Search Results (100)

This study presents a comprehensive spatiotemporal assessment of climatic and bioclimatic conditions across Türkiye for both a historical reference period (1995–2014) and future projections (2020–2099) under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) scenarios using the regional climate model (RCM) COSMO-CLM to downscale large-scale signals to a regional scale at high resolution (0.11). A comparison of the model with ERA5-Land reanalysis data revealed annual biases of +1.41 °C (warm) and −0.28 mm/day (dry), emphasizing the importance of bias correction in regional climate assessments. Bias-corrected future projections indicate a marked warming trend and significant decline in precipitation, especially after the 2060s, with pronounced spatial variability across regions. The most intense warming period of the century is the 2060–2079 period, with an anticipated increase of 0.109 °C/year under the SSP3-7.0 scenario, while, under the SSP2-4.5, it is the 2040–2059 period with an increase of 0.068 °C/year. Bioclimatic variables further illustrate shifts in temperature extremes, seasonal variability, and precipitation patterns. Coastal regions are expected to experience a delay in the onset of wet seasons of 1–2 months, while high-altitude zones show earlier shifts of up to 4 months. Four distinct clusters were identified by using k-means clustering method, each with unique temporal and spatial evolution under both SSP scenarios. Clusters 1 and 2, which predominantly represent continental and interior regions, exhibit a strong association with earlier precipitation onset. Notably, arid and semi-arid conditions expand northward, replacing temperate zones in Central Anatolia. Overall, findings suggest that Türkiye is undergoing a substantial climatic transition toward hotter and drier conditions, regardless of the emission scenario. This study has critical implications for ecological resilience, agricultural sustainability, and water resource management, and offers valuable information for targeted climate adaptation strategies and land-use planning in vulnerable regions of Türkiye. Full article

Multi-modal remote sensing image (MRSI) matching suffers from severe nonlinear radiometric distortions and geometric deformations, and conventional feature-based techniques are generally ineffective. This study proposes a novel and robust MRSI matching method using the side window filter (MSWF). First, a novel side window scale space is constructed based on the side window filter (SWF), which can preserve shared image contours and facilitate the extraction of feature points within this newly defined scale space. Second, noise thresholds in phase congruency (PC) computation are adaptively refined with the Weibull distribution; weighted phase features are then exploited to determine the principal orientation of each point, from which a maximum index map (MIM) descriptor is constructed. Third, coarse position, orientation, and scale information obtained through global matching are employed to estimate image-pair geometry, after which descriptors are recalculated for precise correspondence search. MSWF is benchmarked against eight state-of-the-art multi-modal methods—six hand-crafted (PSO-SIFT, LGHD, RIFT, RIFT2, HAPCG, COFSM) and two learning-based (CMM-Net, RedFeat) methods—on three public datasets. Experiments demonstrate that MSWF consistently achieves the highest number of correct matches (NCM) and the highest rate of correct matches (RCM) while delivering the lowest root mean square error (RMSE), confirming its superiority for challenging MRSI registration tasks. Full article

The study examines the impacts of climate change on the operation and capacity of the combined sewer network in the historic center of Thessaloniki, Greece. Rainfall data from three high-resolution Regional Climate Models (RCMs), namely (a) the Cosmo climate model (CCLM), (b) the regional atmospheric climate model (RACMO) and (c) the regional model (REMO), from the MED-CORDEX initiative with future estimations based on Representative Concentration Pathway (RCP) 4.5, are first corrected for bias based on existing measurements in the study area. Intensity–duration–frequency (IDF) curves are then constructed for future data using a temporal downscaling approach based on the scaling of the Generalized Extreme Value (GEV) distribution to derive the relationships between daily and sub-daily precipitation. Projected rainfall events associated with various return periods are subsequently developed and utilized as input parameters for the hydrologic–hydraulic model. The simulation results for each return period are compared with those of the current climate, and the projections from various RCMs are ranked according to their impact on the combined sewer network and overflow volumes. In the short term (2020–2060), the CCLM and REMO project a decrease in CSO volumes compared to current conditions, while the RACMO predicts an increase, highlighting uncertainties in short-term climate projections. In the long term (2060–2100), all models indicate a rise in combined sewer overflow volumes, with CCLM showing the most significant increase, suggesting escalating pressure on urban drainage systems due to more intense rainfall events. Based on these findings, it is essential to adopt mitigation strategies, such as nature-based solutions, to reduce peak flows within the network and alleviate the risk of flooding. Full article

The electrocardiogram (ECG) is one of the widespread diagnostic methods used in telemedicine. However, in the telemedicine systems, the data transfer process to the end user may suffer from security risks. Reversible watermarking can preserve the security of electrocardiograms and keep their original precision for correct diagnostics. In this paper, we present an extensive investigation of four reversible watermarking methods: prediction error expansion (PEE), reversible contrast mapping difference expansion (RCM), integer transform-based difference expansion (ITB), and compression-based watermarking. We discover new facets of the existing ECG watermarking methods (PEE and compression-based watermarking) and adapt image watermarking methods (RCM and ITB) to ECG signal. We compare different kinds of prediction and compression methods used in the studied methods and provide a watermark capacity comparison for different methods’ implementations. The research results will help in watermarking method selection in practice. Full article

In the coming decades, crop production in regions such as the Mediterranean Basin is expected to be influenced by climate change. This study evaluates the impacts of climate change on maize yield and irrigation water in Northern Greece for the mid-21st century and late 21st century using CropSyst, a cropping systems simulation model. Data from a two-year field experiment with maize, in 2016 and 2017, were used to calibrate and validate CropSyst. RCP4.5 and RCP8.5 climate change scenarios were employed, derived from three Regional Climate Models (RCMs), for two future periods (2030–2050 and 2080–2100) and the baseline period (1980–2000). The RCMs used in this study were derived from the Rossby Centre regional atmospheric model (RCA4), which downscaled three General Circulation Models (GCMs), CNRM-CM5, CM5A-MR, and HadGEM2-ES, as part of the Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX) for the European domain. Results indicate that changes in climate variables will exert potential pressure on full irrigation water requirements, leading to both increases and decreases in irrigation amounts, with varying magnitudes of change. Yield impacts vary depending on the climate change scenario and climate model, with CropSyst predictions indicating both positive and negative effects on maize yield under full irrigation. The combined effects of increased temperatures, reduced precipitation, and elevated CO₂ concentrations under the high-emission scenario RCP8.5 by the late 21st century resulted in substantial declines in maize yields. The study identifies the key factor influencing maize yield in future periods as the combined changes in climate variables under CO₂ concentration enrichment, which lead to alterations in full irrigation water requirements, highlighting the multiparameter nature of impact assessment on agricultural production in Northern Greece under various future climate scenarios. Full article

Droughts are caused either by a deficiency in precipitation compared to normal levels or by excessive evapotranspiration exceeding long-term averages. Therefore, assessing future drought prevalence based on projected climatic variables is essential for effective drought preparedness. In this study, an ensemble of three Regional Climate Models (REMO2009, RCA4, and CCLM4-8-17) was used for Representative Concentration Pathways (RCP 4.5 and RCP 8.5), covering two future time periods (2025–2069 and 2070–2100). The quantile distribution mapping technique was employed to bias-correct the RCMs. The ensemble of RCMs projected an increase in rainfall, ranging from 40% to 85% under both RCP 8.5 and RCP 4.5. Both RCPs indicated an increase in daily average temperatures. RCP 4.5 projects an increase in average daily temperature by 1% between 2025 and 2069 and 6.5% between 2070 and 2100, while under RCP 8.5, temperatures are expected to rise by 3.7% between 2025 and 2069 and 12.7% between 2070 and 2100. The Standard Precipitation Index (SPI) was used to translate these projected climatic anomalies into future drought prevalence. The results suggest that RCP 4.5 forecasts an 8% increase in drought prevalence, while RCP 8.5 projects an 11% increase in drought frequency, with a greater rise in moderate and severe droughts and a decrease in extreme drought occurrences. Full article

As a special microwave detection system, multistatic radar has obvious advantages in covert operation, anti-jamming, and anti-stealth due to its configuration of spatial diversity. As a high-orbit irradiation source, a geosynchronous orbit satellite (GEO) has the advantages of a low revisit period, large beam coverage area, and stable power of ground beam compared with traditional passive radar irradiation sources. This paper focuses on the key technologies of flight target detection in multistatic radar based on geosynchronous orbit satellite irradiation with one transmitter and multiple receivers. We carry out the following work: Firstly, we aim to address the problems of low signal-to-noise ratio (SNR) and range cell migration of high-speed cruise targets. The Radon–Fourier transform constant false alarm rate detector-range cell migration correction (RFT-CFAR-RCMC) is adopted to realize the coherent integration of echoes with range cell migration correction (RCM) and Doppler phase compensation. It significantly improves the SNR. Furthermore, we utilize the staggered PRF to solve the ambiguity and obtain multi-view data. Secondly, based on the aforementioned target multi-view detection data, the linear least square (LLS) multistatic positioning method combining bistatic range positioning (BR) and time difference of arrival positioning (TDOA) is used, which constructs the BR and TDOA measurement equations and linearizes by mathematical transformation. The measurement equations are solved by the LLS method, and the target positioning and velocity inversion are realized by the fusion of multistatic data. Finally, using target positioning data as observation values of radar, the Kalman filter (KF) is used to achieve flight trajectory tracking. Numerical simulation verifies the effectiveness of the proposed process. Full article

This work aims to examine the effect of bias correction (BC) methods on the development of Intensity–Duration–Frequency (IDF) curves under climate change at multiple temporal scales. Daily outputs from a 9-member CORDEX-CA GCM-RCM multi-model ensemble (MME) under RCP 8.5 were used to represent future precipitation. Two stationary BC methods, empirical quantile mapping (EQM) and gamma-pareto quantile mapping (GPM), along with three non-stationary BC methods, detrended quantile mapping (DQM), quantile delta mapping (QDM), and robust quantile mapping (RQM), were selected to adjust daily biases between MME members and observations from the SJO weather station located in Costa Rica. The equidistant quantile-matching (EDQM) temporal disaggregation method was applied to obtain future sub-daily annual maximum precipitation series (AMPs) based on daily projections from the bias-corrected ensemble members. Both historical and future IDF curves were developed based on 5 min temporal resolution AMP series using the Generalized Extreme Value (GEV) distribution. The results indicate that projected future precipitation intensities (2020–2100) vary significantly from historical IDF curves (1970–2020), depending on individual GCM-RCMs, BC methods, durations, and return periods. Regardless of stationarity, the ensemble spread increases steadily with the return period, as uncertainties are further amplified with increasing return periods. Stationary BC methods show a wide variety of trends depending on individual GCM-RCM models, many of which are unrealistic and physically improbable. In contrast, non-stationary BC methods generally show a tendency towards higher precipitation intensities as the return period increases for individual GCM-RCMs, despite differences in the magnitude of changes. Precipitation intensities based on ensemble means are found to increase with the change factor (CF), ranging between 2 and 25% depending on the temporal scale, return period, and non-stationary BC method, with moderately smaller increases for short-durations and long-durations, and slightly higher for mid-durations. In summary, it can be concluded that stationary BC methods underperform compared to non-stationary BC methods. DQM and RQM are the most suitable BC methods for generating future IDF curves, recommending the use of ensemble means over ensemble medians or individual GCM-RCM outcomes. Full article

Background/Objectives: Facial pigmented skin lesions are extremely common, starting from the fourth to fifth decades, especially in South-European countries, often located in the periorbital region. These include malignant forms, Lentigo maligna (LM) and lentigo maligna melanoma (LMM), characterized by growing incidence, and a series of benign simulators, including solar lentigo (SL), pigmented actinic keratosis (PAK), seborrheic keratosis (SK) and lichen planus-like keratosis (LPK). The clinical differential diagnosis of atypical pigmented skin lesions (aPFLs) can be difficult, even for dermatologists, leading to inappropriate skin biopsies with consequent aesthetic impacts. Dermoscopy of the facial area is a specific dermoscopic field that requires dedicated training and proved to increase diagnostic accuracy in dermatologists. Since these lesions are often seen by ophthalmologists at first, we aimed to evaluate the effect of a focused dermoscopy training course on a group of ophthalmologists naïve to the use of a dermatoscope. Methods: A set of 80 periorbital pigmented skin lesions with both clinical and dermoscopic images was selected and evaluated by six ophthalmologists before and after a one-day intensive dermoscopic training course. They were required to evaluate 80 periorbital lesions one month before and after a one-day intensive dermoscopic training course, illustrating second-level diagnostic options such as reflectance confocal microscopy (RCM), obtaining a total of 480 evaluations. Specifically, they had to provide, for each case, a punctual diagnosis and a management option among dermoscopic follow-up/skin biopsy/RCM/LC-OCT. Descriptive statistics were carried out, and the accuracy (ACC), sensitivity (SE), and specificity (SP), with their 95% confidence interval (95% CI), were estimated. Results: In the pre-course test, ophthalmologists achieved 84.0% SP, 33.3% SE and 63.7% ACC, while after the course, SE increased by +9% (i.e., 41.7%), SP decreased by 4%, and ACC remained comparable, i.e., 64.6%. In the management study, the percentage of benign lesions for which a close dermoscopic follow-up was suggested significantly decreased (51.6% versus 22.2%), in parallel with an increase in the number of lesions referred for RCM. As for malignant cases, the reduction in responses “close dermoscopic follow-up” decreased from 37.0% to 9.9%, (−27%), in favor of RCM (+15%) and skin biopsy (+12%). Conclusions: The ophthalmologists proved to be very receptive in quickly metabolizing and putting into practice the concepts learned during the one-day intensive dermoscopy training course. Indeed, after only a one-day lesson, they were able to increase their SE by 9% and to improve their management strategy. The present findings highlight the importance of providing training ophthalmologists in dermoscopy during residency programs, in terms of benefits for the correct patient care. Full article

Bias in regional climate model (RCM) data makes bias correction (BC) a necessary pre-processing step in climate change impact studies. Among a variety of different BC methods, quantile mapping (QM) is a popular and powerful BC method. Studies have shown that QM may be vulnerable to reductions in calibration sample size. The question is whether this also affects the climate change signal (CCS) of the RCM data. We applied four different QM methods without subsampling and with three different subsampling timescales to an ensemble of seven climate projections. BC generally improved the RCM data relative to observations. However, the CCS was significantly modified by the BC for certain combinations of QM method and subsampling timescale. In conclusion, QM improves the RCM data that are fundamental for climate change impact studies, but the optimal subsampling timescale strongly depends on the chosen QM method. Full article

When a synthetic aperture sonar (SAS) system operates under low-frequency broadband conditions, the azimuth range coupling of the point target reference spectrum (PTRS) is severe, and the high-resolution imaging range is limited. To solve the above issue, we first convert multi-receivers’ signal into the equivalent monostatic signal and then divide the equivalent monostatic signal into range subblocks and the range frequency subbands within each range subblock in order. The azimuth range coupling terms are converted into linear terms based on piece-wise linear approximation (PLA), and the phase error of the PTRS within each subband is less than π/4. Then, we use the chirp-z transform (CZT) to correct range cell migration (RCM) to obtain low-resolution results for different subbands. After RCM correction, the subbands’ signals are coherently summed in the range frequency domain to obtain a high-resolution image. Finally, different subblocks are concatenated in the range time domain to obtain the final result of the whole swath. The processing of different subblocks and different subbands can be implemented in parallel. Computer simulation experiments and field data have verified the superiority of the proposed method over existing methods. Full article

The unknown relative motions between synthetic aperture radar (SAR) and a ground moving target will lead to serious range cell migration (RCM) and Doppler frequency spread (DFS). The energy of the moving target will defocus, given the effect of the RCM and DFS. The moving target will easily produce Doppler ambiguity, due to the low pulse repetition frequency of radar, and the Doppler ambiguity complicates the corrections of the RCM and DFS. In order to address these issues, an efficient ground moving target focusing method for SAR based on scaled Fourier transform and scaled inverse Fourier transform is presented. Firstly, the operations based on the scaled Fourier transform and scaled inverse Fourier transforms are presented to focus the moving targets in consideration of Doppler ambiguity. Subsequently, in accordance with the detailed analysis of multiple target focusing, the spurious peak related to the cross term is removed. The proposed method can accurately eliminate the DFS and RCM, and the well-focused result of the moving target can be achieved under the complex Doppler ambiguity. Then, the blind speed sidelobe can be further avoided. The presented method has high computational efficiency without the step of parameter search. The simulated and measured SAR data are provided to demonstrate the effectiveness of the developed method. Full article

In 3D microsphere tracking, unlike in-plane motion that can be measured directly by a microscope, axial displacements are resolved by optical interference or a diffraction model. As a result, the axial results are affected by the environmental noise. The immunity to environmental noise increases with measurement accuracy and the signal-to-noise ratio (SNR). In compound digital holography microscopy (CDHM)-based measurements, precise identification of the tracking marker is critical to ensuring measurement precision. The reconstruction centering method (RCM) was proposed to suppress the drawbacks caused by installation errors and, at the same time, improve the correct identification of the tracking marker. The reconstructed center is considered to be the center of the microsphere, rather than the center of imaging in conventional digital holographic microscopy. This method was verified by simulation of rays tracing through microspheres and axial moving experiments. The axial displacements of silica microspheres with diameters of 5 μm and 10 μm were tested by CDHM in combination with the RCM. As a result, the SNR of the proposed method was improved by around 30%. In addition, the method was successfully applied to axial displacement measurements of overlapped microspheres with a resolution of 2 nm. Full article

Future climate scenarios based on regional climate models (RCMs) have been evaluated widely. However, the use of RCMs without bias correction may increase the uncertainty in the assessment of climate change impacts, especially in mountain areas. Five quantile mapping methods (QMMs) were evaluated as bias correction methods for precipitation and temperature in the historical period (1979–2005) of one local climate model and three RCMs at the Achibueno River Basin, southcentral Chile. Additionally, bias-corrected climate scenarios from 2025 to 2050 under two Representative Concentration Pathways (RCPs) were evaluated on the hydrological response of the catchment with the Soil and Water Assessment Tool (SWAT+). The parametric transformation function and robust empirical quantile were the most promising bias correction methods for precipitation and temperature, respectively. Climate scenarios suggest changes in the frequency and amount of precipitation with fluctuations in temperatures. Under RCP 2.6, partial increases in precipitation, water yield, and evapotranspiration are projected, while for RCP 8.5, strong peaks of precipitation and water yield in short periods of time, together with increases in evapotranspiration, are expected. Consequently, flooding events and increasing irrigation demand are changes likely to take place. Therefore, considering adaptation of current and future management practices for the protection of water resources in southcentral Chile is mandatory. Full article

An airborne bistatic radar working in downward-looking mode confronts two major challenges for low-altitude target detection. One is range cell migration (RCM) and Doppler migration (DM) resulting from the relative motion of the radar and target. The other is the non-stationarity characteristic of clutter due to the radar configuration. To solve these problems, this paper proposes a joint implementation method based on sub-aperture processing to achieve clutter suppression and coherent maneuvering target detection. Specifically, clutter Doppler compensation and sliding window processing are carried out to realize sub-aperture space–time processing, removing the clutter non-stationarity resulting from the bistatic geometric configuration. Thus, the output matrix of clutter suppression in the sub-aperture could be obtained. Then, the elements with the same phase of this matrix are superimposed and rearranged to achieve the reconstructed 2-D range-pluse echo matrix. Next, the aperture division with respect to slow time is conducted and the RCM correction based on modified location rotation transform (MLRT) and coherent integration (CI) are realized within each sub-aperture. Finally, the matched filtering process (MFP) is applied to compensate for the RCM/DM among different sub-apertures to coherently integrate the maneuvering target energy of all sub-apertures. The simulation and measured data processing results prove the validity of the proposed method. Full article