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3,709 results for “urbanization.”
The accelerating loss of resilience in suburban woodlands can largely be attributed to changes in urban precipitation patterns
<p><span>Vegetation resilience holds significant importance for stabilizing ecosystem service functions in a changing climate. While global land surface vegetation resilience changes have been extensively studied, the impact of urbanization on the resilience of suburban woodlands remains inadequately understood.</span> <span>In this study, we utilized two Critical Slowing Down (CSD) indicators, namely lag-one autocorrelation (LOA) and variance (VA), to assess the vegetation resilience, its long-term trends, and influencing factors in suburban woodlands across 1,356 cities worldwide. The recovery rates estimated by LOA (r<sub>r1</sub>) and VA (r<sub>r2</sub>) showed close alignment in suburban woodlands with low suburban forest coverage (SFC) areas (correlation coefficient (r)=0.95). However, a notable divergence was observed in areas with high SFC (r=0.73). Suburban woodlands with high SFC typically exhibited lower recovery rate estimates, thus indicating greater vegetation resilience compared to areas with lower SFC. From 1986 to 2022, the recovery rates of suburban woodland areas in over 83% of the cities demonstrated a significant upward trend, with an average of 3.23×10<sup>−3</sup> yr<sup>−1</sup> for both r<sub>r1</sub> and r<sub>r2</sub>, signifying a widespread decline in vegetation resilience. The accelerating pace of urbanization led to higher rising rates of r<sub>r1</sub> and r<sub>r2</sub> during 2010-2022 (5.11×10<sup>−3</sup> yr<sup>−1</sup>) compared to 1986-1999 (0.49×10<sup>−3</sup> yr<sup>−1</sup>). The notable decrease in resilience of forestland was primarily attributed to reduced precipitation in urban suburbs, which can be explained by urbanization-induced heat island and building barrier effects, causing a shift of precipitation center from urban suburbs to central cities. In summary, this study revealed that urbanization diminishes the vegetation resilience of urban suburban woodlands by altering urban precipitation patterns. These findings underscore the necessity of augmenting water availability in urban suburbs to restore resilience in these woodlands, thereby enhancing their ecosystem service value.</span></p>
Essential Urban Land Cover Category across the Conterminous United States
<p>This dataset, titled "Essential Urban Land Cover Category across the Conterminous United States", contains high-resolution urban land cover maps for urban areas across the Conterminous United States produced in the manuscript "Large-scale High-resolution Essential Urban Land Cover Category (EULCC) Mapping Using a Semantic-Augmented and Noise-Tolerant Approach". The land cover maps are organized by city, with each city’s data stored as a separate <span>TIFF </span>file. These city-level files are grouped by state, and the dataset provided here is the compressed files of the state-level folders.</p> <p>The raster data values range from 1 to 9 in the land cover maps, representing different essential urban land cover categories as follows:</p> <table> <tbody> <tr> <td>Values</td> <td>Classes</td> </tr> <tr> <td>1</td> <td>Building</td> </tr> <tr> <td>2</td> <td>Tree</td> </tr> <tr> <td>3</td> <td>Grass/Shrub</td> </tr> <tr> <td>4</td> <td>Parking lot</td> </tr> <tr> <td>5</td> <td>Road</td> </tr> <tr> <td>6</td> <td>Water</td> </tr> <tr> <td>7</td> <td>Barren</td> </tr> <tr> <td>8</td> <td>Agriculture</td> </tr> <tr> <td>9</td> <td>Others</td> </tr> </tbody> </table> <p> </p>
Operational Dataset for Phased Array Radar Network for Natural Hazard Monitoring and Warnings in Urban Environments over the Greater Bay Area, China
<p>This is the dataset for the BAMS paper: Operational Phased Array Radar Network for Natural Hazard Monitoring and Warnings in<br>Urban Environments over the Greater Bay Area, China</p> <p>Due to policy restrictions, long-term data cannot be openly shared. Access to these data requires further arrangements through a formal agreement. For inquiries regarding data access, please contact us to discuss the terms and conditions.</p>
Wave-Cascade Nested Model: The Urban-rural Diffusion Model of Suzhou(Essays on Linguistics 2025(1))
<p>This is the high-resolution images (Figure 3) from published paper entitled Wave-Cascade Nested Model: The Urban-rural Diffusion Model of Suzhou (Essays on Linguistics 2025(1)) (in Chinese 波浪-级联嵌套模型”:苏州城乡方言的扩散模式 (《语言学论丛》2025年第1期)) . </p> <p>Given the journal doesn't provide color printing or needs to compress images due to size limitations, it offers readers access to the high-quality and full-color image.</p> <p>If you have any question, please contact me without any hesitation! Thank you very much!</p>
Urban Solar Irradiation at Ground Level for Rennes Métropole
<p>Conducting a comprehensive assessment of solar irradiation at the pedestrian scale across all ground surfaces in a city can help identify cooler routes for pedestrian navigation and prepare the city for potential overheating issues by pinpointing overexposed areas. This dataset results from an effective method for conducting such assessments within a Geographic Information System (GIS) at a metric resolution across regions, such as Rennes Métropole in France, which spans over 700 km². This method has been detailed in the article entitled "Efficient matrix algebra encoding for urban solar irradiation simulation: fine-grid ground-level estimation with vector data" (doi: <a href="https://dx.doi.org/10.1080/13658816.2024.2425339" target="_blank" rel="noopener">10.1080/13658816.2024.2425339</a>). Please note that these simulation results only account for the effects of building shading. The shading provided by trees, street furniture, or the terrain model is not considered at all.</p>
Data from: Developing and applying a macroinvertebrate‐based multimetric index for urban rivers in the Niger Delta, Nigeria
<p class="MsoCommentText">Urban pollution of riverine ecosystem is a serious concern in the Niger Delta region of Nigeria. No biomonitoring tool exists for the routine monitoring of effects of urban pollution on riverine systems within the region. Therefore, the aim of this study was to develop and apply a macroinvertebrate-based multimetric index for assessing water quality condition of impacted urban river systems in the Niger Delta area of Nigeria. Macroinvertebrate and physico-chemical samples were collected from 11 stations in eight river systems. Based on the physico-chemical variables, the stations were categorised into three impact categories namely; least impacted stations (LIS), moderately impacted stations (MIS) and heavily impacted stations (HIS). Seventy seven (77) candidate metrics were tested and only five: Hemiptera abundance, %Coleoptera+Hemiptera, %Chironomidae+Oligochaeta, Evenness index and Logarithm of relative abundance of very large body size (>40-80 mm) were retained and integrated into the final Niger Delta urban multimetric index (MINDU). The validation data set showed a correspondence of 83.3% between the index result and the physico-chemically-based classification for the LIS and a 75% correspondence for the MIS. A performance of 22.2% was recorded for the HIS. The newly developed MINDU proved useful as a biomonitoring tool in the Niger Delta region of Nigeria, and can thus be used by environmental managers and government officials for routine monitoring of rivers and streams subjected to urban pollution.</p>
SUMMER-MUSTARD (Summer season Multi-cross Urban Signalized Traffic Aggregated Region Dataset)
<p>Dataset release for ECML-PKDD 2021 paper</p> <p><em>OBELISC: Oscillator-Based Modelling and Control using Efficient Neural Learning for Road Traffic Signal Offset Calculation</em></p> <p><em>Cristian Axenie, Daniele Foroni, Alexander Wieder, Mohamad Al Hajj Hassan, Paolo Sottovia, Margherita Grossi, Rongye Shi, Stefano Bortoli, Götz Brasche</em></p> <p>SUMMER-MUSTARD (Summer season Multi-cross Urban Signalized Traffic Aggregated Region Dataset) real-world dataset, contains 59 days of real urban road traffic data from 8 crosses in a city in China.<br> </p>
Dancing bees evaluate central urban forage resources as superior to agricultural land
<p class="ColorfulList-Accent11CxSpFirst">Recent evidence suggests that flower-rich areas within cities could play an important role in pollinator conservation, but direct comparison of floral resources within agricultural and urban areas has proved challenging to perform over large scales.</p> <p class="ColorfulList-Accent11CxSpMiddle">Here we use the waggle dances of honeybees (<i>Apis mellifera</i> L.) to perform large-scale landscape surveys at heavily urban or agricultural sites for a key pollinator of wild and crop plants. We analyzed 2827 dances that were performed by 20 colonies in SE England.</p> <p class="ColorfulList-Accent11CxSpMiddle">We show that hive median foraging trip distance is consistently lower at urban sites across the entire season. The sucrose content of collected nectar did not significantly differ between urban and agricultural land, ruling out the possibility that longer foraging distances in agricultural sites were driven by distant but nectar-rich resources.</p> <p class="ColorfulList-Accent11CxSpMiddle">Within cities, bees preferentially targeted residential areas on foraging trips, while trips to mass-flowering crops overwhelmingly dominated at agricultural sites. For both land-use types, distances flown increased in the summer, but there was high variation in temporal patterns between individual sites</p> <p class="ColorfulList-Accent11CxSpLast"><i>Policy implications: </i>From the self-reported perspective of a generalist pollinator, forage was easier to find in heavily urbanized areas than in the modern agricultural landscapes that we studied. A focus on continuous spatial and temporal provision within agricultural environments is key to redressing this imbalance.</p>
Data from: Urban street lighting differentially affects community attributes of airborne and ground-dwelling invertebrate assemblages
<p><span>The introduction of artificial light at night (ALAN) into natural and urbanised landscapes is a known and highly pervasive disruptor of invertebrate communities. However, the effect of variation in intensity and spectra of ALAN on invertebrate communities inhabiting different spatial niches is little understood. Further, the remarkable ability of ALAN to continue to disrupt biodiversity even in chronically-illuminated urban landscapes is not often acknowledged. </span></p> <p><span>Here, we simultaneously sampled airborne and ground-dwelling invertebrate assemblages under and between urban streetlights to explore the effects on community composition and abundance of a) proximity to decadal (i.e long-illuminated) nocturnal street lighting and b) variation in the spectral output of light. </span></p> <p><span>The two assemblages responded differently. For airborne invertebrates, night-time abundance doubled, and night-time assemblage composition was significantly different for traps under, compared with between, streetlights. These differences in abundance were not affected by streetlight intensity, and were absent in day samples, suggesting that even weak ALAN may be causing short-term redistribution of nocturnal invertebrates. Further, the abundance (but not composition) effects of ALAN on airborne invertebrates increased when the streetlights emitted a higher proportion of short-wavelength light. </span></p> <p><span>In contrast, for ground-dwelling invertebrates, we found only marginal effects of proximity and spectrum of lighting on abundance and no effect on assemblage composition. However, more intense streetlighting reduced abundance and altered composition at traps both under and between lights. </span></p> <p><span><i>Synthesis and Applications: </i>Public lighting managers must consider ALAN impacts on invertebrate communities not only when introducing ALAN to naïve environments, but also when changing lighting in areas that are highly urbanised and exposed to decades of artificial light at night. Further, lighting proposals and environmental monitoring of invertebrate communities must take into account effects on both ground-dwelling and airborne assemblages, as these may respond very differently to the presence, intensity and spectrum of ALAN. </span></p>
Single versus repeated human trampling events: Responses of ground vegetation in sub-urban beech forests
<p>Forests provide important ecosystem services and are often the only natural areas that are freely accessible to the public for outdoor recreation. Large numbers of forest visitors can cause severe damage to forest ecosystems, which in turn can affect the ecosystem functioning. We aimed to assess whether experimental short-term and long-term trampling affect the ground vegetation in deciduous forests and its recovery to a different extent. We used a standard experimental trampling procedure to simulate single and repeated human trampling events of different intensity. Experimental trampling of different intensity was conducted on a single day (single trampling) or on five days at intervals of four weeks (repeated trampling) in three suburban beech forests on different soil types. We recorded the cover, height, species density and species composition of the ground vegetation in the trampling lanes. We also assessed the recovery of the ground vegetation one and two years after trampling.</p> <p>Trampling intensity and the type of trampling (single vs. repeated) affected the ground vegetation in the three forests. Vegetation cover, plant height and species density all decreased with increasing trampling intensity, but to a different extent in the three forests. Most vegetation characteristics were more severely affected by repeated trampling than single trampling of equal intensity. A longer trampling period strengthened the effects of trampling on ground vegetation, except in one forest. Two years after experimental trampling, most vegetation characteristics still differed from those of undisturbed ground vegetation</p>
Comparison among three different Digital Surface Models and their respective hydraulic outcomes in the flood-prone urban area of Navaluenga (Ávila, Spain)
<p>Three different Digital Surface Models (DSMs) generated from LiDAR data are presented. The LiDAR information has been considered as raw data (DSM3) and subjected to some transformations to better represent the urban environment (DSM1). DSM2 is an intermediate state between DSM1 and DSM3. </p> <p>On the other hand, a hydraulic model has been run for each DSM and for two return periods (25 and 500 years), obtaining in all cases the graphical outputs of depths, velocities, Froude numbers and hazard. </p> <p>The different DSMs are named DSM1, DSM2 and DSM3, which can be downloaded in TIN format. The hydraulic outputs associated with the different DSMs can be downloaded in raster format and are named as follows: the Digital Surface Model to which it refers, the return period considered and the type of hydraulic output (depth, velocity, Froude number and hazard).</p> <p>DSM1: Digital Surface Model 1 (TIN format).<br> dsm1_25depth: Depths obtained by considering the DSM1 and the flow associated with the 25-years return period (raster format).<br> dsm1_25froud: Froude numbers obtained by considering the DSM1 and the flow associated with the 25-years return period (raster format).<br> dsm1_25haz: Hazard obtained by considering the DSM1 and the flow associated with the 25-years return period (raster format).<br> dsm1_25veloc: Velocities obtained by considering the DSM1 and the flow associated with the 25-years return period (raster format). <br> dsm1_500depth: Depths obtained when considering the DSM1 and the flow associated with the 500-years return period (raster format).<br> dsm1_500froud: Froude numbers obtained by considering the DSM1 and the flow associated with the 500-years return period (raster format).<br> dsm1_500haz: Hazard obtained by considering the DSM1 and the flow associated with the 500-years return period (raster format).<br> dsm1_500veloc: Velocities obtained by considering the DSM1 and the flow associated with the 500-years return period (raster format).</p> <p>DSM2: Digital Surface Model 2 (TIN format).<br> dsm2_25depth: Depths obtained by considering the DSM2 and the flow associated with the 25-years return period (raster format).<br> dsm2_25froud: Froude numbers obtained by considering the DSM2 and the flow associated with the 25-years return period (raster format).<br> dsm2_25haz: Hazard obtained by considering the DSM2 and the flow associated with the 25-years return period (raster format).<br> dsm2_25veloc: Velocities obtained by considering the DSM2 and the flow associated with the 25-years return period (raster format). <br> dsm2_500depth: Depths obtained by considering the DSM2 and the flow associated with the 500-years return period (raster format).<br> dsm2_500froud: Froude numbers obtained by considering the DSM2 and the flow associated with the 500-years return period (raster format).<br> dsm2_500haz: Hazard obtained by considering the DSM2 and the flow associated with the 500-years return period (raster format).<br> dsm2_500veloc: Velocities obtained by considering the DSM2 and the flow associated with the 500-years return period (raster format).</p> <p>DSM3: Digital Surface Model 2 (TIN format).<br> dsm3_25depth: Depths obtained by considering the DSM3 and the flow associated with the 25-years return period (raster format).<br> dsm3_25froud: Froude numbers obtained by considering the DSM3 and the flow associated with the 25-years return period (raster format).<br> dsm3_25haz: Hazard obtained by considering the DSM3 and the flow associated with the 25-years return period (raster format).<br> dsm3_25veloc: Velocities obtained by considering the DSM3 and the flow associated with the 25-years return period (raster format). <br> dsm3_500depth: Depths obtained by considering the DSM3 and the flow associated with the 500-years return period (raster format).<br> dsm3_500froud: Froude numbers obtained by considering the DSM3 and the flow associated with the 500-years return period (raster format).<br> dsm3_500haz: Hazard obtained by considering the DSM3 and the flow associated with the 500-years return period (raster format).<br> dsm3_500veloc: Velocities obtained by considering the DSM3 and the flow associated with the 500-years return period (raster format).</p>
Comparing the Influence of Global Warming and Urban Anthropogenic Heat on Extreme Precipitation in Urbanized Pearl River Delta Area Based on WRF Dynamical Downscaling
<p>The simulation outputs from the Weather Research and Forecasting (WRF) v3.8.1 coupled with single layer urban canopy model from three experiments (HIST_AH300, HIST_AH0, and RCP85_AH300).</p> <p>Variables include hourly precipitation, wind, specific humidity, relative humidity, convective available potential energy, convective inhibition, temperature, model height, land use land cover, and topography.</p> <p> </p>
Deprived Urban Areas in Nairobi
<p>Code and main results of the analysis in the deprived urban areas of Nairobi, Kenya through Earth Observation and machine learning techniques.</p>
Figure 1 in Anuran species in a remnant of the Atlantic rainforest in an urban area
Figure 1. Map of the study location in the state of Espírito Santo, southeastern Brazil. In detail, Vitória municipality with delimitations of Parque Estadual da Fonte Grande (yellow contour).
Figure 2 in Anuran species in a remnant of the Atlantic rainforest in an urban area
Figure 2. Species rarefaction curve of the anuran recorded at Parque Estadual da Fonte Grande, municipality of Vitória, state of Espírito Santo, southeastern Brazil. Vertical bars indicate the upper and lower limits of the confidence interval (95%).
Fig. 1 in Low Genetic Variability In The Recovering Urban Banded Leaf Monkey Population Of Singapore
Fig. 1. Distribution of Presbytis femoralis.
Assessing Urban Green Space Accessibility in Amsterdam
<p>This is dataset is an ArcGIS Pro project was used to calculate walking distance from buildings to Urban Green Spaces (UGS) within the municipality of Amsterdam. This was made as part of an MSc Earth Sciences thesis aimed at assessing UGS and heat exposure in Amsterdam. The thesis is based on the idea that UGS function as cool spaces within the urban heat island of the city, and thus provides lower temperatures to urban residents, specifically during hot summer months, therefore reducing the risk of heat stress and heat-related illnesses and morbidity.</p>
Urbanization extends flight phenology and leads to local adaptation of seasonal plasticity in Lepidoptera
<p>Urbanization is globally gaining force and challenges biodiversity but has recently also emerged as an agent of evolutionary change. Seasonal phenology and life-cycle regulation are essential processes that urbanization is likely to alter through both the urban-heat-island effect (UHI) and artificial-light-at-night (ALAN). However, how UHI and ALAN affect the evolution of seasonal adaptations has received little attention. Here, we test for urban evolution of seasonal life-history plasticity, specifically changes in the photoperiodic induction of diapause in two lepidopterans, <i>Pieris napi </i>(Pieridae) and <i>Chiasmia clathrata</i> (Geometridae). We used long-term data from standardized monitoring and citizen science observation schemes to compare yearly phenological flight curves in six cities in Finland and Sweden to those of adjacent rural populations. This analysis showed for both species that flight seasons are longer and end later in most cities, suggesting a difference in timing of diapause induction. Then, we used common-garden experiments to test whether evolution of the photoperiodic reaction norm for diapause could explain these phenological changes for a subset of these cities. These experiments demonstrated a genetic shift for both species in urban areas towards a lower daylength threshold for direct development, consistent with predictions based on the UHI but not ALAN. The correspondence of this genetic change to the results of our larger-scale observational analysis of <i>in situ</i> flight phenology indicates that it may be widespread. These findings suggest that seasonal life-cycle regulation evolves in urban ectotherms and may contribute to eco-evolutionary dynamics in cities.</p>
Figure 1 in Diversity and abundance of Phytoseiidae (Acari: Mesostigmata) on horse chestnut (Aesculus hippocastanum L.) in an urban environment: a comparison between Greece and the Czech Republic
Figure 1 Species composition of Phytoseiidae onAesculus hippocastanumin České Budějovice (left)
Dataset for Examining the Antimicrobial Efficacy of Granulated Tetraacetylethylenediamine (TAED) Derived Peracetic Acid and Commercial Peracetic Acid in Urban Wastewaters
<p>The dataset used to generate figures in the manuscript, <em>Examining the Antimicrobial Efficacy of Granulated Tetraacetylethylenediamine (TAED) Derived Peracetic Acid and Commercial Peracetic Acid in Urban Wastewaters,</em><strong> </strong>submitted to Water Environment Research for publication. </p>
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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.