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135 results for “Urban Model”
A GDM-GTWR Coupled Model for Spatiotemporal Heteroge-neity Quantification of CO2 Emissions: A case of the Yangtze River Delta Urban Agglomeration from 2000 to 2017
<p>The compressed package contains some pictures and data on the paper.</p>
Supplementary material 3 from: Wübbelmann T, Bouwer LM, Förster K, Bender S, Burkhard B (2022) Urban ecosystems and heavy rainfall – A Flood Regulating Ecosystem Service modelling approach for extreme events on the local scale. One Ecosystem 7: e87458. https://doi.org/10.3897/oneeco.7.e87458
Maps of the individual potential FRES demand indicators
Supplementary material 2 from: Wübbelmann T, Bouwer LM, Förster K, Bender S, Burkhard B (2022) Urban ecosystems and heavy rainfall – A Flood Regulating Ecosystem Service modelling approach for extreme events on the local scale. One Ecosystem 7: e87458. https://doi.org/10.3897/oneeco.7.e87458
Table of the scaled Flood Regulating Ecosystem Services indicators and categories
Supplementary material 1 from: Wübbelmann T, Bouwer LM, Förster K, Bender S, Burkhard B (2022) Urban ecosystems and heavy rainfall – A Flood Regulating Ecosystem Service modelling approach for extreme events on the local scale. One Ecosystem 7: e87458. https://doi.org/10.3897/oneeco.7.e87458
Ratio of FRES supply and flood hazard
Data from: A game-theoretical model of kleptoparasitic behaviour in an urban gull (Laridae) population.
Kleptoparasitism (food stealing) is a significant behaviour for animals that forage in social groups as it permits some individuals to obtain resources whilst avoiding the costs of searching for their own food. Evolutionary game theory has been used to model kleptoparasitism, with a series of differential equation based compartmental models providing significant theoretical insights into behaviour in kleptoparasitic populations. In this paper we apply this compartmental modelling approach to kleptoparasitic behaviour in a real foraging population of urban gulls (Laridae). Field data was collected on kleptoparasitism and a model developed that incorporated the same kleptoparasitic and defensive strategies available to the study population. Two analyses were conducted: 1. An assessment of whether the density of each behaviour in the population was at an equilibrium. 2. An investigation of whether individual foragers were using Evolutionarily Stable Strategies (ESS) in the correct environmental conditions. The results showed the density of different behaviours in the population could be at an equilibrium at plausible values for handling time and fight duration. Individual foragers used aggressive kleptoparasitic strategies effectively in the correct environmental conditions but some individuals in those same conditions failed to defend food items. This was attributed to the population being composed of three species that differed in competitive ability. These competitive differences influenced the strategies that individuals were able to use. Rather than gulls making poor behavioural decisions these results suggest a more complex three-species model is required to describe the behaviour of this population.
Supplementary material 1 from: Nunes P, Robinet C, Branco M, Franco JC (2023) Modelling the invasion dynamics of the African citrus psyllid: The role of human-mediated dispersal and urban and peri-urban citrus trees. In: Jactel H, Orazio C, Robinet C, Douma JC, Santini A, Battisti A, Branco M, Seehausen L, Kenis M (Eds) Conceptual and technical innovations to better manage invasions of alien pests and pathogens in forests. NeoBiota 84: 369-396. https://doi.org/10.3897/neobiota.84.91540
Supplementary tables
Model simulations utilizing the latest urban underlying surface and anthropogenic heat data
<p>Based on numerical simulations utilizing the latest urban underlying surface and anthropogenic heat data over the Yangtze River Delta urban agglomeration, we find that LU change and AH emission can result in opposite effects on summer precipitation. The related model simulations are included in this dataset.</p>
Datasets for Gong Modeling walking accessibility to urban parks in Hong Kong
<p>Datasets (ArcMap format) for Gong Modeling walking accessibility to urban parks in Hong Kong</p>
The Electric Vehicle Travelling Salesman Problem on Digital Elevation Models for Traffic-Aware Urban Logistics Supplementary Material
<p>These files correspond to the supplementary material of the article <em>The Electric Vehicle Travelling Salesman Problem on Digital Elevation Models for Traffic-Aware Urban Logistics</em>. </p> <p><strong>Code</strong></p> <ul> <li><strong>algorithm.py</strong> corresponds to an implementation of the algorithm developed in the paper to solve the EV-TSP for the city of Madrid. It takes as input a list of nodes from the graph of Madrid city <strong>madrid_elevation_energy.pckl</strong> and the output consists of an ordered list of all the nodes representing the solution to the TSP.</li> <li><strong>bellmanFord.py</strong> is a Python implementation of the Bellman-Ford algorithm. </li> <li><strong>evaluation.py</strong> is the script that offers the evaluation of the algorithm offered in Tables 1 and 2 in the paper.</li> <li><strong>neuralNetworkTraining.py</strong> is the script used to train and save the Neural Network model using the data generated by <strong>simulation.py</strong>.</li> <li><strong>nn_model_predictor.py</strong> is a script where the model trained in <strong>neuralNetworkTraining.py</strong> can be used to generate predictions.</li> <li><strong>simulation.py</strong> is the script that simulated the routes through the months of October and November 2022 using the data in <strong>snapshots_2022.zip</strong>. It generates the routes in <strong>simulationOctober.csv</strong> and <strong>simulationNovember.csv</strong></li> <li><strong>twoOptNearestNeighnors.py</strong> is a Pyhton implementation of the 2-Opt algorithm that uses Nearest Neighbors to generate the initial tour.</li> </ul> <p><strong>Files</strong></p> <ul> <li><strong>Madrid{5,10,15}.pkl</strong> are the test instances for the city of Madrid. Correspond to Python list of list. Each list is a set of stops to visit in the city graph of Madrid (<strong>madrid_elevation_energy.pckl</strong>) </li> <li><strong>energy_estimation_full.h5</strong> is a Keras model trained using <strong>nn_model_predictor.py</strong> to estimate the energy.</li> <li><strong>scaler_full.pkl</strong> is the scaler needed to use the <strong>energy_estimation_full.h5</strong> model.</li> <li><strong>simulation{October, November}.pkl</strong> are the routes generated for each month using <strong>simulation.py</strong>.</li> <li><strong>snapshots_2022.zip</strong> are the traffic data for the months of October and November 2022</li> </ul>
Data from: A model to identify urban traffic congestion hotspots in complex networks
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Caterpillar survival in the city: Attack rates on model lepidopteran larvae along an urban-rural gradient show no increase in predation with increasing urban intensity (Raw Data)
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Data from: A game-theoretical model of kleptoparasitic behaviour in an urban gull (Laridae) population.
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Data from: A model of urban scaling laws based on distance dependent interactions
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Urbanization mediates the effects of water quality and climate on a model aerial insectivorous bird
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Skin response to urban pollution in an ex vivo model
GEO Series GSE126440. Homo sapiens. 33 samples. Type: Expression profiling by array.
A hybrid model for fast and probabilistic urban pluvial flood prediction - dataset
<p>A hybrid model for fast and probabilistic urban pluvial flood prediction - dataset </p> <p>This dataset presents the data used in the paper "A hybrid model for fast and probabilistic urban pluvial flood prediction". Data used to build, calibrate and evaluate the model and data that support the findings of the study are given for two cases, namely Gent and Antwerp. </p> <p>Under the folder of each case, one could find the following content:</p> <ul> <li>Model building: Data used to build the model topology. It includes geo-data of the 1D sewer network, boundary conditions of the catchment and spatial rainfall configurations </li> <li>Calibration: Rainfall data and flood records data used for calibration of the model.</li> <li>Results and evaluation: Rainfall events used for evaluation, flood probability predicted by the hybrid models and flood records used for comparing with the hybrid models. </li> </ul>
Data from: A worldwide model for boundaries of urban settlements
The shape of urban settlements plays a fundamental role in their sustainable planning. Properly defining the boundaries of cities is challenging and remains an open problem in the science of cities. Here, we propose a worldwide model to define urban settlements beyond their administrative boundaries through a bottom-up approach that takes into account geographical biases intrinsically associated with most societies around the world, and reflected in their different regional growing dynamics. The generality of the model allows one to study the scaling laws of cities at all geographical levels: countries, continents and the entire world. Our definition of cities is robust and holds to one of the most famous results in social sciences: Zipf's law. According to our results, the largest cities in the world are not in line with what was recently reported by the United Nations. For example, we find that the largest city in the world is an agglomeration of several small settlements close to each other, connecting three large settlements: Alexandria, Cairo and Luxor. Our definition of cities opens the doors to the study of the economy of cities in a systematic way independently of arbitrary definitions that employ administrative boundaries.
Interpretable Deep Convolutional Neural Network-based Surrogates for Complex Urban Hydrodynamic Modeling using Random Chaotic Rainfall
<p>This data is part of the article "Interpretable Deep Convolutional Neural Network-based Surrogates for Complex Urban Hydrodynamic Modeling using. Random Chaotic Rainfall "data for model training and validation, as well as a dynamic runoff range generated by DHMUrban</p>
Datasets used in: Modelling eye-level visibility of urban green space: Optimising city-wide point-based viewshed computations through prototyping
<p>Research data supporting our publication. Full workflows using the R programming language have been provided on <a href="https://github.com/STBrinkmann/protoVS">GitHub</a>. Here we provide external data that has been used for our research, as well as the resulting Viewshed Greenness Visibility Index (VGVI) raster.</p> <p><strong>Datasets</strong></p> <p>Digital Terrain Model (DTM):</p> <ul> <li>Spatial Resolution: 1 m</li> <li>Source: Canada’s Open Government Portal</li> <li>Licence: <a href="https://open.canada.ca/en/open-government-licence-canada">Open Government Licence - Canada</a></li> <li>File name: Vancouver_DTM_1m.tif<br> </li> </ul> <p>Digital Surface Model (DSM):</p> <ul> <li>Spatial Resolution: 1 m</li> <li>Source: Canada’s Open Government Portal</li> <li>Licence: <a href="https://open.canada.ca/en/open-government-licence-canada">Open Government Licence - Canada</a></li> <li>File name: Vancouver_DSM_1m.tif<br> </li> </ul> <p>Landuse</p> <ul> <li>Spatial Resolution: 2 m</li> <li>Source: Land Cover Classification 2014 - 2m LiDAR</li> <li>Licence: <a href="http://www.metrovancouver.org/data">Metro Vancouver</a></li> <li>File name: Vancouver_LULC_2m.tif<br> </li> </ul> <p>VGVI map</p> <ul> <li>Spatial Resolution: 5 m</li> <li>Source: Resulting dataset from our analysis</li> <li>Licence: MIT License</li> <li>File name: vgvi_van.tif</li> </ul>
Data from: Hierarchical multi-taxa models inform riparian vs. hydrologic restoration of urban streams in a permeable landscape
The degradation of streams caused by urbanization tends to follow predictable patterns; however, there is a growing appreciation for heterogeneity in stream response to urbanization due to the local geoclimatic context. Furthermore, there is building evidence that streams in mildly sloped, permeable landscapes respond uncharacteristically to urban stress calling for a more nuanced approach to restoration. We evaluated the relative influence of local-scale riparian characteristics and catchment-scale imperviousness on the macroinvertebrate assemblages of streams in the flat, permeable urban landscape of Perth, Western Australia. Using a hierarchical multi-taxa model, we predicted the outcomes of stylized stream restoration strategies to increase the riparian integrity at the local scale or decrease the influences of imperviousness at the catchment scale. In the urban streams of Perth, we show that local-scale riparian restoration can influence the structure of macroinvertebrate assemblages to a greater degree than managing the influences of catchment-scale imperviousness. We also observed an interaction between the effect of riparian integrity and imperviousness such that the effect of increased riparian integrity was enhanced at lower levels of catchment imperviousness. This study represents one of few conducted in flat, permeable landscapes and the first aimed at informing urban stream restoration in Perth, adding to the growing appreciation for heterogeneity of the Urban Stream Syndrome and its importance for urban stream restoration.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.