Search Results (4,748)

Cropland change detection (CD) in high-resolution remote sensing images is critical for cropland protection and food security. However, style differences caused by inconsistent imaging conditions (such as season and illumination) and ground object scale differences often lead to high numbers of false and missed detections. Existing approaches, predominantly relying on spatial domain features and a multiscale framework, struggle to address these issues effectively. Therefore, we propose FDFENet, incorporating a Frequency Domain Feature Exchange Module (FFEM) that unifies image styles by swapping the low-frequency components of bitemporal features. A Frequency Domain Aggregation Distribution Module (FDADM) is also introduced as a comparative alternative for handling style discrepancies. Subsequently, a Multiscale Feature Enhancement Module (MSFEM) strengthens feature representation, while a Multiscale Change Perception Module (MSCPM) suppresses non-change information, and the two modules work cooperatively to improve detection sensitivity to multiscale ground objects. Compared with the FDADM, the FFEM exhibits superior parameter efficiency and engineering stability, making it more suitable as the primary solution for long-term deployment. Evaluations on four CD datasets (CLCD, GFSWCLCD, LuojiaSETCLCD, and HRCUSCD) demonstrate that FDFENet outperformed 13 state-of-the-art methods, achieving F1 and IOU scores of 77.09% and 62.72%, 81.81% and 73.63%, 74.47% and 59.32%, and 75.95% and 61.23%, respectively. This demonstrates FDFENet’s effectiveness in addressing style differences and ground object scale differences, enabling high-precision cropland monitoring to support food security and sustainable cropland management. Full article

The present study presents long-term monitoring data on the dynamics of bedload transport processes in alpine gravel-bed river systems in Austria (Urslau, Strobler-Weißenbach) using radio frequency identification (RFID) technology. The detection of embedded RFID tracers was facilitated by the use of stationary antennas. This methodology enabled the acquisition of high-resolution data on particle transport velocities, transport distances, and sediment dynamics. Monitoring has been in operation permanently over a period of 8 years, including several intense flood events. In total, 1612 RFID-tagged stones were deployed, and the maximum measured particle velocity was 2.47 m s⁻¹. The measurements at the Urslau stream revealed seasonal variability and long-term trends, while targeted short-term measurements at the Strobler-Weißenbach stream provided valuable insights into the dynamics of flood events. The results underscore the significance of environmental factors, including the grain size, river gradient, and hydraulic parameters, in the dynamics of bedload transport in alpine gravel bed streams. Furthermore, the efficiency of stationary antennas was optimised to ensure uninterrupted monitoring. This study underscores the importance of contemporary monitoring technologies in analysing river processes and addressing challenges, including those brought about by climate change. Full article

In cold climates, maintaining indoor comfort in winter requires heating systems to supply consistent and adequate heat at low ambient temperatures, making the proper definition of indoor and outdoor design temperatures critical for equipment selection. In this paper, a flexible parameter-adjustment design approach is proposed, combining on-site testing and simulation to refine heating load calculation, and a CO₂ cascade air-source heat pump (ASHP) renovation project for a cold-climate public building is used as a case study. The optimized approach ensured that the selected ASHP maintained indoor temperature above 20 °C, with the system achieving a heating season COP of 2.89. Even at −22.2 °C, it kept indoor temperature at 22.4 °C, with a COP of 2.70. This study confirms the effectiveness of the approach and offers a practical reference for similar projects. Full article

The dry area in northwest China (ARNC), with its tough climate, serious soil erosion, and poor soil quality, is one of China’s most fragile ecosystems. Studying changes in plant growth cycles here is very important for improving environmental monitoring and making plans to adapt to climate change. While vegetation growing season parameters (Start/End of Season: SOS/EOS) serve as vital indicators of ecosystem dynamics, comprehensive understanding has been constrained by limited long-term phenological datasets and insufficient exploration of multi-factor interactions. This study used PLS-SEM to analyze 27-year (1990–2016) vegetation index data, systematically quantifying spatiotemporal variations in growing season phenology and disentangling climate–terrain driving mechanisms. The results revealed the following key findings. (1) Spatial heterogeneity in phenological patterns, with the annual average Start of Season (SOS) and End of Season (EOS) being 114.7 Day and 301.7 Day, respectively, exhibiting a northwest–high to southeast–low gradient. The findings indicate a prolongation of the vegetation growing season, with significant spatial variability. (2) Interannual fluctuations showed the SOS and EOS coefficient of variation (CV) values of 0.230 and 0.234, respectively, with southeastern regions displaying higher instability than northwestern counterparts. (3) The spatial variation in SOS/EOS is primarily influenced by meteorological and geographical factors, with an explanatory power exceeding 30%. This research advances mechanistic understandings of arid ecosystem responses to environmental stressors, providing a scientific foundation for targeted ecological restoration, desertification mitigation, and sustainable land management in climate-sensitive drylands. Full article

For an alpine inland river basin affected by climate change, the interaction between groundwater (GW) and surface water (SW) within the watershed plays a crucial role in water resource management. To explore the bidirectional dynamic coupling of surface water and groundwater, this work adopted the extensively employed SWAT–MODFLOW model. Results indicate that statistical parameters including R² (0.81 for calibration periods and 0.79 for validation), NSE (0.79 for calibration periods and 0.75 for validation), RMSE (0.59~1.25 m), and PBIAS (15.21%) demonstrate the dependability of the SWAT–MODFLOW model in evaluating groundwater–surface water exchange processes within alpine inland river basins. Long-term monitoring data show that groundwater levels exhibited an upward trend, rising from 2895.35 m in 2005 to 2906.75 m in 2022. Notably, since 2018, groundwater levels have entered a period of being consistently above the long-term average. In terms of spatial distribution, the groundwater level patterns in 2005, 2010, and 2015 remained relatively consistent, marked by a west-to-east decreasing gradient. However, by 2020, this spatial distribution pattern shifted, marked by an east-to-west decreasing gradient. Meanwhile, our results reveal a pattern of upstream surface water recharge, bidirectional fluctuation in the middle reaches, and downstream groundwater-dominated recharge during the period of 2000~2023. During the 2000–2009 period, groundwater in sub5 received recharge from surface water, with the exchange rate ranging from −4987.75 to −374.82 m³/d. Conversely, during 2010–2023, groundwater in sub5 discharged into surface water, with the exchange rate ranging from 1136.75 to 56,646.56 m³/d. Moreover, there is seasonal variability in the SW–GW interchange relationship. In spring and summer, surface water primarily replenishes groundwater, whereas in autumn and winter, groundwater primarily replenishes surface water. This study provides a foundational method for assessing groundwater–surface water interactions in alpine inland river basins, which will contribute to the evaluation and management of local water resources. Full article

Digital twins (DTs) are increasingly used in controlled-environment agriculture to model microclimates and drive energy-efficient control. However, long-term drift and seasonal variability require continuous recalibration and controller retuning. We develop a self-adaptive DT of a phytotron chamber that combines an MAPE-K loop with an evolutionary heuristic. A genetic algorithm (GA) calibrates the DT parameters against IoT time series and subsequently optimizes heater control settings (two-position, three-position, and proportional modes) subject to comfort constraints on temperature and humidity. Six monitoring intervals (May–June 2025) are used for per-interval calibration and six-fold cross-validation. The calibrated DT reproduces temperature and humidity with high fidelity across unseen intervals: the average cross-validated deviations are 0.27 °C and 7.1%RH (30 transfers). Controller optimization yields cumulative energy savings of 186.54 kWh (3.24%) over six intervals, with per-interval savings ranging from 0.37% to 5.94%. Coupling GA-based DT calibration with model-in-the-loop controller optimization consistently reduces energy use while maintaining microclimate quality, providing a practical pathway for the robust, year-round operation of vertical farms. Full article

As a sink for microplastics (MPs) in the aquatic environment, sediments have garnered considerable attention. However, the occurrence characteristics of MPs in sediments of different water seasons are not clear, especially for reservoir sediment cores. This study aimed to elucidate the occurrence, spatial and vertical distribution, fragmentation and pollution risk of MPs in the sediment cores of the Xiangxi River, Three Gorges Reservoir (TGR) during different seasons. In sediment cores, the average abundance of MPs was 8.57 × 10³ ± 5.65 × 10³ items/kg DW in the wet season (WS) and 7.98 × 10³ ± 4.00 × 10³ items/kg DW in the dry season (DS), respectively. The abundance of MPs in surface sediments and sediment cores exhibited spatial heterogeneity, reflecting seasonally contrasting hydrodynamic conditions between sites S1 and S3. However, the abundance of MPs in the river estuary was the highest, both in surface sediments and sediment cores. Interestingly, the occurrence characteristics of MPs in surface sediments indicated that in addition to anthropogenic activity, hydrological conditions of the river can also have an impact on the spatial distribution of MP abundance in surface sediments. Polypropylene (PP), polyethylene (PE), polystyrene (PS), and polyethylene-propylene copolymer (EPM) were identified as the dominant polymer types (57–99%), with small-sized microplastics (SMPs, 0–300 μm) being the most prevalent. Water seasons influenced the size distribution of MPs in surface sediments. Using a conditional fragmentation model, MP sources were inferred by comparing fragmentation parameters (λ and α) in sediments with those reported for atmospheric deposition, reservoir water, and water-level fluctuation zone soils. Furthermore, the pollution load index (PLI) exceeded 1, indicating MP accumulation in the sediments. The pollution risk index (PRI) values indicated a considerable (300 < PRI < 1000) pollution risk in two water seasons, primarily due to the presence of polyvinyl chloride (PVC). This study enhances the understanding of MP behavior and associated environmental risks in reservoir sediments, offering valuable insights for future research and pollution mitigation efforts. Full article

We present a novel framework for hyperspectral satellite image classification that explicitly balances spatial nearness with spectral similarity. The proposed method is trained on closed-set datasets, and it generalizes well to open-set agricultural scenarios that include both class distribution shifts and presence of novel and absence of known classes. This scenario is reflective of real-world agricultural conditions, where geographic regions, crop types, and seasonal dynamics vary widely and labeled data are scarce and expensive. The input data are projected onto a lower-dimensional spectral manifold, and a pixel-wise classifier generates an initial class probability saliency map. A kernel-based spectral-spatial weighting strategy fuses the spatial-spectral features. The proposed approach improves the classification accuracy by $7.22$–$15\%$ over spectral-only models on benchmark datasets. Incorporating an additional unsupervised learning refinement step further improves accuracy, surpassing several recent state-of-the-art methods. Requiring only 1–$10\%$ labeled training data and at most two tuneable parameters, the framework operates with minimal computational overhead, qualifying it as a data-efficient and scalable few-shot learning solution. Recent deep architectures although exhibit high accuracy under data rich conditions, often show limited transferability under low-label, open-set agricultural conditions. We demonstrate transferability to new domains—including unseen crop classes (e.g., paddy), seasons, and regions (e.g., Piedmont, Italy)—without re-training. Rice paddy fields play a pivotal role in global food security but are also a significant contributor to greenhouse gas emissions, especially methane, and extent mapping is very critical. This work presents a novel perspective on hyperspectral classification and open-set adaptation, suited for sustainable agriculture with limited labels and low-resource domain generalization. Full article

This study examined the seasonal and spatial distribution of heavy metals (Cd, Pb, and Ni) in relation to environmental parameters in five regions of Greater Cairo, Egypt (Helwan, Al-Azhar, Al-Orman, Al-Orman Center, and Al-Moqattam) between 2023 and 2024 using Ficus nitida as a bioindicator. Leaf and soil samples were taken periodically and tested for heavy metal levels, growth factors, chlorophyll, NPK, and moisture content. Concentrations of Cd, Pb, and Ni were highest at Helwan, the industrial site, reaching 0.22 mg/kg, followed by Al-Azhar, a high-traffic urban area, with 0.12 mg/kg, particularly during the summer season. In contrast, the lowest concentrations (0.03 mg/kg) were recorded at Al-Orman Center and Al-Moqattam, both characterized as low-traffic residential zones. A positive correlation was observed between heavy metal concentrations in Ficus nitida leaves and those in the corresponding soils. Additionally, the minimum leaf area was recorded at Helwan during winter, followed by the Al-Azhar region, with values of 36.2 cm² and 41.7 cm², respectively. Reductions in chlorophyll content and nutritional composition were linked to heavy metal levels. Ficus nitida may function as a trustworthy bioindicator of the environmental heavy metal contamination and the health of urban ecosystems, and it accurately reflects soil and air pollution levels. Full article

Storage-oriented reservoir schemes are effective for large-scale hydrological modeling, yet two important limitations remain. First, although some reservoirs seasonally adjust flood storage capacity (FSC), no global study has examined whether constant or seasonally varying FSC performs better. Second, these schemes rely on empirical operational-zone parameterization, but its impact on simulation accuracy has never been systematically assessed. This study presents an open-source Python module integrating three leading storage-oriented schemes (S25, Z17, H22) with both constant and seasonally varying FSC options. Evaluated using daily observations from 289 global reservoirs via Nash-Sutcliffe Efficiency (NSE), constant FSC significantly outperforms seasonal variation, increasing median outflow NSE by 0.18–0.47 and reducing storage error magnitude by 38–61%, and is selected as optimal for 84% of reservoirs. Sensitivity analysis across eight alternative zoning schemes shows that, under constant FSC, outflow remains stable, whereas seasonal FSC sharply increases sensitivity. Storage simulation is more sensitive overall, yet constant FSC consistently yields the smallest errors. This work provides the first global comparison of FSC strategies and the first systematic assessment of operational zone parameter uncertainty. It strongly recommends constant FSC with H22 or S25 as the default for large-scale modeling. The released module offers a flexible, reproducible platform for the community. Future extensions may incorporate demand-driven rules and hybrid calibration to further improve performance in data-rich regions. Full article

Wheat productivity and seed quality are often constrained by nutrient imbalances and environmental stress, which can be mitigated through biostimulants and nanofertilisers. This study evaluated the effects of foliar applications of nanoparticulate sulphur (SNP) and hydrolysed amino acids (AAs) on wheat agronomic performance and seed quality under contrasting environmental conditions in Paraná, Brazil, during the 2022 and 2023 growing seasons. The experiment was conducted in four environments, using a randomised block design, with a 5 × 2 factorial scheme and four replications. Parameters included grain yield, yield components, and physiological and nutritional seed traits. SNP positively influenced the number of grains per ear and spikes per metre, with quadratic responses peaking at 1.048 kg ha⁻¹ for SNP and 0.347 kg ha⁻¹ for S, respectively. However, AAs showed no significant effects, likely due to favourable climatic conditions and high soil fertility. Regarding seed quality, a positive response in seed vigour was observed at 2 kg ha⁻¹ SNP in one environment, while other parameters showed no consistent improvement. Principal component analysis indicated that environment and soil fertility were the main sources of variation in yield and seed quality. Overall, foliar SNP and AA applications did not markedly enhance wheat performance under non-stressful conditions. Full article

The use of Bacillus spp. in combination with mineral fertilizers represents a sustainable alternative to conventional agricultural practices. This study evaluated the effects of inoculation with Bacillus amyloliquefaciens BV03 (Ba) on corn fertilized with phosphorus (P) sources of different solubilities. Two experiments were conducted under greenhouse conditions in a completely randomized design, following a 2 (without and with Ba) × 4 [control (without P, –P), triple superphosphate (TSP), Bayóvar natural phosphate (BNP), and Pratápolis natural phosphate (PNP)] factorial arrangement. Plant growth parameters, chlorophyll a fluorescence, gas exchange, photosynthetic pigments, nutritional status, biomass accumulation, and grain yield were assessed. Corn responses to Ba inoculation varied with P source and season. Inoculation with Ba, Ba + TSP, and Ba + BNP at sowing enhanced biometric traits (height, stem diameter, and leaf area); physiological parameters (F_v’/F_m’, ΦPSII, ETR, E, g_s, WUE); biochemical variables (Chl a, Chl b, and carotenoids); nutritional contents (N, P, K, Ca, and Mg); and yield traits. Overall, our results highlight the potential of Bacillus amyloliquefaciens BV03, alone or in combination with triple superphosphate or Bayóvar natural phosphate, as a sustainable alternative for phosphorus fertilization to improve corn growth and development. Full article

Background: Vitamin D (VD) plays a central role in calcium homeostasis during pregnancy and has been implicated in redox-related biological processes. While VD deficiency (VDD) has been consistently associated with adverse pregnancy outcomes, the relationships between VD insufficiency (VDI), maternal antioxidant-related biomarkers, and neonatal outcomes remain incompletely characterized, particularly during the third trimester. Objective: To determines the prevalence of VDI in third-trimester pregnant women and to examine its associations with antioxidant-related markers and selected neonatal outcomes. Methods: A cross-sectional study was conducted among pregnant women in the third trimester attending a tertiary referral hospital in Mexico City. Maternal serum 25-hydroxyvitamin D (25-OHD) concentrations were measured, along with a panel of redox-related markers, including 2,2-diphenyl-2-2picrylhydrazyl (DPPH) radical scavenging activity, reduced glutathione (GSH), glutathione S-transferase (GST), glutathione peroxidase (GPx), and oxygen radical absorbance capacity (ORAC). Neonatal anthropometric parameters were recorded at birth. Associations between maternal VD status, redox-related markers, environmental factors, and neonatal outcomes were evaluated using appropriate statistical analyses. Results: A high prevalence of VDI was observed in the study population. Maternal VDI was associated with lower activities of GSH, GST, and GPx. Passive exposure to tobacco smoke and season of sampling were also associated with lower VD concentrations. Neonates born to women with VDI had higher birth weight compared with those born to women with sufficient VD concentrations. Maternal serum 25-OHD concentrations correlated positively with selected antioxidant enzyme activities. Conclusions: In this cohort of third-trimester pregnant women, VDI co-occurred with environmental factors, differences in maternal redox-related markers, and selected neonatal outcomes. These findings support an associative framework in which suboptimal VD status during the third trimester is accompanied by variations in redox-related markers. Longitudinal and mechanistic studies are needed to clarify the temporal sequence and biological relevance of these associations. Full article

Grapevines face the dual challenge of sustaining yield and fruit quality under arid and increasingly variable environmental conditions. This study characterized the phenotypic variability and multi-year stability of 49 grapevine (Vitis spp.) accessions conserved in the Chincha germplasm bank over three consecutive growing seasons, with the aim of identifying promising material for table grape, pisco (a traditional grape-based distilled spirit from Peru), and wine production. Morphological traits (cluster weight, berry weight and dimensions), colorimetric parameters (CIELAB), and physicochemical attributes (moisture, dry matter, soluble solids, pH, titratable acidity, maturity index, and reducing sugars) were evaluated. Multivariate analyses (PCA, hierarchical clustering), genotype × environment interaction models (AMMI and GGE), stability indices (ASV and WAASBY), and assessments of interannual stability were applied, together with a multi-criteria selection index tailored to the intended end use. The results revealed two contrasting phenotypic profiles: one characterized by high berry volume/weight and elevated water content and another with smaller berries but higher dry matter, sugars, balanced acidity, and superior maturity indices. Genotypic effects were predominant for size-related traits such as berry weight, whereas titratable acidity and reducing sugars exhibited a more pronounced genotype × year interaction, supporting the use of AMMI models and the WAASBY index to select genotypes that are both productive and stable. The ranking identified accessions PER1002061, PER1002062, and PER1002168 as outstanding candidates for table grape production; PER1002076, PER1002097, and PER1002156 for pisco; and PER1002122, PER1002131, PER1002135, and PER1002098 as accessions with high oenological potential. Overall, these findings highlight the value and diversity of Peruvian grapevine germplasm and provide a foundation for breeding programs targeting varieties adapted to specific market niches, including table grape, wine, and pisco. Full article

The Xiaohai Lagoon is a vital coastal ecosystem that has faced decades of significant natural and anthropogenic pressures. This study investigated the spatio-temporal dynamics its phytoplankton communities through quarterly sampling from 2024 to 2025. Significant spatial and seasonal variations (p < 0.05) in physicochemical parameters were observed. The concentrations of various physicochemical parameters were highest at the lagoon mouth and decreased inwards. In contrast, sites inside the lagoon experienced elevated nutrient and organic matter indicators. Seasonally, the highest temperatures were recorded in Summer. However, Autumn recorded the highest NH₃-N and NO₂-N levels, while Winter recorded the highest NO₃-N levels. The findings generally suggest minimal pollution, as key physicochemical parameters, met the China water quality standard for environmental protection (GB 3838–2002). Overall, 109 phytoplankton species belonging to 38 genera and 5 phyla, including Cyanophyta, Bacillariophyta, Chlorophyta, Cryptophyta, and Dinophyta, were identified. The phytoplankton average density was 1.65 × 10³ Ind L⁻¹ with insignificant differences both spatially and seasonally (p > 0.05). One-way ANOSIM indicated significant seasonal dissimilarity in phytoplankton community composition (R = 0.828, p < 0.001), with SIMPER results revealing that Ceratocorys sp., Chaetoceros sp., Coscinodiscus subtilis, Oscillatoria princes, and Thalassionema nitzschioides contributed to the seasonal difference. CCA indicated phytoplankton composition and abundance were influenced by COD, TN, TDS, salinity, oxidation-reduction potential, EC, water temperature, NH₃-N, and NO₃-N. This study highlights the critical need for effective management strategies to protect and preserve the ecological integrity of Xiaohai Lagoon. Full article