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  • 1
    Online Resource
    Online Resource
    Numerical predictions of shear stress and cyclic stretch in pulmonary hypertension due to left heart failure
    Springer Science and Business Media LLC ; 2022
    In:  Biomechanics and Modeling in Mechanobiology Vol. 21, No. 1 ( 2022-02), p. 363-381
    Details
    In: Biomechanics and Modeling in Mechanobiology, Springer Science and Business Media LLC, Vol. 21, No. 1 ( 2022-02), p. 363-381
    Type of Medium: Online Resource
    ISSN: 1617-7959 , 1617-7940
    URL: Article
    DOI: 10.1007/s10237-021-01538-1
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2064972-1
    SSG: 12
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  • 2
    Online Resource
    Online Resource
    40th EASD Annual Meeting of the European Association for the Study of Diabetes : Munich, Germany, 5–9 September 2004
    Springer Science and Business Media LLC ; 2004
    In:  Diabetologia Vol. 47, No. S1 ( 2004-8), p. A1-A464
    Details
    In: Diabetologia, Springer Science and Business Media LLC, Vol. 47, No. S1 ( 2004-8), p. A1-A464
    Type of Medium: Online Resource
    ISSN: 0012-186X , 1432-0428
    URL: Article
    DOI: 10.1007/BF03375463
    RVK:
    XA 40615
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2004
    detail.hit.zdb_id: 1458993-X
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  • 3
    Online Resource
    Online Resource
    Modelling the Diameter Distribution of Savanna Trees with Drone-Based LiDAR
    MDPI AG ; 2021
    In:  Remote Sensing Vol. 13, No. 7 ( 2021-03-26), p. 1266-
    Details
    In: Remote Sensing, MDPI AG, Vol. 13, No. 7 ( 2021-03-26), p. 1266-
    Abstract: The diameter distribution of savanna tree populations is a valuable indicator of savanna health because changes in the number and size of trees can signal a shift from savanna to grassland or forest. Savanna diameter distributions have traditionally been monitored with forestry techniques, where stem diameter at breast height (DBH) is measured in the field within defined sub-hectare plots. However, because the spatial scale of these plots is often misaligned with the scale of variability in tree populations, there is a need for techniques that can scale-up diameter distribution surveys. Dense point clouds collected from uncrewed aerial vehicle laser scanners (UAV-LS), also known as drone-based LiDAR (Light Detection and Ranging), can be segmented into individual tree crowns then related to stem diameter with the application of allometric scaling equations. Here, we sought to test the potential of UAV-LS tree segmentation and allometric scaling to model the diameter distributions of savanna trees. We collected both UAV-LS and field-survey data from five one-hectare savanna woodland plots in northern Australia, which were divided into two calibration and three validation plots. Within the two calibration plots, allometric scaling equations were developed by linking field-surveyed DBH to the tree metrics of manually delineated tree crowns, where the best performing model had a bias of 1.8% and the relatively high RMSE of 39.2%. A segmentation algorithm was then applied to segment individual tree crowns from UAV-LS derived point clouds, and individual tree level segmentation accuracy was assessed against the manually delineated crowns. 47% of crowns were accurately segmented within the calibration plots and 68% within the validation plots. Using the site-specific allometry, DBH was modelled from crown metrics within all five plots, and these modelled results were compared to field-surveyed diameter distributions. In all plots, there were significant differences between field-surveyed and UAV-LS modelled diameter distributions, which became similar at two of the plots when smaller trees ( 〈 10 cm DBH) were excluded. Although the modelled diameter distributions followed the overall trend of field surveys, the non-significant result demonstrates a need for the adoption of remotely detectable proxies of tree size which could replace DBH, as well as more accurate tree detection and segmentation methods for savanna ecosystems.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs13071266
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2513863-7
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  • 4
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    Leveraging TLS as a Calibration and Validation Tool for MLS and ULS Mapping of Savanna Structure and Biomass at Landscape-Scales
    MDPI AG ; 2021
    In:  Remote Sensing Vol. 13, No. 2 ( 2021-01-13), p. 257-
    Details
    In: Remote Sensing, MDPI AG, Vol. 13, No. 2 ( 2021-01-13), p. 257-
    Abstract: Savanna ecosystems are challenging to map and monitor as their vegetation is highly dynamic in space and time. Understanding the structural diversity and biomass distribution of savanna vegetation requires high-resolution measurements over large areas and at regular time intervals. These requirements cannot currently be met through field-based inventories nor spaceborne satellite remote sensing alone. UAV-based remote sensing offers potential as an intermediate scaling tool, providing acquisition flexibility and cost-effectiveness. Yet despite the increased availability of lightweight LiDAR payloads, the suitability of UAV-based LiDAR for mapping and monitoring savanna 3D vegetation structure is not well established. We mapped a 1 ha savanna plot with terrestrial-, mobile- and UAV-based laser scanning (TLS, MLS, and ULS), in conjunction with a traditional field-based inventory (n = 572 stems 〉 0.03 m). We treated the TLS dataset as the gold standard against which we evaluated the degree of complementarity and divergence of structural metrics from MLS and ULS. Sensitivity analysis showed that MLS and ULS canopy height models (CHMs) did not differ significantly from TLS-derived models at spatial resolutions greater than 2 m and 4 m respectively. Statistical comparison of the resulting point clouds showed minor over- and under-estimation of woody canopy cover by MLS and ULS, respectively. Individual stem locations and DBH measurements from the field inventory were well replicated by the TLS survey (R2 = 0.89, RMSE = 0.024 m), which estimated above-ground woody biomass to be 7% greater than field-inventory estimates (44.21 Mg ha−1 vs 41.08 Mg ha−1). Stem DBH could not be reliably estimated directly from the MLS or ULS, nor indirectly through allometric scaling with crown attributes (R2 = 0.36, RMSE = 0.075 m). MLS and ULS show strong potential for providing rapid and larger area capture of savanna vegetation structure at resolutions suitable for many ecological investigations; however, our results underscore the necessity of nesting TLS sampling within these surveys to quantify uncertainty. Complementing large area MLS and ULS surveys with TLS sampling will expand our options for the calibration and validation of multiple spaceborne LiDAR, SAR, and optical missions.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs13020257
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2513863-7
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  • 5
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    Online Resource
    Identifying Species and Monitoring Understorey from UAS-Derived Data: A Literature Review and Future Directions
    MDPI AG ; 2019
    In:  Drones Vol. 3, No. 1 ( 2019-01-08), p. 9-
    Details
    In: Drones, MDPI AG, Vol. 3, No. 1 ( 2019-01-08), p. 9-
    Abstract: Understorey vegetation plays an important role in many ecosystems, yet identifying and monitoring understorey vegetation through remote sensing has proved a challenge for researchers and land managers because understorey plants tend to be small, spatially and spectrally similar, and are often blocked by the overstorey. The emergence of Unmanned Aerial Systems (UAS) is revolutionising how vegetation is measured, and may allow us to measure understorey species where traditional remote sensing previously could not. The goal of this paper was to review current literature and assess the current capability of UAS to identify and monitor understorey vegetation. From the literature, we focused on the technical attributes that limit the ability to monitor understorey vegetation—specifically (1) spatial resolution, (2) spectral sensitivity, (3) spatial extent, and (4) temporal frequency at which a sensor acquires data. We found that UAS have provided improved levels of spatial resolution, with authors reporting successful classifications of understorey vegetation at resolutions of between 3 mm and 200 mm. Species discrimination can be achieved by targeting flights to correspond with phenological events to allow the detection of species-specific differences. We provide recommendations as to how UAS attributes can be tailored to help identify and monitor understorey species.
    Type of Medium: Online Resource
    ISSN: 2504-446X
    URL: Article
    DOI: 10.3390/drones3010009
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2934569-8
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  • 6
    Online Resource
    Online Resource
    Developing landscape-scale forest restoration targets that embrace spatial pattern
    Springer Science and Business Media LLC ; 2022
    In:  Landscape Ecology Vol. 37, No. 7 ( 2022-07), p. 1747-1760
    Details
    In: Landscape Ecology, Springer Science and Business Media LLC, Vol. 37, No. 7 ( 2022-07), p. 1747-1760
    Abstract: Forest restoration plays an important role in global efforts to slow biodiversity loss and mitigate climate change. Vegetation in remnant forests can form striking patterns that relate to ecological processes, but restoration targets tend to overlook spatial pattern. While observations of intact reference ecosystems can help to inform restoration targets, field surveys are ill-equipped to map and quantify spatial pattern at a range of scales, and new approaches are needed. Objective This review sought to explore practical options for creating landscape-scale forest restoration targets that embrace spatial pattern. Methods We assessed how hierarchy theory, satellite remote sensing, landscape pattern analysis, drone-based remote sensing and spatial point pattern analysis could be applied to assess the spatial pattern of reference landscapes and inform forest restoration targets. Results Hierarchy theory provides an intuitive framework for stratifying landscapes as nested hierarchies of sub-catchments, forest patches and stands of trees. Several publicly available tools can map patches within landscapes, and landscape pattern analysis can be applied to quantify the spatial pattern of these patches. Drones can collect point clouds and orthomosaics at the stand scale, a plethora of software can create maps of individual trees, and spatial point pattern analysis can be applied to quantify the spatial pattern of mapped trees. Conclusions This review explored several practical options for producing landscape scale forest restoration targets that embrace spatial pattern. With the decade on ecosystem restoration underway, there is a pressing need to refine and operationalise these ideas.
    Type of Medium: Online Resource
    ISSN: 0921-2973 , 1572-9761
    URL: Article
    DOI: 10.1007/s10980-022-01461-5
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2016200-5
    SSG: 12
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  • 7
    Online Resource
    Online Resource
    Reference site selection protocols for mine site ecosystem restoration
    Wiley ; 2021
    In:  Restoration Ecology Vol. 29, No. 1 ( 2021-01)
    Details
    In: Restoration Ecology, Wiley, Vol. 29, No. 1 ( 2021-01)
    Abstract: Reference site selection associated with mining and resource development requires a comprehensive approach so that stakeholders can be confident that restoration efforts have appropriate target ecosystems. Here, we present our process to select reference sites, within a savanna ecosystem, which will be used to develop and assess closure criteria and restoration guidelines for Ranger Mine (Northern Territory, Australia). The selection of reference sites followed five steps involving desktop and field methods. We recommend that restoration projects consider inclusion criteria, randomly select sites from areas matching the chosen criteria, conduct preliminary data analysis, estimate and update sampling effort and precision at several points throughout the project, and invite stakeholder feedback and revision of the process as often as required. This detailed reference site approach appears to be the first to demonstrate how to use available data to reduce bias, address sampling effort and site selection quantitatively, involve stakeholders, and provide useful data, which can be used to calibrate ecological restoration outcomes for savanna ecosystems.
    Type of Medium: Online Resource
    ISSN: 1061-2971 , 1526-100X
    URL: Issue
    URL: Article
    DOI: 10.1111/rec.v29.1
    DOI: 10.1111/rec.13278
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2020952-6
    detail.hit.zdb_id: 914746-9
    SSG: 12
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  • 8
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    Reproducibility and sensitivity of 36 methods to quantify the SARS-CoV-2 genetic signal in raw wastewater: findings from an interlaboratory methods evaluation in the U.S.
    Royal Society of Chemistry (RSC) ; 2021
    In:  Environmental Science: Water Research & Technology Vol. 7, No. 3 ( 2021), p. 504-520
    Details
    In: Environmental Science: Water Research & Technology, Royal Society of Chemistry (RSC), Vol. 7, No. 3 ( 2021), p. 504-520
    Type of Medium: Online Resource
    ISSN: 2053-1400 , 2053-1419
    URL: Article
    DOI: 10.1039/D0EW00946F
    Language: English
    Publisher: Royal Society of Chemistry (RSC)
    Publication Date: 2021
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  • 9
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    Online Resource
    Improving DPR Quantitative Microbial Risk Assessments Using Extensive New Pathogen Monitoring Datasets
    Water Environment Federation ; 2018
    In:  Proceedings of the Water Environment Federation Vol. 2018, No. 11 ( 2018-01-01), p. 3540-3540
    Details
    In: Proceedings of the Water Environment Federation, Water Environment Federation, Vol. 2018, No. 11 ( 2018-01-01), p. 3540-3540
    Type of Medium: Online Resource
    ISSN: 1938-6478
    URL: Article
    DOI: 10.2175/193864718825135595
    Language: English
    Publisher: Water Environment Federation
    Publication Date: 2018
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