This paper presents a performance evaluation framework for streetscape vegetation. A performance index (PI) is conceived using the following seven traits, specific to the street environments - Pollution Flux Potential (PFP), Carbon Sequestration Potential (CSP), Thermal Comfort Potential (TCP), Noise Attenuation Potential (NAP), Biomass Energy Potential (BEP), Environmental Stress Tolerance (EST) and Crown Projection Factor (CPF). Its application is demonstrated through a case study using fifteen street vegetation species from the UK, utilising a combination of direct field measurements and inventoried literature data. Our results indicate greater preference to small-to-medium size trees and evergreen shrubs over larger trees for streetscaping. The proposed PI approach can be potentially applied two-fold: one, for evaluation of the performance of the existing street vegetation, facilitating the prospects for further improving them through management strategies and better species selection; two, for planning new streetscapes and multi-functional biomass as part of extending the green urban infrastructure.
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http://dx.doi.org/10.1016/j.envpol.2015.09.003 | DOI Listing |
Data Brief
June 2024
Joint Research Center, European Commission, Ispra, Italy.
Urban focused semantically segmented datasets (e.g. ADE20k or CoCo) have been crucial in boosting research and applications in urban areas by providing rich sources of delineated objects in Street View Images (SVI).
View Article and Find Full Text PDFSci Total Environ
January 2025
Occoquan Watershed Monitoring Laboratory, The Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, 9408 Prince William Street, Manassas, VA, USA.
We present the results of a 1-year study that quantified salt levels in stormwater, soils, and plant tissues from 14 stormwater detention basins across Northern VA in an above-average snow year. We characterize (1) the level of salt stress plants experience, (2) the extent to which current plant communities feature salt tolerant species, and (3) the capacity of these species to phytoremediate soils and reduce the impacts of deicer and anti-icer use. Our results suggest that detention basin vegetation experience a range of salt stress levels that depend on drainage area type (roads: moderate to high > parking lots: low to moderate > pervious areas: none).
View Article and Find Full Text PDFHeliyon
January 2025
Lithuanian University of Health Sciences, Faculty of Medicine, A.Mickeviciaus street, 9, LT-44307, Kaunas, Lithuania.
Introduction: is a formidable pathogen that poses a significant threat to immunocompromised and might cause rare atypical forms of the disease especially complicated with coinfection.
Case: We present a case of a patient with meningoencephalitis, endocarditis, sepsis, and osteomyelitis, highlighting the complexities of managing disseminated polymicrobial infection. A 64-year-old female with multiple myeloma treated with chemotherapy presented with fever, altered mental status, nausea, and diarrhea to the emergency department.
Mol Phylogenet Evol
January 2025
Autonomous University of Barcelona, Systematics and Evolution of Vascular Plants (UAB) - Associated Unit to CSIC by IBB - Cerdanyola del Vallès, Spain.
Widely distributed plant genera offer insights into biogeographic processes and biodiversity. The Carduus-Cirsium group, with over 600 species in eight genera, is diverse across the Holarctic regions, especially in the Mediterranean Basin, Southwest Asia, Japan, and North America. Despite this diversity, evolutionary and biogeographic processes within the group, particularly for the genus Cirsium, remain underexplored.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Biological and Environmental Sciences, Liverpool John Moores University, James Parsons Building, Byrom Street, Liverpool L3 3AF, UK.
Camera traps offer enormous new opportunities in ecological studies, but current automated image analysis methods often lack the contextual richness needed to support impactful conservation outcomes. Integrating vision-language models into these workflows could address this gap by providing enhanced contextual understanding and enabling advanced queries across temporal and spatial dimensions. Here, we present an integrated approach that combines deep learning-based vision and language models to improve ecological reporting using data from camera traps.
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