Search Results (158)

The Northern Tibetan Plateau is among the most climate-sensitive alpine regions globally. To address the limited applicability of the traditional Remote Sensing Ecological Index (RSEI) in sparsely vegetated areas, this study developed a Soil-Adjusted Remote Sensing Ecological Index (SRSEI) tailored to cold and arid environments. The ecological quality of the Northern Tibetan Plateau from 2000 to 2025 was systematically evaluated and analyzed. The results indicate that: (1) The improved SRSEI achieved a first principal component (PC1) contribution of 72.76%, a significant enhancement over traditional models that effectively mitigates noise from soil backgrounds and anthropogenic features. (2) Between 2000 and 2025, ecological quality was predominantly moderate, following a characterized east-to-west declining spatial gradient. Overall mean SRSEI values fluctuated between 0.420 and 0.476, exhibiting a marginal downward trend. (3) Ecological degradation affected 50.17% of the region, with 26.14% facing risks of sustained decline. Conversely, 40.11% of the area displayed potential recovery trends, suggesting potential spatial divergence in future ecological trajectories. (4) Regional ecological dynamics are governed by a topographic-thermal compound driving mechanism. Elevation (DEM), temperature (TEMP), and surface shortwave radiation (SRAD) emerged as the dominant explanatory variables. Furthermore, dual-factor interactions exhibited significant enhancement effects, while the influence of anthropogenic factors was comparatively weak at the regional scale. These findings provide a scientific basis for the long-term monitoring of fragile alpine ecosystems and the strategic development of the Qiangtang National Park. Full article

Acoustic indices are popular tools for rapid biodiversity assessment using passive acoustic monitoring recordings, yet anthropogenic sounds in human activity areas compromise their robustness. In this paper, we focus on the typical urban–rural soundscape, where anthropogenic noise mainly originates from a narrow angular sector far from the monitoring device. We propose a denoising preprocessing algorithm with two microphone sensors for the robust application of existing acoustic indices. Our algorithm first develops an adaptive multi-tap null-steering beamformer based on a back-to-back first-order differential microphone array, which increases the system degrees of freedom to enhance the broadband interference cancellation capability. Building on this, a parallel bank of mutually orthogonal null-steering beamformers is proposed, each forming deep nulls toward directional interference-concentrated bands and generating diverse responses to the target signal. Finally, a signal compensation mechanism is applied to the beamformers’ outputs, mitigating the signal self-cancellation effects from these unconstrained adaptive beamformers prior to index calculation. The proposed preprocessing method is evaluated using the frequency-dependent acoustic diversity index as a representative of acoustic indices. Experiment results on both simulation and real-world recordings show that the proposed method generates high-fidelity acoustic information for subsequent acoustic index calculation over a much wider signal-to-interference-plus-noise ratio (SINR) range in urban–rural soundscapes characterized by directional anthropogenic interference. Full article

Monitoring cropland dynamics in arid regions is critical for balancing food security with water scarcity constraints. However, distinguishing fragmented agricultural oases from spectrally similar desert vegetation remains a persistent challenge due to spectral confusion and landscape heterogeneity. To address these challenges, this study developed the STGP-OCE feature cube on the Google Earth Engine platform (GEE) by integrating the Oasis Cooling Effect (OCE) into the commonly used STGP (Spectral, Textural, Geomorphic, and Phenological) feature space, coupled with the XGBoost ensemble model. Through ablation experiments and feature importance analysis, we quantified the feature construction mechanism for arid regions. Oasis Cooling Intensity emerged as the most influential variable (Gain score: 0.315), demonstrating that the thermal signature of continuous anthropogenic irrigation serves as a robust thermodynamic proxy to resolve the spectral ambiguity between crops and drought-tolerant desert vegetation. By hierarchically coupling this thermal indicator with textural features to suppress fragmentation noise, topographic constraints to filter non-arable terrain, and phenological trajectories, the STGP-OCE feature cube achieved an Overall Accuracy of 95.12% and a Precision of 94.95%, significantly outperforming models built on lower-dimensional cubes as well as existing global land cover products. We generated a 10 m annual cropland dataset for Xinjiang, China, revealing a substantial 32.9% expansion (19,360 km²) from 2015 to 2024, mainly occurring in vulnerable oasis–desert transition zones and coinciding with reported reclamation activities. These highlight the continuous agricultural encroachment into desert margins, while the proposed STGP-OCE cube provides a reliable methodology for high-precision cropland monitoring in arid regions. Full article

Groundwater systems in semi-arid and industrial regions are increasingly affected by climate-driven non-stationarity and anthropogenic pressure, challenging conventional forecasting approaches. This study develops and evaluates an integrated artificial intelligence framework designed to minimize piezometric head residual dispersion under non-stationary hydroclimatic conditions. The proposed methodology combines Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) and Variational Mode Decomposition (VMD) with a Slime Mould Algorithm–optimized Long Short-Term Memory (SMA–LSTM) model and a CNN–LSTM architecture, which are dynamically fused using an Adaptive Weighting Model (AWM). The framework was applied to long-term groundwater level (1994–2024), groundwater quality (2017–2023), and meteorological datasets to evaluate the predictive robustness across climatic variability regimes. The proposed ensemble achieved a mean absolute error of 0.267 m, root mean square error of 0.429 m, coefficient of determination (R²) of 0.948, and Nash–Sutcliffe efficiency of 0.938, representing substantial residual reduction compared to baseline deep learning models. Residual diagnostics confirmed minimized peak deviations and stable performance under non-stationary conditions. Scenario-based simulations driven by CMIP6 climate projections indicate increasing groundwater stress under future warming trajectories, with amplified variability and declining recharge signals. These findings demonstrate that multi-stage signal decomposition coupled with metaheuristic optimization and adaptive ensemble learning significantly enhances predictive stability and residual minimization in climate-sensitive aquifer systems. The proposed framework provides a transferable, climate-resilient decision-support tool for sustainable groundwater management in industrial and semi-arid regions. Full article

Urban travel intensity is a practical proxy for human mobility, but direct mobility data are often costly, geographically restricted, and privacy sensitive. UTScan uses continuous ambient seismic data to estimate urban travel intensity in a passive, non-intrusive manner. Model development used 10 cities in Hubei Province during January–April 2020, and external validation used 84 non-Hubei cities that satisfied the study’s data-quality criteria. From each hourly power spectral density (PSD) curve, we extracted 13 features in the 2–20 Hz anthropogenic band, applied a station-wise low-activity baseline subtraction, and then modeled daily travel intensity with a CatBoost–LSTM framework. Under the calendar-based forward-validation protocol, the final UTScan implementation (FusionB) achieved a mean RMSE of 0.537 ± 0.214 and a mean Pearson correlation of 0.768 ± 0.076 across the internal Hubei folds and a mean RMSE of 0.789 ± 0.229 and a mean Pearson correlation of 0.605 ± 0.370 across the 84-city external validation set. Additional sensitivity analyses using alternative validation windows and light-touch outlier handling indicated that the main conclusions were stable, while single-station representativeness remained the principal limitation. Ambient seismic noise is therefore a useful passive proxy for estimating city-scale mobility dynamics, especially for abrupt mobility disruptions, but its interpretation remains conditional on station siting, source mixture, and the proxy nature of the Baidu travel-intensity target. Full article

Wind-driven surface processes are a major source of underwater ambient sound and are therefore an important component of coastal soundscapes. Yet their frequency-dependent expression in shallow nearshore reef environments remains insufficiently characterized from field observations. This study investigates low-to-mid-frequency (20–1000 Hz) ambient acoustic variability at Faro’s natural reef (southern Portugal) using short-term passive acoustic monitoring combined with concurrent sea state measurements. The results show evidence of a relationship between frequency-dependent acoustic response and wind-driven surface processes. At frequencies of 20–100 Hz, ambient sound levels exhibit a weak relationship with wind-driven surface conditions, with elevated variability under low agitation. This is attributed to persistent background anthropogenic noise, particularly vessel traffic. In contrast, above 100 Hz, the ambient sound level increases consistently with wind-driven agitation, indicating that wind-driven surface processes dominate ambient sound in the 100–1000 Hz frequency range. Transient high-energy peaks increase in frequency and intensity with surface agitation, consistent with breaking-wave events, even though elevated background sound levels persist after peak removal. These findings demonstrate that wind-related ambient sound variability at Faro’s natural reef is robustly expressed above approximately 100 Hz. This highlights the importance of frequency-dependent interpretation in passive acoustic monitoring as a necessary baseline for assessing the nearshore reef environment’s influence on ambient sound levels and acoustic propagation under variable sea state conditions. Full article

Urban wetlands are acoustic hotspots where vegetation structure, hydrological dynamics, and anthropogenic noise interact, yet multi-season assessments of how vegetation influences avian soundscapes are limited. This study explored bird soundscape dynamics across forest, open forest grassland, and meadow habitats in Nanjing Xinjizhou National Wetland Park, eastern China, using passive acoustic monitoring during spring and autumn 2023. Twelve sampling points (four per vegetation type) were established, and six acoustic indices were calculated, including the Acoustic Complexity Index (ACI), Acoustic Diversity Index (ADI), Acoustic Evenness Index (AEI), Bioacoustic Index (BIO), Normalized Difference Soundscape Index (NDSI), and Acoustic Entropy Index (H). were calculated from 48-h recordings each season. Random forest models and redundancy analysis assessed the relationships between acoustic indices, fine-scale vegetation parameters (e.g., crown width, tree height, species richness), and anthropogenic factors (e.g., distance to roads/trails, surface hardness). Vegetation structure, particularly crown width, was the primary driver of avian acoustic diversity, with broad-crowned forests consistently exhibiting the highest acoustic complexity. In spring, anthropogenic factors such as trail and road proximity dominated soundscape variation, suppressing biological sounds. In autumn, with reduced human presence, vegetation structure emerged as the dominant factor, while bioacoustic activity remained elevated despite reduced peaks in acoustic complexity. Proximity to roads increased low-frequency (1–2 kHz) noise and suppressed mid-frequency (4–8 kHz) bird vocalizations, but trees with crown widths ≥4 m maintained higher acoustic diversity even near disturbance sources. This study demonstrates that vegetation structure mediates both resource availability and sound propagation, buffering the effects of anthropogenic disturbance in frequency-specific ways. Multi-season sampling is crucial for understanding the dynamic interplay between vegetation phenology and human activity that shapes urban wetland soundscapes. Full article

This article presents a literature review aimed at outlining the state of the art in the assessment of underwater noise and in the evaluation of its effects on fish behavior and health. We examine current methodologies for characterizing the underwater soundscape, emphasizing the importance of incorporating particle motion sensors alongside pressure sensors due to the nature of fish auditory systems. Guidelines for simulating underwater acoustic environments in laboratory settings are also summarized. To characterize anthropogenic noise sources, we consider ship propellers as the primary source of continuous underwater noise, whereas we consider the equipment used in marine seismic surveys as the primary source of impulsive underwater noise. Finally, we summarize documented effects of acoustic pollution on a commercially important species, European seabass (Dicentrarchus labrax), and describe experimental setups suitable for observing these effects. Full article

Accurate and timely mapping of paddy rice is essential for agricultural management, food security, and climate-resilient policy. However, high-precision mapping remains challenging in subtropical monsoon regions due to persistent cloud cover, long revisit intervals, and striping noise, which compromise satellite data quality and availability. To address these limitations, a rice mapping framework suitable for different geographical environments was developed based on a random forest (RF) by combining time-series harmonic analysis (HANTS) with Sentinel-1 and Sentinel-2 multi-source data. To address these limitations, a rice mapping classification algorithm for different geographical environments was developed by combining Harmonic Analysis of Time Series (HANTS) with Sentinel-1/2 multi-source data. The research obtained annual maps of single-season and double-season rice in the research area from 2019 to 2024, with a spatial resolution of 10 m. The results indicated that the Sentinel-1, Sentinel-2, GEE, and HANTS algorithm can effectively support the yearly mapping of single- and double-season paddy rice in Anhui Province, China. The resultant paddy rice map has a high accuracy with overall accuracies exceeding 92% and Kappa coefficients above 0.84. HANTS effectively captures key phenological features of paddy rice, and it can especially enhance the discrimination between single- and double-season rice; compared to existing rice mapping products, the proposed approach reduces classification errors by an average of 3.92% in six major rice-producing cities, each with cultivation areas exceeding 1 million hectares; spatial correlation analysis indicates substantial heterogeneity in rice cultivation patterns across northern, central, and southern Anhui, associated with both biophysical and anthropogenic factors. These results indicate that integrating phenological data with machine learning can enhance the accuracy of long-term, high-resolution crop monitoring, and annual rice maps will offer valuable support for food security assessment, water resource management, and policy planning. Full article

Underwater noise pollution, driven by human activities, is an emerging environmental concern, yet its effects on fish behavior and physiology remain poorly understood. As a vertebrate model with conserved stress pathways, zebrafish (Danio rerio) is well-suited for investigating the mechanistic basis of such impacts. We hypothesized that daytime and nighttime noise exposure would differentially induce anxiety-like behavior and associated neuroendocrine disruptions in zebrafish, with effects varying by sex. To evaluate this hypothesis, adult zebrafish were exposed to anthropogenic noise (100–1000 Hz, 130 dB) for seven days, specifically during daytime (08:00–20:00) and nighttime (20:00–08:00) periods. Behavioral assays revealed that noise exposure delayed the first entry of females into the top zone during daytime, while both sexes exhibited prolonged bottom-dwelling and reduced exploratory behavior under nighttime noise. Physiological analyses showed elevated plasma cortisol levels in females, accompanied by up-regulated HPI-axis genes, whereas males displayed a non-significant cortisol increase. Neurotransmitter profiling indicated a sex-specific response to nighttime noise: In females, brain 5-hydroxytryptamine (5-HT) showed a non-significant increasing trend, whereas in males it was significantly elevated, while dopamine (DA) decreased in both sexes. Gene expression analysis further revealed disruptions in 5-HT and DA pathways. These findings demonstrate that underwater noise induces anxiety-like behavior in zebrafish by dysregulating endocrine and neurotransmitter systems, with nighttime noise exhibiting more pronounced effects, suggesting that chronic exposure to anthropogenic noise may impair natural behavior and stress regulation in aquatic species, particularly during nighttime periods. Full article

The recent growth of Blue Economy-related human activities has increased underwater noise pollution. Sound is a key factor in ensuring the well-being of marine animals as it allows them to communicate with each other and extract valuable information from the environment. Although the Marine Strategy Framework Directive requires monitoring programs to achieve good environmental status, there remains a significant deficit of information concerning three key domains: the characteristics of the underwater soundscape, its transformation due to anthropogenic activities, and the effects of noise on marine animals. This study aimed to evaluate the impact of anthropogenic activities on marine acoustic environments. Acoustic metrics and ecoacoustic indices were applied to characterise variability and assess daily, weekly, and seasonal patterns, as well as the effects of trawling restrictions. Three underwater soundscapes were compared in this study: two natural environments in the Mediterranean Sea and one artificial environment, a land-based fish farm tank. High anthropogenic noise levels were found, primarily due to fishing vessels near the selected locations. Similarly, the soundscape exhibited notable seasonal variations (annual and weekly), demonstrating a significant dependence on tourist activities. The results highlight the benefits of acoustic parameters as a tool for monitoring environmental conditions over time. Full article

The real-time phase picking, detection, and location of seismic events is a crucial challenge for monitoring in densely populated volcanic areas. In such contexts, low-magnitude events may escape traditional detection methods due to high levels of anthropogenic noise, which often masks weak seismic signals. This study presents the implementation of a near-real-time automatic event detector with a seismic phase recognizer, pick associator, and localiser. The system is based on PhaseNet, a well-established deep neural network recognized for its effectiveness in seismology. The main innovation introduced in this work lies in the direct application of this method to real-time data streams. This integration allows for the enhanced identification and cataloguing of low-magnitude seismic events that would otherwise remain unobserved. The adoption of the system in a real-time operational context not only increases monitoring sensitivity and responsiveness but also contributes to a more detailed and comprehensive understanding of seismic activity in critical volcanic areas, providing essential data for risk assessment and prevention. Full article

The shipping industry serves as an integral component of the global and regional economy development; however, the anthropogenic acoustic emissions generated during its operations pose considerable threats to human health, marine biodiversity and ecosystems, ultimately undermining the foundations of sustainable development. With the expansion of global trade and the continued growth of maritime transport, strengthening the governance of shipping noise pollution has emerged as a critical issue of international concern. The effective governance of shipping noise is no longer a peripheral environmental issue but an imperative, cross-sectoral challenge. Addressing it is critical for ensuring the integrity of marine ecosystems, safeguarding biodiversity, and advancing the long-term sustainability of our blue economy. This study investigates the legal and policy framework for shipping noise governance in China and finds that China has established a foundation for addressing shipping noise pollution through a dual-track legislative system which is supplemented by systematically deployed policy measures aiming at advancing noise mitigation in shipping. However, the current institutional framework exhibits some limitations. This study summarizes existing experiences, identifies areas requiring further improvement and attention, and offers recommendations for enhancing domestic legal frameworks on shipping noise pollution as well as promoting international cooperation in shipping noise governance. Full article

Adverse exposure to noise pollution is increasingly recognized as a significant public health concern. Strong evidence links noise exposure with negative health outcomes such as cardiovascular disease, mental disorders, stress, and sleep disturbance. The presence of noise in parks, which are environmental settings associated with health promotion, recreation, and restoration, presents a paradox that warrants further exploration. The United States offers a distinct context for exploring this paradox, given its vast public park system and a wide array of anthropogenic and environmental noise sources. Our scoping review synthesized findings from fifteen research studies that investigated noise exposure and noise levels in United States public parks. The review examined how studies measured noise, the integration of subjective perceptions with objective assessments, and the role of park characteristics in shaping park visitor noise experiences. Results highlighted varying methodological approaches, with some studies employing sound level meters or modeling techniques, while others also incorporated surveys to capture visitor perceptions. Despite this variety, evidence on the direct health impacts of park noise exposure remains limited, and longitudinal studies are largely absent. Notably, few studies evaluated how noise interacts with other environmental exposures, such as air pollution or greenness, to influence visitor perception and wellness. By synthesizing the current evidence base, this review suggests knowledge gaps and few methodological inconsistencies that limit the field. Findings call for future research mobilizing standardized, multimodal noise assessment methods, and considerations for health outcome measures. Such advancements are important for informing public health interventions and guiding urban planning strategies to improve the acoustic quality and restorative potential of US parks. Full article

The Strait of Gibraltar is a major biogeographic bottleneck connecting the Atlantic Ocean and the Mediterranean Sea, where migratory cetaceans coexist with an intense maritime traffic. To evaluate the feasibility of broadband passive acoustic monitoring (PAM) for both soundscape characterisation and cetacean detection, a short drifting-buoy experiment was conducted near Barbate, Spain, in May 2025. The system, equipped with a calibrated SoundTrap 400 recorder, continuously sampled the underwater acoustic environment for 2.5 h. Analysis of the recordings revealed vocalisations of Orcinus orca, representing the first preliminary and incomplete description of the Iberian killer whale acoustic repertoire, and numerous transient tonal events with energy peaks between 40 and 50 Hz, consistent with baleen whale sounds previously attributed to foraging fin whales (Balaenoptera physalus). Sperm whale clicks and delphinid whistles were also occasionally detected. The power spectral density analysis further showed a persistent anthropogenic component dominated by vessel noise below 200 Hz and narrow-band echosounder signals at 30 and 50 kHz. These findings confirm the potential of PAM to detect multiple cetacean species and to resolve the complex interplay between biophony and anthropophony in one of the world’s busiest marine corridors. Establishing a permanent PAM observatory in the Strait would enable continuous, non-intrusive monitoring of species presence, behaviour, and habitat use, thereby contributing to conservation efforts for endangered populations such as the Iberian killer whale. Full article