Search Results (27,266)

Perfectionism is multidimensional, yet it remains unclear whether evaluative self-criticism and high personal standards differentially identify adolescents with unfavorable depressive symptom profiles. Using data from a baseline sample of 1150 adolescents aged 14 to 19 years and six monthly follow-up assessments, a three-class quadratic growth mixture model identified low-stable, high-decreasing, and increasing/high-escalating profiles among 1129 trajectory-eligible participants. Three-Step Approach(R3STEP) models entered self-critical perfectionism, personal standards perfectionism, age, sex, rural/urban source, and highest parental education simultaneously; a sensitivity model additionally included baseline depressive symptoms. Self-critical perfectionism was associated with both non-low-stable profiles and remained significant after baseline symptom adjustment, although estimates were attenuated. Personal standards perfectionism showed no consistent association. Direct coefficient contrasts indicated stronger self-critical than personal-standards effects for both non-low-stable profiles in the primary model, but these between-predictor differences were no longer significant after baseline Center for Epidemiologic Studies Depression Scale (CES-D) adjustment. A targeted sensitivity analysis excluding parental education as a covariate yielded the same substantive pattern for self-critical perfectionism. The findings provide a person-centered extension of multidimensional perfectionism-depression research while also indicating that the two Child and Adolescent Perfectionism Scale(DPSCA) subscales showed only modest internal consistency and imperfect absolute factorial fit in this sample. Full article

Automated manhole cover detection, a key task in urban infrastructure inspection, is hindered by modality-specific limitations: conventional monocular image-based detectors do not directly quantify cover-to-road elevation differences, LiDAR-based methods suffer from sparse sampling that limits recall for small, distant targets, and existing fusion approaches suffer from cross-modal spatial misalignment and lack 3D defect quantification. This paper proposes SDFA-Net, an end-to-end fisheye image and LiDAR point cloud fusion framework for manhole cover detection and diagnosis in wearable mobile mapping scenarios. The semi-dense depth-supervised view transformation (SDS-VT) module constructs semi-dense depth ground truth from multi-frame accumulated point clouds to explicitly supervise image-to-bird’s-eye-view (BEV) feature projection, addressing cross-modal spatial registration under wide-angle fisheye distortion. The fidelity-adaptive fusion (FA-Fusion) module builds a physical fidelity map by combining point-cloud projection density with depth-prediction entropy, then performs quality-aware adaptive fusion via cascaded channel-spatial attention. The geometry-aware decoupled detection head (Geo-Head) adopts an anchor-free decoupled architecture to jointly predict 2D localization, physical dimensions, and millimeter-level relative elevation in a single forward pass. A multimodal dataset of 3500 spatiotemporally aligned frames is constructed using the NavVis VLX wearable platform, covering five defect categories, with Random Sample Consensus (RANSAC)-derived relative-elevation reference labels independently validated by digital leveling. Experiments show that SDFA-Net achieves 92.9% mAP@0.5 and 63.5% mAP@0.5:0.95 with 18.5 M parameters, improving over the best single-modal baseline by 4.6, 11.0, and 8.7 percentage points in mAP@0.5, mAP@0.5:0.95, and Recall, respectively. Compared with BEVFusion, SDFA-Net achieves higher detection accuracy while maintaining a smaller overall model size and an inference speed of 35 FPS. Full article

City-level indicators are difficult to ground across heterogeneous statistical systems in the Global South, where large language model (LLM) agents accelerate multilingual source discovery but risk unsupported values and fabricated execution reports. We present TerriScan, a doctrine-governed multi-agent system built while producing a 142-indicator matrix for ten emerging centralities in eight countries. A versioned charter separates production, model review, deterministic validation and non-delegable human decisions. We evaluate it as a four-month longitudinal design case study with one instrumented four-day period; its lot evidence is stratified, and six lots required substantive interception. During 15–19 July 2026, eight defect classes were registered, each with an identifiable corrective and no recorded intra-class recurrence; exposure denominators were published where countable; and seven earlier qualifying corrections predating the register are reported. The arbiter origin recurred across classes; the exhaustive hash-resolution control remained planned. No unsupported value detected by recorded controls remained in the engraved matrix. The system stopped when work required unrecorded human decisions, but our audit found its absence rule unenforced—181 of 210 absence-state cells named no consulted source. We claim no minimal or universal architecture, but show how incident records, deterministic controls and decision boundaries make urban data production auditable and capable of principled refusal. Full article

The urban heat island (UHI) effect has become a persistent climate-related challenge affecting sustainable urban development, with consequences for public health, thermal comfort, energy demand, and climate adaptation. Numerous studies have investigated UHI using diverse observational, modeling, and analytical approaches. However, existing approaches remain fragmented and lack standardized integrated assessment frameworks. This study aims to synthesize the contemporary methodologies in UHI assessment and provide an integrated framework that supports sustainable urban heat mitigation and decision-making. A PRISMA-inspired systematic review was conducted using Web of Science (WoS) and considered peer-reviewed English-language articles published between 2016 and 2026. In line with the predefined inclusion and exclusion criteria, studies were screened and classified into several methodological domains: urban characterization, microclimate monitoring, urban environmental indicators, spatial analysis, statistical modeling, cooling interventions, and sustainable assessment. Based on the synthesized evidence, a proposed integrated methodological framework was developed, providing a comprehensive foundation for researchers, urban planners, and decision-makers to design standardized UHI studies and support climate-resilient and sustainable urban development. Full article

Context-aware building massing is an important early-stage design task: given a site for buildings, a generated massing should not only fit the target parcel, but also relate to the scale, density, and morphology of its surrounding urban fabric. This task is naturally multimodal, since the target output should remain structured and editable, while the surrounding context, including other buildings or roads, can be represented as vector geometry, map imagery, or three-dimensional views. In this paper, we study contextual massing generation using vision-language models (VLMs) and analyze their performance on this task across different context modalities during training and inference.We assemble an experimental dataset of 12,845 Melbourne massings with parcel contours, structured 3D geometry, neighboring buildings, top-down views, and multi-view 3D context images. We also introduce a learned contextual relevance metric for evaluating whether generated massings are morphologically compatible with their surrounding context. Using Qwen3-VL models, we compare no-context, unimodal-context, and multimodal-context training regimes and evaluate inference performance under controlled combinations of modalities and amounts of context. The results show that model size strongly affects generation quality, multimodal training improves the use of individual modalities, and multimodal inference provides a stronger contextual signal than isolated context inputs. Full article

Despite growing attention to inland water-stressed basins, few investigations have explicitly linked urbanization water resource coupling assessments to the SDG 6 and SDG 11 targets in water-scarce coastal urban agglomerations. Achieving the United Nations Sustainable Development Goals (SDGs)—particularly SDG 6 (Clean Water and Sanitation) and SDG 11 (Sustainable Cities and Communities)—depends critically on sustainable water management in rapidly urbanizing coastal regions. This study examines the dynamic coupling and coordination between urbanization and water resources in the Minnan Delta Region (Xiamen, Quanzhou, and Zhangzhou). We constructed an integrated evaluation index system comprising 16 indicators across urbanization (population, economic, social, and spatial dimensions) and water resources (resource level, utilization efficiency, and conservation) subsystems. Using the entropy weight method and a coupling coordination degree model, we analyzed spatiotemporal evolution patterns from 2014 to 2024. Additionally, the geographical detector model was applied to quantitatively identify the drivers of coupling coordination differentiation. The results reveal that: (1) the comprehensive urbanization index exhibited a sustained upward trajectory, with subsystem importance ranking as economic urbanization > social urbanization > spatial urbanization > population urbanization; (2) the water resources comprehensive index followed a fluctuating yet generally rising pattern, with subsystem contributions ordered as water conservation > water utilization > water resource level; (3) the coupling coordination degree (D) rose from 0.2008 in 2014 to 0.4173 in 2024; and (4) pronounced spatial heterogeneity remained evident, with Quanzhou achieving primary coordination (0.6033), Xiamen reaching barely coordinated status (0.5149), and Zhangzhou remaining on the verge of imbalance (0.4764) by 2024. These findings underscore that sustainable urbanization in water-stressed coastal regions hinges on governance intensity and targeted infrastructure investment rather than on natural water abundance, thereby offering actionable pathways for SDG 6 and SDG 11 localization in similar global contexts, though persistent spatial inequalities necessitate differentiated, city-specific strategies and enhanced inter-city collaborative mechanisms. Full article

Deterministic propagation prediction faces a fundamental trade-off: the image method is exact but single-mechanism, while the shooting and bouncing ray method is flexible yet suffers from path omissions due to discrete sampling. This paper proposes the hybrid forward–backward ray tube propagation model (HFB-RTPM), which decouples the exhaustive forward construction of a ray tube tree from the backward path screening at the receiver, handling reflection, refraction, diffraction, and diffuse scattering within a unified framework. A quasi-3D extension and a dual-lobe diffuse scattering model are further introduced. Simulations show 99.8% reflection path completeness (RMSE 0.05 dB) and 100% diffraction completeness under all conditions. With diffuse scattering, the mmWave NLoS RMSE drops from 23.9/16.2 dB to 6.9/6.8 dB at 28/73 GHz, with a single model configuration valid across both frequency bands. In field measurements at 2.3–5.9 GHz across dense urban blocks, the simulation-to-measurement RMSE ranges from 5.6 to 8.5 dB. For large-scale coverage, HFB-RTPM is two orders of magnitude faster than the image method. The proposed method achieves accuracy, efficiency, and physical completeness for deterministic multipath prediction in 6G wireless networks. Full article

Mineral resource-based cities face long-term conflicts among resource exploitation, urban expansion, and ecological conservation, making it necessary to clarify how long-term land-use change affects ecosystem services and ecological security patterns. Taking Chenzhou, China, as a case study, this study analyzed land-use change from 1990 to 2024 and quantified four ecosystem services—water yield, carbon storage, habitat quality, and soil conservation—using the InVEST model. Ecological sources were identified based on an integrated ecosystem service index, while ecological corridors, ecological pinch points, and ecological barrier points were identified by integrating an ecological resistance surface, least-cost path analysis, and circuit theory. On this basis, an ecological restoration spatial pattern was delineated. The results showed that land-use change in Chenzhou was mainly characterized by stage-specific transitions between cropland and forest land and the continuous expansion of impervious surfaces. The integrated ecosystem service index generally declined before gradually stabilizing and recovering, with high-value areas concentrated in the mountainous forest regions of eastern, southern, and southwestern Chenzhou. Forest restoration improved ecosystem services, whereas the conversion of ecological land to impervious surfaces caused pronounced losses of ecological functions. The regional ecological network remained relatively stable overall, while ecological sources, corridors, pinch points, and barrier points of different levels exhibited clear spatial differentiation and differences in relative importance. Based on these characteristics, an ecological restoration spatial pattern was developed, comprising the Luoxiao and Nanling mountain ecological barriers, major ecological corridors, the Dongjiang Lake core ecological source, three ecological restoration zones, and priority ecological restoration nodes. The results indicate that integrating long-term land-use change, ecosystem services, and ecological network analysis can help identify key ecological security spaces and priority areas for ecological restoration, providing a spatial basis for differentiated ecological conservation and restoration in Chenzhou and a reference for mineral resource-based cities with similar development backgrounds. Full article

Conventional Sigmoid-based path generation for autonomous vehicles suffers from inherent central symmetry and limited curvature tunability, which restricts its adaptability to asymmetric driving scenarios and complex boundary matching requirements. On the control side, traditional preview control architectures, predominantly relying on single-point or fixed integer-order weighting strategies, fail to fully capture the continuous trend of the path ahead, and face an inherent trade-off among tracking accuracy, response speed, and ride comfort. To address these limitations, this paper proposes a systematic fractional-order framework covering both reference path generation and lateral trajectory tracking. First, a generalized Sigmoid path function is constructed by replacing the exponential term in the standard Sigmoid form with the two-parameter Mittag–Leffler function. Two independent parameters $\alpha$ and $\beta$ are introduced to realize continuous tuning of path smoothness, morphological asymmetry, heading angle distribution, and curvature profile. Second, an fractional-order accumulation preview tracking controller (FOA-PTC) is designed for vehicle lateral dynamics. By weighting lateral errors at multiple preview positions with fractional-order coefficients, the controller achieves nonlocal spatial fusion of preview information without introducing additional temporal states, and the fractional order $\nu$ enables continuous balancing between far-field trend anticipation and near-field tracking precision. Simulations are carried out based on a nonlinear two-degree-of-freedom vehicle model with the Pacejka Magic Formula tire model, covering both gentle urban lane-change scenarios and sharp low-speed obstacle-avoidance scenarios. Comparative evaluations against five representative baseline control schemes—single-point preview, equal-weight multipoint, linear weighting, exponential weighting, and Gaussian weighting—demonstrate that the proposed FOA-PTC consistently achieves the optimal comprehensive performance in both scenarios. For the sharp-curvature generalized Sigmoid path, it reduces the maximum lateral tracking error by 42.1% (from 0.337 m to 0.195 m) and the root-mean-square error (RMSE) by 54.0% (from 0.176 m to 0.081 m) compared with the single-point preview baseline. For the gentle-curvature lane-change scenario, the corresponding reduction rates are 59.0% and 46.7%, respectively. Further simulation-based validation indicates that the proposed method achieves better robustness performance than baseline controllers within the tested parameter range, and shows acceptable computational overhead for potential embedded deployment. The proposed framework improves the geometric flexibility of path planning and the tracking performance of lateral control, providing a tunable framework with potential for autonomous navigation in complex driving scenarios. Full article

The opioid epidemic continues to be a major public health crisis in the United States, and nalmefene has recently emerged as an alternative opioid overdose reversal agent. However, little is known about pharmacists’ awareness and beliefs regarding nalmefene use and distribution. Therefore, the purpose of this study was to assess Alabama pharmacists’ knowledge, perceptions, and behavioral intentions related to nalmefene. This study used a cross-sectional survey design. Practicing pharmacists in the state of Alabama were eligible to participate, and were recruited through the Alabama Board of Pharmacy email listserv. An anonymous online survey was distributed via email, and respondents were eligible to enter a lottery for one of five $100 electronic gift cards. The survey instrument was developed by the investigators, adapted from prior overdose reversal literature and informed by the Theory of Planned Behavior. Primary outcome measures included: knowledge of nalmefene (12 items); perceived barriers regarding nalmefene stocking and recommendations (19 items); and Theory of Planned Behavior concepts including attitudes (15 items), subjective norms (perceived social support) (six items), perceived behavioral control (confidence in ability to stock or recommend nalmefene) (11 items), and behavioral intentions surrounding nalmefene stocking and recommendations (13 items). Outcomes were measured via multiple-choice (objective knowledge) and Likert-type scale (1 = strongly disagree, 5 = strongly agree) questions. Differences in mean scale scores across pharmacy setting (pharmacists employed in inpatient versus outpatient settings), community pharmacy type (chain vs. independent), and geographic location (rural vs. urban) were analyzed using two-sided Mann–Whitney U tests for non-parametric data or t-tests for parametric data, as appropriate. Multiple linear regression analyses examined associations between TPB constructs and pharmacists’ intentions to stock or recommend nalmefene over the next six months. All data were analyzed using SPSS statistical software version 29 with an alpha of 0.05. There were 119 pharmacist respondents (n = 25 inpatient, n = 94 outpatient). The majority were female (68.1%), White (94.1%), and worked in community settings (35.3% independent, 10.9% corporate, 10.1% big-box, 5.0% grocery). Median age was 42 years (IQR: 36–51). Awareness of nalmefene was low: only 39.5% had heard of it and 5.9% had seen it in practice. Inpatient versus outpatient pharmacists reported higher subjective norms external to the workplace (median [IQR]: 3.00 [2.33, 3.58] vs. 2.33 [1.67, 3.00]; p = 0.004) as well as subjective knowledge (mean [SD]: 2.96 [0.94] vs. 2.55 [0.74]; p = 0.023), while outpatient versus inpatient pharmacists reported higher perceived barriers related to fiscal/logistical concerns (mean [SD]: 3.45 [0.59] vs. 3.07 [0.66]; p = 0.009). Among community pharmacists, stocking and procurement confidence was higher among independent versus chain pharmacists (3.75 [3.00–4.17] vs. 3.17 [2.67–3.92]; p = 0.026). Furthermore, external workplace norms among urban pharmacists were higher than among rural pharmacists (2.50 [2.00–3.00] vs. 2.33 [1.67, 2.67]; p = 0.027), while stocking and procurement confidence was higher among rural than urban pharmacists (3.83 [2.83–4.50] vs. 3.17 [2.67–4.00]; p = 0.034). In adjusted reduced regression models, perceived behavioral control regarding nalmefene stocking and procurement (B = 0.189, 95% CI: 0.049, 0.329; p = 0.009), subjective norms external to the workplace (B = 0.232, 95% CI: 0.047, 0.418; p = 0.015), and interprofessional recommendation attitudes (B = 0.237, 95% CI: 0.037, 0.437; p = 0.021) positively predicted nalmefene implementation intentions. These findings suggest practice-setting differences that could be further explored for optimal implementation of nalmefene distribution and access, and highlight the need for targeted education, interprofessional collaboration, procurement guidance, and workflow tools to improve pharmacist preparedness for nalmefene services. Full article

This study examines the evolutionary characteristics and potential influencing factors of production–living–ecological spaces (PLES) in resource-exhausted cities, using Zaozhuang City in Shandong Province—the first coal-based resource-exhausted city in eastern China—as a case study. A territorial spatial transition matrix, dynamic degree model, Geo-information Tupu, chord diagram visualization, and Pearson correlation analysis were integrated to examine PLES evolution from 2000 to 2020. The results show the following: (1) Spatial conversions were relatively frequent during 2000–2010 but slowed markedly after 2010, indicating clear stage-specific characteristics. (2) Urban living space, rural living space, and industrial and mining production space continued to expand, while water ecological space increased with fluctuations. In contrast, agricultural production space and terrestrial ecological space continued to decline. Urban living space expanded mainly around the built-up areas of Shizhong District, Xuecheng District, and Tengzhou City and around major industrial parks, while conversions between rural living space and agricultural production space were particularly frequent. (3) PLES changes showed varying degrees of association with resource endowment, economic and industrial development, population and transport, and planning and policy, with differentiated responses among spatial types. Zaozhuang’s designation as a resource-exhausted city in 2009 occurred shortly before spatial evolution became more stable after 2010, providing important contextual evidence for understanding this stage transition. Overall, PLES evolution shifted from outward expansion under resource development toward spatial stabilization and stock-based restructuring during the resource-exhausted stage. These findings provide empirical insights for resource-exhausted cities with similar coal-dependent development trajectories and transformation contexts. Full article

Canal heritage settlements in the Jiangnan water-network region constitute a built-environment legacy of sustained, long-term human–water co-adaptation, yet their traditional morphologies and spatial fabrics are undergoing rapid restructuring amid accelerated industrialization and urbanization. Existing analytical approaches remain largely confined to two-dimensional buffer-zone analysis and planar kernel-density estimation, which cannot distinguish whether contact relationships among historical layers represent conformable contacts or angular unconformities, and have failed to translate geological stratigraphic succession into an operational framework for built heritage conservation. Drawing on landscape stratigraphy theory, this study converts historical layering, path dependency, and spatial inheritance into quantifiable GIS indicators, employing an extrusion index, a path-dependency index, a Gaussian residual field model, and Geodetector factor-interaction analysis to interrogate spatial evolution mechanisms. Most settlements exhibit stable stratigraphic layering, while a subset display angular unconformity linked to institutional displacement events and others demonstrate structural wedging toward canal frontages driven by commercial densification. Commercial points of interest retain the strongest clustering lock-in on historical waterway networks, while transportation points of interest remain linearly constrained along the historical canal corridor. Archaeological remnants remain significantly spatially coupled with contemporary land-use patterns through residual field effects even after abandonment or functional weakening. Water-network density and historical period exhibit enhanced synergistic effects on settlement spatial differentiation. These findings indicate that the spatial evolution of canal heritage settlements follows a stratigraphic logic, in which the vertical embeddedness of historical infrastructure is associated with the horizontal elasticity of contemporary spatial responses. The proposed metrics furnish replicable quantitative tools for heritage zoning and sustainable conservation planning. Full article

Semantic segmentation of 3D urban meshes is a fundamental task for intelligent urban scene understanding. However, conventional methods face severe computational efficiency bottlenecks in large-scale scenarios. Meanwhile, state space models (SSMs) with inherent linear time complexity offer an efficient solution, but existing SSM-based approaches fail to fully exploit the intrinsic textural properties of 3D meshes, resulting in degraded feature discriminability and inferior performance on fine-grained structures and small urban objects. To address these issues, we propose TOTMSeg, a texture-aware octree-based Transformer-Mamba framework for large-scale urban mesh semantic segmentation. It follows a coherent pipeline of texture feature extraction, octree-guided local feature aggregation, and global semantic feature modeling. Specifically, we design a Point-template-based Texture Sampling (PTS) strategy and integrate a lightweight Texture Triangular Convolution (TTC) module to extract fine-grained texture details, effectively alleviating the texture information deficiency in conventional point cloud-based methods. Extensive experiments on two large-scale public datasets demonstrate that TOTMSeg outperforms state-of-the-art (SOTA) baselines on main evaluation metrics, achieves notable performance gains on fine-grained structures and small-object categories, and preserves the high computational efficiency of SSM-based architectures. Full article

To improve the binary semantic segmentation of bare rock and background in complex urban environments, this study developed an improved DeepLabV3+ model for red–green–blue (RGB) imagery derived from Gaofen-1 (GF-1) data. Four backbone networks—Xception, ResNet50, MobileNetV2, and MobileNetV3—were first evaluated. ResNet50 was selected because it achieved the highest bare-rock IoU and bare-rock F1-score among the evaluated backbones under the evaluated experimental configuration. An Adam-based training configuration was subsequently evaluated against a stochastic gradient descent (SGD)-based configuration and selected for the ResNet50 baseline. Squeeze-and-excitation (SE) channel attention, a spatial attention module (SATM), and a receptive field block (RFB) were then integrated to enhance feature representations from channel, spatial, and multi-scale perspectives. In the repeated evaluation of the proposed model within the ablation experiment using three independent training runs, the model achieved a mean bare-rock IoU of 79.36 ± 0.30%, a mean bare-rock precision of 88.65 ± 0.55%, and a mean bare-rock F1-score of 88.49 ± 0.19%. These results indicate favorable overall bare-rock segmentation performance under the evaluated experimental setting. Compared with the original DeepLabV3+ configuration (Xception + SGD), the proposed model achieved improvements of 14.51, 4.80, and 9.82 percentage points in bare-rock IoU, precision, and F1-score, respectively. These improvements reflect the combined effects of backbone selection, optimizer configuration, and the proposed module integration. Compared with the ResNet50 + Adam baseline model established in this study, the proposed model further improved these metrics by 5.19, 4.60, and 3.32 percentage points, respectively. Among the evaluated models, the proposed method achieved the highest bare-rock IoU and bare-rock F1-score, whereas U-Net achieved a higher bare-rock precision. Thus, the comparative advantage of the proposed model was primarily reflected in segmentation overlap and overall F1 performance rather than in precision. Qualitative comparisons further showed favorable boundary continuity and feature discrimination in representative complex urban scenes containing buildings, vegetation, roads, and shadow-affected areas. These results provide methodological support for bare-rock segmentation and related geological remote-sensing applications in complex plateau urban environments. Full article

Urban campuses represent complex landscapes comprising buildings, roads, water bodies, and vegetation patches. Differences in spatial structures among landscape microhabitats and levels of human disturbance may influence avian acoustic activity and birdsong soundscape characteristics. However, continuous spatiotemporal dynamics of birdsong soundscapes and differences in acoustic community composition at the campus scale remain insufficiently explored. To address this gap, this study integrates 24 h continuous passive acoustic monitoring across replicated landscape microhabitats with field-validated deep learning-based birdsong identification, enabling diel, spatial, and acoustic-community patterns to be evaluated within a unified fine-scale campus framework. Using the Qingdao Agricultural University campus as a case study, we established 25 monitoring sites from March to May 2026 across five landscape microhabitat types: streamside, lakeshore, green space, building, and edge. Twelve days of 24 h continuous passive acoustic monitoring were conducted, and target bird species were identified using MFCC–based acoustic features combined with the EfficientNet–B0 multi-label classification model, whose field applicability was further evaluated using an independently selected and manually annotated subset of the campus recordings. The results revealed that birdsong soundscapes across different landscape microhabitats exhibited consistent diel rhythms, with the highest avian acoustic activity occurring during the early-morning period. Spatially, avian acoustic activity and the number of detected target bird species were generally higher in streamside-type, lakeshore-type, and green space-type microhabitats than in building-type and edge-type microhabitats. Significant differences in birdsong acoustic community composition were observed among different landscape microhabitats and fixed clock-time periods, showing species-specific spatiotemporal responses. These findings demonstrate the value of species-resolved birdsong soundscape monitoring as a complementary approach for fine-scale ecological assessment and provide site-specific evidence for landscape microhabitat management and bird-friendly planning on urban campuses. Full article