Search Results (22,957)

The use of remote sensing technologies for mapping forest fires has experienced significant growth in recent decades, driven by advancements in remote sensors, processing platforms, and artificial intelligence algorithms. This study presents a review of 192 scientific articles published between 1990 and 2024, selected using PRISMA criteria from the Scopus database. Trends in the use of active and passive sensors, spectral indices, software, and processing platforms as well as machine learning and deep learning approaches are analyzed. Bibliometric analysis reveals a concentration of publications in Northern Hemisphere countries such as the United States, Spain, and China as well as in Brazil in the Southern Hemisphere, with sustained growth since 2015. Additionally, the publishers, journals, and authors with the highest scientific output are identified. The normalized burn ratio (NBR) and the normalized difference vegetation index (NDVI) were the most frequently used indices in fire mapping, while random forest (RF) and convolutional neural networks (CNN) were prominent among the applied algorithms. Finally, the main technological and methodological limitations as well as emerging opportunities to enhance fire detection, monitoring, and prediction in various regions are discussed. This review provides a foundation for future research in remote sensing applied to fire management. Full article

The direct fitting of sea level anomaly (SLA) using satellite along-track data provides a critical approach for monitoring mesoscale ocean dynamics. While bicubic quasi-uniform B-spline surface fitting has demonstrated feasibility in localized sea areas, its applicability to basin-scale regions remains underexplored. This study focuses on the northern Atlantic Ocean, employing B-spline surface fitting to derive SLA fields from satellite along-track data. The results show strong agreement with in situ measurements, yielding a mean absolute error (MAE) of 1.89 cm and a root mean square error (RMSE) of 3.02 cm. Comparative analysis against the Copernicus Marine Environment Monitoring Service (CMEMS) Level-4 gridded SSH data reveals nearly equivalent accuracy (MAE: 1.95 cm; RMSE: 3.06 cm). The relationship between the order of fitting and the spatial extent of the fitting domain is also examined. Furthermore, the influence of the coastline on the fitting results is investigated in detail. As the coastline area expanded, the MAE and RMSE for the entire region increased. But the maximum increase in MAE was only 1.20 cm, and the maximum increase in RMSE was only 2.49 cm. Notably, there was no upward trend in MAE and RMSE in the mesoscale vortex dense area, which highlights the advantage of B-spline’s local support. Geostrophic flow and vertical component of relative vorticity are computed from the satellite along-track SLA data, with results showing agreement with Level-4 gridded geostrophic flow and vertical component of relative vorticity data. Full article

To evaluate water pollution status and sustainable development potential in the Huai River Basin, this study focused on the spatiotemporal evolution and influencing factors of the grey water footprint (GWF) across 35 cities in the basin from 2005 to 2020. This study quantifies the GWF from agricultural, industrial, and domestic perspectives and analyzes its spatial disparities by incorporating spatial autocorrelation analysis. The Tapio decoupling model was applied to explore the relationship between pollution and economic growth, and geographic detectors along with the STIRPAT model were utilized to identify driving factors. The results revealed no significant global spatial clustering of GWF in the basin, but a pattern of “high in the east and west, low in the north and south” emerged, with high-value areas concentrated in southern Henan and northern Jiangsu. By 2020, 85.7% of cities achieved strong decoupling, indicating improved coordination between the environment and economy. Key driving factors included primary industry output, crop sown area, and grey water footprint intensity, with a notable interaction between agricultural output and grey water footprint intensity. The quantitative analysis based on the STIRPAT model demonstrated that seven factors, including grey water footprint intensity and total crop sown area, exhibited significant contributions to influencing variations. Ranked by importance, these factors were grey water footprint intensity > total crop sown area > urbanization rate > population size > secondary industry output > primary industry output > industrial wastewater discharge, collectively explaining 90.2% of the variability in GWF. The study provides a robust scientific basis for water pollution control and differentiated management in the river basin and holds significant importance for promoting sustainable development of the basin. Full article

This study aimed at proposing a predictive model for real-time monitoring of epidemic dynamics at the municipal scale in Lombardy region, in northern Italy, leveraging Emergency Medical Services (EMS) dispatch data and Geographic Information Systems (GIS) methodologies. Unlike traditional epidemiological models that rely on official diagnoses and offer limited spatial granularity, our approach uses EMS call data (rapidly collected, geo-referenced, and unbiased by institutional delays) as an early proxy for outbreak detection. The model integrates spatial filtering and machine learning (random forest classifier) to categorize municipalities into five epidemic scenarios: from no diffusion to active spread with increasing trends. Developed in collaboration with the Lombardy EMS agency (AREU), the system is designed for operational applicability, emphasizing simplicity, speed, and interpretability. Despite the complexity of the phenomenon and the use of a five-class output, the model shows promising predictive capacity, particularly for identifying outbreak-free areas. Performance is affected by changing epidemic dynamics, such as those induced by widespread vaccination, yet remains informative for early warning. The framework supports health decision-makers with timely, localized insights, offering a scalable tool for epidemic preparedness and response. Full article

This study investigates the presence, origin, and associated ecological and human health risks of polycyclic aromatic hydrocarbons (PAHs) in soils from uncultivated lands and beach sediments within the Yellow River Delta (YRD), China. The measured concentrations of 16 priority PAHs in soils spanned 24.97–326.42 ng/g (mean: 130.88 ng/g), while concentrations in sediments ranged from 46.17 to 794.32 ng/g, averaging 227.22 ng/g. In terms of composition, low-molecular-weight PAHs predominated in soil samples, whereas high-molecular-weight compounds were more prevalent in sediments. The positive matrix factorization (PMF) model results suggested that petroleum pollution and fuel combustion were the main sources of PAHs in soils, whereas the contribution in sediments was derived from petroleum and traffic pollution. The ecological risk assessment results indicated that there existed no obvious ecological risk of soil PAHs, but sediment PAHs could negatively impact the surrounding ecological environment, especially in the northern coastal beach area. In addition, soil PAHs posed no potential carcinogenic risk to humans. Further pollution prevention and management measures are required in this region to ensure the safety of the environment. Full article

White-tailed deer (Odocoileus virginianus) are a cervid species native to the Americas with ecological, social, and economic significance. Managers must consider several factors when working to maintain the health and sustainability of these wild herds, including reproduction, particularly pregnancy and recruitment rates. White-tailed deer have a variable reproductive capacity, with age, health, and habitat influencing this variability. However, it is unknown whether chronic wasting disease (CWD) impacts reproduction and, more specifically, if CWD infection alters a female deer’s probability of pregnancy. Our study addressed this question using data from 9783 female deer culled in northern Illinois between 2003 and 2023 as part of the Illinois Department of Natural Resources’ ongoing CWD management program. Multilevel Bayesian logistic regression was employed to quantify the relationship between pregnancy probability and covariates like maternal age, deer population density, and date of culling. Maternal infection with CWD was found to have no significant effect on pregnancy probability, raising concerns that the equal ability of infected and non-infected females to reproduce could make breeding, which inherently involves close physical contact, an important source of disease transmission between males and females and females and their fawns. The results also identified that female fawns (<1 year old) are sensitive to county-level deer land cover utility (LCU) and deer population density, and that there was no significant difference in how yearlings (1–2 years old) and adult (2+ years old) responded to these variables. Full article

Trace metal pollution in tropical freshwater ecosystems poses growing public health concerns, particularly in regions where fisheries are central to food security; however, little is known about metal exposure risks in the Western Amazon. This study presents the first assessment of trace metal concentrations in fish sold at the main market in El Coca, a rapidly growing city in the Ecuadorian Amazon. We analyzed 11 trace metals in 17 commercially important species and estimated seven health risk indices based on two fish consumption scenarios and international reference dose standards. Our results show that all species exceeded recommended thresholds for arsenic, mercury, and lead, while one species surpassed guidelines for aluminum. Metal concentrations varied by species and river of origin: small catfish from the Payamino River had elevated cadmium, chromium, copper, and manganese levels, potentially linked to upstream gold mining, whereas larger catfish showed higher mercury and arsenic accumulation. Monte Carlo simulations of risk indices suggested overall low disease risk, but the lack of local demographic data limits accurate assessments for vulnerable groups. Despite sampling limitations, our findings offer the first baseline for monitoring trace metal exposure in the northern Ecuadorian Amazon and underscore the need for targeted public health strategies in this understudied region. Full article

Background: Behçet’s Disease (BD) was traditionally classified according to the International Study Group (ISG), where oral ulcers were mandatory. The International Team for the Revision of the International Criteria for BD (ICBD) introduced a scoring system instead. Our aim was to assess (a) sensitivity, (b) concordance between ISG and ICDB criteria in global and severe BD cases (ocular, vascular, and neurological), and (c) evaluate their clinical implications. Methods: Retrospective cohort study including 142 BD patients diagnosed in a well-defined population in Northern Spain, between January 1980 and November 2023. Both ISG and ICBD criteria were compared, sensitivity and concordance were assessed using Prevalence-Adjusted and Bias-Adjusted Kappa (PABAK) and the unadjusted Kappa. Results: A total of 142 BD patients diagnosed by expert rheumatologists (73 men; mean age of 36.4) were studied. Among them, 84 met ISG criteria, while 116 fulfilled ICBD criteria. Sensitivity of ISG and ICBD criteria in the overall cohort was (59.1% and 81.6%), respectively. Among patients with severe manifestations (ocular, vascular, or neurological), sensitivity increased to 71.2% for ISG and 92.5% for ICBD. Overall concordance was moderate (Kappa = 0.490), with 70.4% of patients classified identically. When adjusting prevalence and bias, concordance improved slightly (PABAK = 0.549). Of the 32 patients classified as BD exclusively by ICBD, 7 were receiving anti-TNF therapy, and 2 were receiving apremilast. Conclusions: The ICBD criteria demonstrated higher sensitivity than the traditional ISG criteria in classifying BD, particularly in severe cases. Classifying these additional patients under ICBD facilitated the initiation of on-label biologic treatments, potentially enhancing BD management, especially for severe cases. Full article

Petroglyph motifs from 23 sites and 37 panels in northern Georgia and western North Carolina foothills and mountains are analyzed within their archaeological, ethnographic, and landscape contexts. The Track Rock Tradition comprises 10 chronologically sequenced marking categories: (1) Cupules/Meanders/Open Circles; (2) Soapstone Extraction cars; (3) Vulva Shapes; (4) Figures; (5) Feet/Hands/Tracks; (6) Nested Circles; (7) Cross-in-Circles; (8) Spirals; (9) Straight Lines; and (10) Thin Incised Lines. Dating spans approximately 3800 years. Early cupules and meanders predate 3000 years ago, truncated by Late Archaic soapstone extraction. Woodland period (3000–1050 years ago) motifs include vulva shapes, figures, feet, tracks, and hands. Early Mississippian concentric circles date to 1050–600 years ago, while Middle Mississippian cross-in-circles span 600–350 years ago. Late Mississippian spirals (350–200 years ago) and post-contact metal tool incisions represent the most recent phases. The Track Rock Tradition differs from western Trapp and eastern Hagood Mill traditions. Given the spatial overlap with Iroquoian-speaking Cherokee territory, motifs are interpreted through Cherokee beliefs, supplemented by related Muskogean Creek ethnography. In Cherokee cosmology, the matrilocal Thunderers hierarchy includes the Female Sun/Male Moon, Selu (Corn Mother)/Kanati (Lucky Hunter), Medicine Woman/Judaculla (Master of Game), and Little People families. Ritual practitioners served as intermediaries between physical and spirit realms through purification, fasting, body scratching, and rock pecking. Meanders represent trails, rivers, and lightning. Cupules and lines emphasize the turtle appearance of certain rocks. Vulva shapes relate to fertility, while tracks connect to life-giving abilities. Concentric circles denote townhouses; cross-in-circles and spirals represent central fires. The tradition shows continuity in core beliefs despite shifting emphases from hunting (Woodland) to corn cultivation (Mississippian), with petroglyphs serving as necessary waypoints for spiritual supplicants. Full article

Accurate streamflow forecasting at fine temporal and spatial scales is essential to manage the diverse hydrological behaviors of individual catchments, particularly in rapidly responding mountainous regions. This study compares three forecasting models ARIMAX, LSTM, and HEC-HMS applied to the Posina River basin in northern Italy, using 13 years of hourly hydrological data. While recent literature promotes multi-basin LSTM training for generalization, we show that a well-configured single-basin LSTM, combined with a rolling forecast strategy, can achieve comparable accuracy under high-frequency, data-constrained conditions. The physically based HEC-HMS model, calibrated for continuous simulation, provides robust peak flow prediction but requires extensive parameter tuning. ARIMAX captures baseflows but underestimates sharp hydrological events. Evaluation through NSE, KGE, and MAE shows that both LSTM and HEC-HMS outperform ARIMAX, with LSTM offering a compelling balance between accuracy and ease of implementation. This study enhances our understanding of streamflow model behavior in small basins and demonstrates that LSTM networks, despite their simplified configuration, can be reliable tools for flood forecasting in localized Alpine catchments, where physical modeling is resource-intensive and regional data for multi-basin training are often unavailable. Full article

Extreme precipitation events severely impact agriculture, reducing yields and land use efficiency. The spatiotemporal distribution of Total Column Water Vapor (TCWV), the primary gaseous form of water, directly influences sustainable agricultural management. This study, through multi-source data fusion, employs methods including the Mann–Kendall test, sliding change-point detection, wavelet transform, pixel-scale trend estimation, and linear regression to analyze the spatiotemporal dynamics of global TCWV from 1959 to 2023 and its impacts on agricultural systems, surpassing the limitations of single-method approaches. Results reveal a global TCWV increase of 0.0168 kg/m²/year from 1959–2023, with a pivotal shift in 2002 amplifying changes, notably in tropical regions (e.g., Amazon, Congo Basins, Southeast Asia) where cumulative increases exceeded 2 kg/m² since 2000, while mid-to-high latitudes remained stable and polar regions showed minimal content. These dynamics escalate weather risks, impacting sustainable agricultural management with irrigation and crop adaptation. To enhance prediction accuracy, we propose a novel hybrid model combining wavelet transform with LSTM, TCN, and GRU deep learning models, substantially improving multidimensional feature extraction and nonstationary trend capture. Comparative analysis shows that WT-TCN performs the best (MAE = 0.170, R² = 0.953), demonstrating its potential for addressing climate change uncertainties. These findings provide valuable applications for precision agriculture, sustainable water resource management, and disaster early warning. Full article

Rubus magurensis Wolanin, M. Nobis & Oklej. (Rosaceae), a new species from the Northern Carpathians, described and illustrated here, is a tetraploid (2n = 28) belonging to the subgenus Rubus series Micantes. Among the most characteristic features of this species are first-year stems that are almost glabrous, leaflets most often arched downward, and inflorescences leafy to the apex with a few simple oval leaves in the upper part, which make this species easy to recognise. This species resembles R. tabanimontanus Figert, from which it differs in having smaller primocane prickles, digitate to subpedate leaves, larger flowers, and inflorescences leafy to the apex. Rubus magurensis is currently known from 11 populations located in southeastern Poland (7 ATPOL 2 × 2 km units). Most of them were found in the central part of the Low Beskid Mts., with two populations located in the northwestern part of the Strzyżów Foothills. Full article

Accurate estimation of actual evapotranspiration (ET) is critical for understanding hydrothermal cycles and ecosystem functioning in arid regions, where water scarcity governs ecological resilience. To address persistent gaps in ET quantification, this study integrates multi-source remote sensing data, energy balance modeling, and ground-based validation that significantly enhances spatiotemporal ET accuracy in the vulnerable desert steppe ecosystems. The study utilized meteorological data from several national stations and Landsat-8 imagery to process monthly remote sensing images in 2019. The Surface Energy Balance System (SEBS) model, chosen for its ability to estimate ET over large areas, was applied to derive modeled daily ET values, which were validated by a large-weighted lysimeter. It was shown that ET varied seasonally, peaking in July at 6.40 mm/day, and reaching a minimum value in winter with 1.83 mm/day in December. ET was significantly higher in southern regions compared to central and northern areas. SEBS-derived ET showed strong agreement with lysimeter measurements, with a mean relative error of 4.30%, which also consistently outperformed MOD16A2 ET products in accuracy. This spatial heterogeneity was driven by greater vegetation coverage and enhanced precipitation in the southeast. The steppe ET showed a strong positive correlation with surface temperatures and vegetation density. Moreover, the precipitation gradients and land use were primary controllers of spatial ET patterns. The process-based SEBS frameworks demonstrate dual functionality as resource-optimized computational platforms while enabling multi-scale quantification of ET spatiotemporal heterogeneity; it was therefore a reliable tool for ecohydrological assessments in an arid steppe, providing critical insights for water resource management and drought monitoring. Full article

The intensification of anthropogenic pressures, particularly those related to agriculture driven by increasing demands for food and cash crops, generates negative environmental externalities. Assessing these externalities is essential to better identify and implement measures that promote the environmental sustainability of rural landscapes. This study aims to develop a multi-criteria assessment method of the negative environmental externalities of rural landscapes in the northern Benin agricultural basin, based on satellite-derived data. Starting from a 12-class land cover map produced through satellite image classification, the evaluation was conducted in three steps. First, the 12 land cover classes were reclassified into Human Disturbance Coefficients (HDCs) via a weighted sum model multi-criteria analysis based on nine criteria related to the negative environmental externalities of anthropogenic activities. Second, the HDC classes were spatially aggregated using a regular grid of 1 km² landscape cells to produce the Landscape Environmental Sustainability Index (LESI). Finally, various discretization methods were applied to the LESI for cartographic representation, enhancing spatial interpretation. Results indicate that most areas exhibit moderate environmental externalities (HDC and LESI values between 2.5 and 3.5), covering 63–75% (HDC) and 83–94% (LESI) of the respective sites. Areas of low environmental externalities (values between 1.5 and 2.5) account for 20–24% (HDC) and 5–13% (LESI). The LESI, derived from accessible and cost-effective satellite data, offers a scalable, reproducible, and spatially explicit tool for monitoring landscape sustainability. It holds potential for guiding territorial governance and supporting transitions towards more sustainable land management practices. Future improvements may include, among others, refining the evaluation criteria and introducing variable criteria weighting schemes depending on land cover or region. Full article

Understanding the migratory strategies of plateau-endemic species is essential for informing effective conservation, especially under climate change. The Black-necked Crane (Grus nigricollis), a high-altitude specialist, has shown notable population growth in recent years. We analysed satellite tracking data from 16 individuals of a western subpopulation in the lake basin region of northern Tibet (2021–2024), focusing on migration patterns, stopover use, and habitat selection. This subpopulation exhibited short-distance (mean: 284.21 km), intra-Tibet migrations with low reliance on stopover sites. Autumn migration was shorter, more direct, higher in altitude, and slower in speed than spring migration. Juveniles used smaller, more fragmented habitats than subadults, and their spatial range expanded over time. Given these patterns, we infer that the short-distance migration strategy may reduce energetic demands and mortality risks while increasing route flexibility—characteristics that may benefit population growth. We refer to this as a low-energy, high-efficiency migration strategy, which we hypothesise could support faster population growth and enhance resilience to environmental change. We recommend prioritizing the conservation of short-distance migration corridors, such as the typical lake basin area in northern Tibet–Yarlung Tsangpo River system, which may help sustain plateau-endemic migratory populations under future climate scenarios. Full article