Search Results (1,343)

This study addresses the critical issue of drought zoning in Canada using advanced deep learning techniques. Drought, exacerbated by climate change, significantly affects ecosystems, agriculture, and water resources. Canadian Drought Monitor (CDM) data provided by the Canadian government and ERA5-Land daily data were utilized to generate a comprehensive time series of mean monthly precipitation and air temperature for 199 sample locations in Canada from 1979 to 2023. These data were processed in the Google Earth Engine (GEE) environment and used to develop a Convolutional Neural Network (CNN) model to estimate CDM values, thereby filling gaps in historical drought data. The CanESM5 climate model, as assessed in the IPCC Sixth Assessment Report, was employed under four climate change scenarios to predict future drought conditions. Our CNN model forecasts CDM values up to 2100, enabling accurate drought zoning. The results reveal significant trends in temperature changes, indicating areas most vulnerable to future droughts, while precipitation shows a slow increasing trend. Our analysis indicates that under extreme climate scenarios, certain regions may experience a significant increase in the frequency and severity of droughts, necessitating proactive planning and mitigation strategies. These findings are critical for policymakers and stakeholders in designing effective drought management and adaptation programs. Full article

The upper reaches of the Yellow River are critical ecological barriers within the Yellow River Basin (YRB) that are crucial for source conservation. However, environmental challenges in this area, from Longyangxia to Lijiaxia, have emerged in recent years. To assess the ecological environment quality (EEQ) evolution from 1991 to 2021, we utilized remote sensing ecological indices (RSEIs) on the Google Earth Engine (GEE) platform. Spatial autocorrelation and heterogeneity impacting EEQ changes were examined. The results of this study show that the mean value of the RSEIs fluctuated over time (1991: 0.70, 1996: 0.77, 2001: 0.67, 2006: 0.71, 2011: 0.68, 2016: 0.68, 2016: 0.65, and 2021: 0.66) showing an upward, downward, and then upward trend. The mean values of the overall RSEIs are all at 0.65 and above. Most regions showed no significant EEQ change during 1991–2021 (68.59%, 59.23%, and 55.78%, respectively). Global Moran’s I values (1991–2021) ranged from 0.627 to 0.412, indicating significant positive correlation between EEQ and spatial clustering, and the LISA clustering map (1991–2021) shows that the area near Longyangxia Reservoir shows a pattern of aggregation, dispersion, and then aggregation again. The factor detection results showed that heat was the most influential factor, and the interaction detection results showed that greenness and heat had a significant effect on regional ecosystem distribution. Our study integrates spatial autocorrelation and spatial heterogeneity and combines them with reality to provide an in-depth discussion and analysis of the Longyangxia to Lijiaxia Basin. These findings offer guidance for ecological governance, vegetation restoration, monitoring, and safeguarding the upper Yellow River’s ecological integrity. Full article

Exploring eco-environmental quality dynamics in the Daihai Lake Basin has significant implications for the conservation of ecological environments in the semi-arid and arid regions of northern China. Based on the Google Earth Engine (GEE) platform, the remote sensing ecological index (RSEI) was constructed by coupling Landsat SR remote sensing data from 1985 to 2022. The spatial significance of the RSEI was analyzed using linear regression equations and an F-test. The spatial correlation, distribution characteristics, and driving factors behind the RSEI were explored using Moran’s index and a geodetector. The results indicated that (1) the RSEI was appropriate for evaluating eco-environmental quality in the Daihai Lake Basin. (2) From 1985 to 2022, the eco-environmental quality of the Daihai Lake Basin exhibited a positive trend but remained subpar. (3) A positive spatial autocorrelation was demonstrated for eco-environmental quality with increasing spatial aggregation. (4) Significant eco-environmental quality degradation (slope < 0) occurred primarily in Sanyiquan Town in the northeastern region of the basin and in Tiancheng Township in the southeastern region. Conversely, a notable improvement (slope > 0) was predominantly observed in Yongxing and Liusumu in southwestern Daihai. (5) The improvement in the ecological environment of the Daihai Lake Basin was primarily attributed to an increase in NDVI and WET and a decrease in NDBSI and LST. The interaction between NDVI and LST had the greatest explanatory power for the ecological environment. Among the external driving factors, DEM (elevation) was the dominant factor in the RSEI and had the strongest explanatory power. The interaction between DEM and LST was the most significant, and the driving factors were enhanced. This study provided a theoretical basis for the sustainable development of the Daihai Lake Basin, which is crucial for the local ecological environment and economic development. Full article

Purpose: To evaluate prognostic factors for visual outcome in patients with diabetes who have undergone vitrectomy (PPV) for severe proliferative diabetic vitreoretinopathy (PDVR) in at least one eye in the past 15 years. Methods: Medical records of 132 eyes of 66 patients were analyzed (median age 52 years 21–80; patients with type 1/2 diabetes 40/26; median follow-up 38 months 9–125). Correlations between final favorable visual outcome defined as 0.5≤ best-corrected visual acuity (BCVA) and prognostic factors (age, sex, type and duration of diabetes, metabolic status, BCVA, diabetic retinopathy status, data of preoperative management, data of vitrectomy, and postoperative complications) were analyzed. Results: BCVA improved significantly in the entire study cohort (from median 0.05 min–max 0.001–1 to 0.32, 0.001–1, p < 0.001). Visual stabilization was achieved in the majority of patients, and good visual acuity (0.5 ≤ BCVA) was maintained in more than one-third of the eyes. Multivariable GEE statistics showed that in addition to the duration of diabetes and stable HbA1c values, only preoperative tractional macular detachment proved to be an independent significant predictor of visual outcome. Conclusions: Pars plana vitrectomy is a useful tool when performed early before tractional macular detachment. However, long-term visual stability can only be achieved with good metabolic control. Full article

The IMPACT-FH study implemented strategies (packet, chatbot, direct contact) to promote family member cascade testing for familial hypercholesterolemia (FH). We evaluated the impact of genetic counseling (GC) on medical outcomes, strategy selection, and cascade testing. Probands (i.e., patients with FH) were recommended to complete GC and select sharing strategies. Comparisons were performed for both medical outcomes and strategy selection between probands with or without GC. GEE models for Poisson regression were used to examine the relationship between proband GC completion and first-degree relative (FDR) cascade testing. Overall, 46.3% (81/175) of probands completed GC. Probands with GC had a median LDL-C reduction of −13.0 mg/dL (−61.0, 4.0) versus −1.0 mg/dL (−16.0, 17.0) in probands without GC (p = 0.0054). Probands with and without GC selected sharing strategies for 65.3% and 40.3% of FDRs, respectively (p < 0.0001). Similarly, 27.1% of FDRs of probands with GC completed cascade testing, while 12.0% of FDRs of probands without GC completed testing (p = 0.0043). Direct contact was selected for 47 relatives in total and completed for 39, leading to the detection of 18 relatives with FH. Proband GC was associated with improved medical outcomes and increased FDR cascade testing. Direct contact effectively identified FH cases for the subset who participated. Full article

Spinal muscular atrophy (SMA) is a genetic disorder primarily caused by mutations in the SMN1 gene, leading to motor neuron degeneration and muscle atrophy, affecting multiple organ systems. Nusinersen treatment targets gene expression and is expected to enhance the motor function of voluntary muscles in the limbs and trunk. Motor skills can be assessed through specific scales like the Revised Upper Limb Module Scale (RULM) and Hammersmith Functional Motor Scale Expanded (HFMSE). This study aims to evaluate the influence of nusinersen on the motor skills of patients with SMA Type 2 and 3 using real-world data collected over 54 months. A prospective longitudinal study was conducted on 37 SMA patients treated with nusinersen, analyzing data with R statistical software. The outcomes revealed significant improvements in motor functions, particularly in SMA Type 3 patients with higher RULM and HFSME scores. Additionally, GEE analysis identified time, type, age, and exon deletions as essential predictors of motor score improvements. The extended observation period is both a major strength and a limitation of this research, as the dropout rates could present challenges in interpretation. Variability in responses, influenced by genetic background, SMA type, and onset age, highlights the need for personalized treatment approaches. Full article

Ambient air pollution’s health impacts are well documented, yet the domestic environment remains underexplored. We aimed to compare indoor versus outdoor (I/O) air quality and estimate the association between indoor/ambient fine particulate matter (PM_2.5) exposure and lung function in asthma and chronic obstructive pulmonary disease (COPD) patients. The study involved 24 h monitoring of PM_2.5 levels indoors and outdoors, daily peak expiratory flow (PEF), and biweekly symptoms collection from five patients with asthma and COPD (average age of 50 years, 40% male) over a whole year. Data analysis was performed with linear mixed effect models for PEF and generalized estimating equations (GEE) for exacerbations. More than 5 million PM_2.5 exposure and meteorological data were collected, demonstrating significant I/O PM_2.5 ratio variability with an average ratio of 2.20 (±2.10). Identified indoor PM_2.5 sources included tobacco use, open fireplaces, and cooking, resulting in average indoor PM_2.5 concentrations of 63.89 μg/m³ (±68.41), significantly exceeding revised World Health Organization (WHO) guidelines. Analysis indicated a correlation between ambient PM_2.5 levels and decreased PEF over 0-to-3-day lag, with autumn indoor exposure significantly impacting PEF and wheezing. The study underscores the need to incorporate domestic air quality into public health research and policy-making. A personalized approach is required depending on the living conditions, taking into account the exposure to particulate pollution. Full article

Background: Total energy expenditure (TEE) is the total energy expended by an individual to sustain life, activities, and growth. TEE is formed by four components: resting energy expenditure (REE), activity energy expenditure (AEE), growth-related energy expenditure (GEE), and the thermic effect of feeding (TEF). Some energy expenditure (EE) components may change throughout childhood and cannot be reliably estimated using prediction formulae. Objective: To summarize measured TEE components as reported in the literature in healthy and critically ill children. Methods: We searched MEDLINE, EMBASE, and CINAHL for studies published between 1946 and 7 September 2023. The primary outcome was energy expenditure. Included studies were published in English and measured one or more of TEE, AEE, GEE, and TEF with Indirect Calorimetry or Doubly Labeled Water in participants between 1 month and 18 years of age. We excluded studies reporting only REE or using predictive equations. Following abstraction, reported values were converted into kcal/kg/day or kcal/day as possible. Weighted mean values were calculated using median or means of EE measurements. Results: We found 138 studies, 8163 patients, and 16,636 eligible measurements. The median (IQR) study sample size was 20 (12, 35) patients. TEE was the most evaluated component. The median (IQR) TEE in infants was 73.1 (67.0, 76.5), in children 78.0 (66.0, 81.3), and in adolescents was 44.2 (41.8, 51.9) kcal/kg/day. Very few studies reported on GEE and TEF. Conclusions: This is one of the first studies that summarizes components of total energy expenditure in different pediatric age groups in healthy and critically ill children. Growth- and feeding-associated energy expenditure are poorly reported in healthy children, while all components of TEE (except REE) are poorly reported in critically ill children. Full article

With the global population growth and increasing food demand, the development of precision agriculture has become particularly critical. In precision agriculture, accurately identifying areas of nitrogen stress in crops and planning precise fertilization paths are crucial. However, traditional coverage path-planning (CPP) typically considers only single-area tasks and overlooks the multi-area tasks CPP. To address this problem, this study proposed a Regional Framework for Coverage Path-Planning for Precision Fertilization (RFCPPF) for crop protection UAVs in multi-area tasks. This framework includes three modules: nitrogen stress spatial distribution extraction, multi-area tasks environmental map construction, and coverage path-planning. Firstly, Sentinel-2 remote-sensing images are processed using the Google Earth Engine (GEE) platform, and the Green Normalized Difference Vegetation Index (GNDVI) is calculated to extract the spatial distribution of nitrogen stress. A multi-area tasks environmental map is constructed to guide multiple UAV agents. Subsequently, improvements based on the Double Deep Q Network (DDQN) are introduced, incorporating Long Short-Term Memory (LSTM) and dueling network structures. Additionally, a multi-objective reward function and a state and action selection strategy suitable for stress area plant protection operations are designed. Simulation experiments verify the superiority of the proposed method in reducing redundant paths and improving coverage efficiency. The proposed improved DDQN achieved an overall step count that is 60.71% of MLP-DDQN and 90.55% of Breadth-First Search–Boustrophedon Algorithm (BFS-BA). Additionally, the total repeated coverage rate was reduced by 7.06% compared to MLP-DDQN and by 8.82% compared to BFS-BA. Full article

Snow plays a crucial role in the global water and energy cycles, and its melting process can have a series of impacts on hydrological or climatic systems. Accurately capturing the timing of snowmelt runoff is essential for the utilization of snow resources and the early warning of snow-related disasters. A synthetic aperture radar (SAR) offers an effective means for capturing snowmelt runoff onset dates (RODs) over large areas, but its accuracy under different land cover types remains unclear. This study focuses on the Sierra Nevada Mountains and surrounding areas in the western United States. Using a total of 3117 Sentinel-1 images from 2017 to 2023, we extracted the annual ROD based on the Google Earth Engine (GEE) platform. The satellite extraction results were validated using the ROD derived from the snow water equivalent (SWE) data from 125 stations within the study area. The mean absolute errors (MAEs) for the four land cover types—tree cover, shrubland, grassland, and bare land—are 24, 18, 18, and 16 d, respectively. It indicates that vegetation significantly influences the accuracy of the ROD captured from Sentinel-1 data. Furthermore, we analyze the variation trends in the ROD from 2017 to 2023. The average ROD captured by the stations shows an advancing trend under different land cover types, while that derived from Sentinel-1 data only exhibits an advancing trend in bare land areas. It indicates that vegetation leads to a delayed trend in the ROD captured by using Sentinel-1 data, opposite to the results from the stations. Meanwhile, the variation trends of the average ROD captured by both methods are not significant (p > 0.05) due to the impact of the extreme snowfall in 2023. Finally, we analyze the influence of the SWE on RODs under different land cover types. A significant correlation (p < 0.05) is observed between the SWE and ROD captured from both stations and Sentinel-1 data. An increase in the SWE causes a delay in the ROD, with a greater delay rate in vegetated areas. These findings will provide vital reference for the accurate acquisition of the ROD and water resources management in the study area. Full article

Face swapping or face replacement is a challenging task that involves transferring a source face to a target face while maintaining the target’s facial motion and expression. Although many studies have made a lot of encouraging progress, we have noticed that most of the current solutions have the problem of blurred images, abnormal features, and unnatural pictures after face swapping. To solve these problems, in this paper, we proposed a composite face-swapping generation network, which includes a face extraction module and a feature fusion generation module. This model retains the original facial expression features, as well as the background and lighting of the image while performing face swapping, making the image more realistic and natural. Compared with other excellent models, our model is more robust in terms of face identity, posture verification, and image quality. Full article

This paper presents a remote sensing approach for rapidly and automatically generating maps of surface disturbances caused by landslides on the global scale. Our approach not only identifies the locations of these disturbances but also pinpoints the estimated time of their occurrence. Using the Continuous Change Detection and Classification (CCDC) algorithm within the Google Earth Engine (GEE) platform, we analyzed two decades of Landsat 5, 7, and 8 surface reflectance data. We tested this approach in five landslide-prone regions: Iburi (Japan), Kashmir (Pakistan), Karnataka (India), Porgera (Papua New Guinea), and Pasang Lhamu (Nepal). The results were promising, with R² values ranging up to 0.85, indicating a robust correlation between detected disturbances and actual landslide events compared to manually made inventories. The accuracy metrics further validated our method, with a producer’s accuracy of 75%, a user’s accuracy of 73%, and an F1 score of 75%. Furthermore, the method proved well transferable across different locations. These findings demonstrate the method’s potential as a valuable tool for near real-time and historical analysis of landslide activity, thereby contributing to global disaster management and mitigation efforts. Full article

This study addresses the pressing need for flood extent and exposure information in data-scarce and vulnerable regions, with a specific focus on West Africa, particularly Senegal. Leveraging the Google Earth Engine (GEE) platform and integrating data from the Sentinel-1 SAR, Global Surface Water, HydroSHEDS, the Global Human Settlement Layer, and MODIS land cover type, our primary objective is to delineate the extent of flooding and compare this with flooding for a one-in-a-hundred-year flood event, offering a comprehensive assessment of exposure during the period from July to October 2022 across Senegal’s 14 regions. The findings underscore a total inundation area of 2951 square kilometers, impacting 782,681 people, 238 square kilometers of urbanized area, and 21 square kilometers of farmland. Notably, August witnessed the largest flood extent, reaching 780 square kilometers, accounting for 0.40% of the country’s land area. Other regions, including Saint-Louis, Ziguinchor, Fatick, and Matam, experienced varying extents of flooding, with the data for August showing a 1.34% overlap with flooding for a one-in-a-hundred-year flood event derived from hydrological and hydraulic modeling. This low percentage reveals the distinct purpose and nature of the two approaches (remote sensing and modeling), as well as their complementarity. In terms of flood exposure, October emerges as the most critical month, affecting 281,406 people (1.56% of the population). The Dakar, Diourbel, Thiès, and Saint-Louis regions bore substantial impacts, affecting 437,025; 171,537; 115,552; and 77,501 people, respectively. These findings emphasize the imperative for comprehensive disaster preparation and mitigation efforts. This study provides a crucial national-scale perspective to guide Senegal’s authorities in formulating effective flood management, intervention, and adaptation strategies. Full article

Monitoring areas susceptible to desertification contributes to the strategic development of regions located in environments of extreme hydric and social vulnerability. Therefore, the objective of this study is to evaluate the process of soil degradation in the Desertification Nucleus of Cabrobó (DNC) over the past three decades using remote sensing techniques. This study used primary climatic data from TerraClimate, geospatial data of land use and land cover (LULC), and vegetation indices (SAVI and LAI) via Google Earth Engine (GEE) from Landsat 5/TM and 8/OLI satellites, and established the aridity index (AI) from 1992 to 2022. The results indicated 10 predominant LULC classes with native vegetation suppression, particularly in agriculture and urbanization. SAVI ranged from −0.84 to 0.90, with high values influenced by La Niña episodes and increased rainfall; conversely, El Niño episodes worsened the rainfall regime in the DNC region. Based on the Standardized Precipitation Index (SPI), it was possible to correlate normal and severe drought events in the DNC with years under the influence of El Niño and La Niña phases. In summary, the AI images indicated that the DNC remained semi-arid and that the transition to an arid region is a cyclical and low-frequency phenomenon, occurring in specific periods and directly influenced by El Niño and La Niña phenomena. The Mann–Kendall analysis showed no increasing trend in AI, with a Tau of −0.01 and a p-value of 0.97. During the analyzed period, there was an increase in Non-Vegetated Areas, which showed a growing trend with a Tau of 0.42 in the Mann–Kendall analysis, representing exposed soil areas. Annual meteorological conditions remained within the climatic pattern of the region, with annual averages of precipitation and actual evapotranspiration (ETa) close to 450 mm and an average temperature of 24 °C, showing changes only during El Niño and La Niña events, and did not show significant increasing or decreasing trends in the Mann–Kendall analysis. Full article

Understanding the dynamics of water bodies is crucial for managing water resources and protecting ecosystems, especially in regions prone to climatic extremes. The Tumen River Basin, a transboundary area in Northeast Asia, has seen significant water body changes influenced by natural and anthropogenic factors. Using Landsat 8 and Sentinel-1 data on Google Earth Engine, we systematically analyzed the spatiotemporal variations and drivers of water body changes in this basin from 2015 to 2023. The water body extraction process demonstrated high accuracy, with overall precision rates of 95.75% for Landsat 8 and 98.25% for Sentinel-1. Despite observed annual fluctuations, the overall water area exhibited an increasing trend, notably peaking in 2016 due to an extraordinary flood event. Emerging Hot Spot Analysis revealed upstream areas as declining cold spots and downstream regions as increasing hot spots, with artificial water bodies showing a growth trend. Utilizing Random Forest Regression, key factors such as precipitation, potential evaporation, population density, bare land, and wetlands were identified, accounting for approximately 81.9–85.3% of the observed variations in the water body area. During the anomalous flood period from June to September 2016, the Geographically Weighted Regression (GWR) model underscored the predominant influence of precipitation, potential evaporation, and population density at the sub-basin scale. These findings provide critical insights for strategic water resource management and environmental conservation in the Tumen River Basin. Full article