Unoccupied aerial vehicle-assisted monitoring of benthic vegetation in the coastal zone enhances the quality of ecological data

Author(s):  
Niels Svane ◽  
Troels Lange ◽  
Sara Egemose ◽  
Oliver Dalby ◽  
Aris Thomasberger ◽  
...  

Traditional monitoring (e.g., in-water based surveys) of eelgrass meadows and perennial macroalgae in coastal areas is time and labor intensive, requires extensive equipment, and the collected data has a low temporal resolution. Further, divers and Remotely Operated Vehicles (ROVs) have a low spatial extent that cover small fractions of full systems. The inherent heterogeneity of eelgrass meadows and macroalgae assemblages in these coastal systems makes interpolation and extrapolation of observations complicated and, as such, methods to collect data on larger spatial scales whilst retaining high spatial resolution is required to guide management. Recently, the utilization of Unoccupied Aerial Vehicles (UAVs) has gained popularity in ecological sciences due to their ability to rapidly collect large amounts of area-based and georeferenced data, making it possible to monitor the spatial extent and status of SAV communities with limited equipment requirements compared to ROVs or diver surveys. This paper is focused on the increased value provided by UAV-based, data collection (visual/Red Green Blue imagery) and Object Based Image Analysis for gaining an improved understanding of eelgrass recovery. It is demonstrated that delineation and classification of two species of SAV ( Fucus vesiculosus and Zostera marina) is possible; with an error matrix indicating 86–92% accuracy. Classified maps also highlighted the increasing biomass and areal coverage of F. vesiculosus as a potential stressor to eelgrass meadows. Further, authors derive a statistically significant conversion of percentage cover to biomass ( R2 = 0.96 for Fucus vesiculosus, R2 = 0.89 for Zostera marina total biomass, and R2 = 0.94 for AGB alone, p < 0.001). Results here provide an example of mapping cover and biomass of SAV and provide a tool to undertake spatio-temporal analyses to enhance the understanding of eelgrass ecosystem dynamics.

Forests ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 493 ◽  
Author(s):  
Dong Zhang ◽  
Jinhua Cheng ◽  
Ying Liu ◽  
Hongjiang Zhang ◽  
Lan Ma ◽  
...  

As a basal measure of soil bioengineering, the living brush mattress has been widely applied in riparian ecological protection forest construction. The living brush mattress shows favorable protective effects on riverbanks. However, there are few reports on the root structure and the soil strengthening benefit of the living brush mattress. The present work reports a series of experiments on root morphology and soil shear strength enhancement at the temporal and spatial scales. The object of the study is 24 living brush mattress trees constructed with Salix alba L. ‘Tristis’ (LBS hereafter). Traditional root morphology and mechanical measurement methods were used to collect the parameters. The results showed that the root systems of LBS had the characteristics of symmetry and upslope growth. The roots were mainly distributed in a cylindrical region of the soil (radius × thickness: 0.4 m × 0.5 m) and their biomass increased with different growth rates for the periods from 1 to 5 and from 5 to 7 years. Both age and slope position were factors that influence root growth. The root diameter falls within 0–5 mm, has a significant effect on the soil shear strength and provides a conical-shape potentiation zone to ensure the efficient protection of a riverbank. The results of this study demonstrate that LBS is an efficient and feasible engineering measure in the field of riverbank protection.


2017 ◽  
Vol 4 (2) ◽  
pp. 160900 ◽  
Author(s):  
Dániel Kondor ◽  
Sebastian Grauwin ◽  
Zsófia Kallus ◽  
István Gódor ◽  
Stanislav Sobolevsky ◽  
...  

Thanks to their widespread usage, mobile devices have become one of the main sensors of human behaviour and digital traces left behind can be used as a proxy to study urban environments. Exploring the nature of the spatio-temporal patterns of mobile phone activity could thus be a crucial step towards understanding the full spectrum of human activities. Using 10 months of mobile phone records from Greater London resolved in both space and time, we investigate the regularity of human telecommunication activity on urban scales. We evaluate several options for decomposing activity timelines into typical and residual patterns, accounting for the strong periodic and seasonal components. We carry out our analysis on various spatial scales, showing that regularity increases as we look at aggregated activity in larger spatial units with more activity in them. We examine the statistical properties of the residuals and show that it can be explained by noise and specific outliers. Also, we look at sources of deviations from the general trends, which we find to be explainable based on knowledge of the city structure and places of attractions. We show examples how some of the outliers can be related to external factors such as specific social events.


2016 ◽  
Vol 20 (4) ◽  
pp. 1387-1403 ◽  
Author(s):  
Hjalte Jomo Danielsen Sørup ◽  
Ole Bøssing Christensen ◽  
Karsten Arnbjerg-Nielsen ◽  
Peter Steen Mikkelsen

Abstract. Spatio-temporal precipitation is modelled for urban application at 1 h temporal resolution on a 2 km grid using a spatio-temporal Neyman–Scott rectangular pulses weather generator (WG). Precipitation time series used as input to the WG are obtained from a network of 60 tipping-bucket rain gauges irregularly placed in a 40 km  ×  60 km model domain. The WG simulates precipitation time series that are comparable to the observations with respect to extreme precipitation statistics. The WG is used for downscaling climate change signals from regional climate models (RCMs) with spatial resolutions of 25 and 8 km, respectively. Six different RCM simulation pairs are used to perturb the WG with climate change signals resulting in six very different perturbation schemes. All perturbed WGs result in more extreme precipitation at the sub-daily to multi-daily level and these extremes exhibit a much more realistic spatial pattern than what is observed in RCM precipitation output. The WG seems to correlate increased extreme intensities with an increased spatial extent of the extremes meaning that the climate-change-perturbed extremes have a larger spatial extent than those of the present climate. Overall, the WG produces robust results and is seen as a reliable procedure for downscaling RCM precipitation output for use in urban hydrology.


2001 ◽  
Vol 01 (03) ◽  
pp. 507-526 ◽  
Author(s):  
TONG LIN ◽  
HONG-JIANG ZHANG ◽  
QING-YUN SHI

In this paper, we present a novel scheme on video content representation by exploring the spatio-temporal information. A pseudo-object-based shot representation containing more semantics is proposed to measure shot similarity and force competition approach is proposed to group shots into scene based on content coherences between shots. Two content descriptors, color objects: Dominant Color Histograms (DCH) and Spatial Structure Histograms (SSH), are introduced. To represent temporal content variations, a shot can be segmented into several subshots that are of coherent content, and shot similarity measure is formulated as subshot similarity measure that serves to shot retrieval. With this shot representation, scene structure can be extracted by analyzing the splitting and merging force competitions at each shot boundary. Experimental results on real-world sports video prove that our proposed approach for video shot retrievals achieve the best performance on the average recall (AR) and average normalized modified retrieval rank (ANMRR), and Experiment on MPEG-7 test videos achieves promising results by the proposed scene extraction algorithm.


Author(s):  
Thomas C. van Leth ◽  
Hidde Leijnse ◽  
Aart Overeem ◽  
Remko Uijlenhoet

AbstractWe investigate the spatio-temporal structure of rainfall at spatial scales from 7m to over 200 km in the Netherlands. We used data from two networks of laser disdrometers with complementary interstation distances in two Dutch cities (comprising five and six disdrometers, respectively) and a Dutch nationwide network of 31 automatic rain gauges. The smallest aggregation interval for which raindrop size distributions were collected by the disdrometers was 30 s, while the automatic rain gauges provided 10-min rainfall sums. This study aims to supplement other micro-γ investigations (usually performed in the context of spatial rainfall variability within a weather radar pixel) with new data, while characterizing the correlation structure across an extended range of scales. To quantify the spatio-temporal variability, we employ a two-parameter exponential model fitted to the spatial correlograms and characterize the parameters of the model as a function of the temporal aggregation interval. This widely used method allows for a meaningful comparison with seven other studies across contrasting climatic settings all around the world. We also separately analyzed the intermittency of the rainfall observations. We show that a single parameterization, consisting of a two-parameter exponential spatial model as a function of interstation distance combined with a power-law model for decorrelation distance as a function of aggregation interval, can coherently describe rainfall variability (both spatial correlation and intermittency) across a wide range of scales. Limiting the range of scales to those typically found in micro-γ variability studies (including four of the seven studies to which we compare our results) skews the parameterization and reduces its applicability to larger scales.


2022 ◽  
Author(s):  
Samuel E. LeBlanc ◽  
Michal Segal-Rozenhaimer ◽  
Jens Redemann ◽  
Connor J. Flynn ◽  
Roy R. Johnson ◽  
...  

Abstract. Aerosol particles can be emitted, transported, removed, or transformed, leading to aerosol variability at scales impacting the climate (days to years and over hundreds of kilometers) or the air quality (hours to days and from meters to hundreds of kilometers). We present the temporal and spatial scales of changes in AOD (Aerosol Optical Depth), and aerosol size (using Angstrom Exponent; AE, and Fine-Mode-Fraction; FMF) over Korea during the 2016 KORUS-AQ (KORea-US Air Quality) atmospheric experiment. We use measurements and retrievals of aerosol optical properties from airborne instruments for remote sensing (4STAR; Spectrometers for Sky-Scanning Sun Tracking Atmospheric Research) and in situ (LARGE; NASA Langley Aerosol Research Group Experiment) on board the NASA DC-8, geostationary satellite (GOCI; Geostationary Ocean Color Imager; Yonsei aerosol retrieval (YAER) version 2) and reanalysis (MERRA-2; Modern-Era Retrospective Analysis for Research and Applications, version 2). Measurements from 4STAR when flying below 500 m, show an average AOD at 501 nm of 0.43 and an average AE of 1.15 with large standard deviation (0.32 and 0.26 for AOD and AE respectively) likely due to mixing of different aerosol types (fine and coarse mode). The majority of AODs due to fine mode aerosol is observed at altitudes lower than 2 km. Even though there are large variations, for 18 out of the 20 flight days, the column AOD measurements by 4STAR along the NASA DC-8 flight trajectories matches the south-Korean regional average derived from GOCI. We also observed that, contrary to prevalent understanding, AE and FMF are more spatially variable than AOD during KORUS-AQ, even when accounting for potential sampling biases by using Monte Carlo resampling. Averaging between measurements and model for the entire KORUS-AQ period, a reduction in correlation by 15 % is 65.0 km for AOD and shorter at 22.7 km for AE. While there are observational and model differences, the predominant factor influencing spatial-temporal homogeneity is the meteorological period. High spatio-temporal variability occur during the dynamic period (25–31 May), and low spatio-temporal variability occur during blocking Rex pattern (01–07 June). The changes in spatial variability scales between AOD and FMF/AE, while inter-related, indicate that microphysical processes that impact mostly the dominant aerosol size, like aerosol particle formation, growth, and coagulation, vary at shorter scales than the aerosol concentration processes that mostly impact AOD, like aerosol emission, transport, and removal.


2020 ◽  
Author(s):  
Diego Ellis-Soto ◽  
Kristy M. Ferraro ◽  
Matteo Rizzuto ◽  
Emily Briggs ◽  
Julia D. Monk ◽  
...  

Ecosystems are open systems connected through spatial flows of energy, matter, and nutrients. Predicting and managing ecosystem interdependence requires a rigorous quantitative understanding of the drivers and vectors that connect ecosystems across spatio-temporal scales. Animals act as such vectors when they transport nutrients across landscapes in the form of excreta, egesta, and their own bodies. Here, we introduce a methodological roadmap that combines movement, foraging, and ecosystem ecology to study the effects of animal-vectored nutrient transport on meta-ecosystems. The meta-ecosystem concept — the notion that ecosystems are connected in space and time by flows of energy, matter, and organisms across boundaries — provides a theoretical framework on which to base our understanding of animal-vectored nutrient transport. However, partly due to its high level of abstraction, there are few empirical tests of meta-ecosystem theory, and while we may label animals as important mediators of ecosystem services, we lack predictive inference of their relative roles and impacts on diverse ecosystems. Recently developed technologies and methods — tracking devices, mechanistic movement models, diet reconstruction techniques and remote sensing — have the potential to facilitate the quantification of animal-vectored nutrient flows and increase the predictive power of meta-ecosystem theory. Understanding the mechanisms by which animals shape ecosystem dynamics may be important for ongoing conservation, rewilding, and restoration initiatives around the world, and for more accurate models of ecosystem nutrient budgets. We provide conceptual examples that show how our proposed integration of methodologies could help investigate ecosystem impacts of animal movement. We conclude by describing practical applications to understanding cross-ecosystem contributions of animals on the move.


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