). Snow depth variability (CV sd ) was found to increase as a function of the area measured by a remotely piloted aircraft system (RPAS). Distributions of snow specific surface area (SSA) and density were found for the wind slab (WS) and depth hoar (DH) layers. The mean depth hoar fraction (DHF) was found to be higher in Trail Valley Creek (TVC) than in Cambridge Bay (CB), where TVC is at a lower latitude with a subarctic shrub tundra compared to CB, which is a graminoid tundra. DHFs were fitted with a Gaussian process and predicted from snow depth. Simulations of brightness temperatures using the Snow Microwave Radiative Transfer (SMRT) model incorporating snow depth and DHF variation were evaluated with measurements from the Special Sensor Microwave/Imager and Sounder (SSMIS) sensor. Variation in snow depth (CV sd ) is proposed as an effective parameter to account for sub-pixel variability in PMW emission, improving simulation by 8 K. SMRT simulations using a CV sd of 0.9 best matched CV sd observations from spatial datasets for areas > 3 km 2 , which is comparable to the 3.125 km pixel size of the Equal-Area Scalable Earth (EASE)-Grid 2.0 enhanced resolution at 37 GHz.
Keywords	Environmental sciences ; GE1-350 ; Geology ; QE1-996.5
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Copernicus Publications
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: In-situ passive microwave emission model parameterization of sub-arctic frozen organic soils

Montpetit, B / A. Langlois / A. Roy / A. Royer

Remote sensing of environment. 2018 Feb., v. 205

2018

Abstract: Many passive microwave remote sensing applications such as land surface temperature, snow water equivalent and soil moisture retrievals need to take into account a soil parameterization to the overall surface signal emission. Soil emission modeling ... ...

Abstract	Many passive microwave remote sensing applications such as land surface temperature, snow water equivalent and soil moisture retrievals need to take into account a soil parameterization to the overall surface signal emission. Soil emission modeling presents large uncertainties when the soil is frozen. In this paper, an empirical retrieval method is presented, specifically for rough frozen soil permittivity estimates at 10.7, 19 and 37GHz. The method was tested and validated using in-situ passive microwave measurements at incidence angles from 0 to 60° of sub-arctic frozen organic soils in Northeastern Canada. The retrieved permittivity values give an overall RMSE between the measured and simulated brightness temperatures of 4.6K for all frequencies combined. A sensitivity analysis was conducted on the different soil parameters optimized in this study. This analysis suggests that the accuracy of the retrieved parameters, using the method given here, is of ±1.00 for the permittivity and ±0.12cm for surface roughness. Also, a comparison was conducted between the parameterization used in this study and the one of Wegmüller and Mätzler (1999) to estimate the soil contribution to the emitted brightness temperature of snowpacks. An improvement of 66% of the RMSE between the modeled and measured snow brightness temperatures was observed when using the approach of this study compared to the previous work. The method shows great potential to improve the estimation of the frozen soil contribution to the measured passive microwave brightness temperature.
Keywords	angle of incidence ; frozen soils ; models ; organic soils ; remote sensing ; snow ; snowpack ; soil water ; surface roughness ; surface temperature ; uncertainty ; Canada
Language	English
Dates of publication	2018-02
Size	p. 112-118.
Publishing place	Elsevier Inc.
Document type	Article
ZDB-ID	431483-9
ISSN	0034-4257
ISSN	0034-4257
DOI	10.1016/j.rse.2017.10.033
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Potential of RADARSAT-2 stereo radargrammetry for the generation of glacier DEMs

C. PAPASODORO / A. ROYER / A. LANGLOIS / E. BERTHIER

Journal of Glaciology, Vol 62, Pp 486-

2016 Volume 496

Abstract: The study of glaciers and ice caps in remote and cloudy regions remains difficult using current remote sensing tools. Here the potential of stereo radargrammetry (SRG) with RADARSAT-2 Wide Ultra-Fine images is explored for DEM extraction, elevation ... ...

Abstract	The study of glaciers and ice caps in remote and cloudy regions remains difficult using current remote sensing tools. Here the potential of stereo radargrammetry (SRG) with RADARSAT-2 Wide Ultra-Fine images is explored for DEM extraction, elevation changes and mass-balance calculations on Barnes Ice Cap (Nunavut, Canada). Over low-relief terrain surrounding Barnes, a vertical precision of ~7 m (1σ confidence level) is measured, as well as an average vertical bias of ~4 m. Moreover, we show that the C-band penetration depth over the ice cap is insignificant at this time of the year (i.e. late ablation season). This is likely due to a wet surface and the presence of superimposed ice that leads to a surface radar response. Comparing the SRG DEMs with other datasets, an historical glacier-wide mass balance of −0.52 ± 0.19 m w.e. a−1 is estimated for 1960–2013, whereas it decreases to −1.06 ± 0.84 m w.e. a−1 between 2005 and 2013. This clear acceleration of mass loss is in agreement with other recent studies. Given its all-weather functionality and its possible use without ground control points, the RADARSAT-2 SRG technology represents an appropriate alternative for glacier monitoring in cloudy and remote regions.
Keywords	Barnes Ice Cap ; Canadian Arctic Archipelago ; elevation change ; mass balance ; penetration depth ; stereo radargrammetry ; RADARSAT-2 ; Environmental sciences ; GE1-350 ; Meteorology. Climatology ; QC851-999
Subject code	550
Language	English
Publishing date	2016-06-01T00:00:00Z
Publisher	Cambridge University Press
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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