Rapid identification of groundwater sources is crucial for emergency water supplies. Yudu County (YDC) in Southern China serves as a case study due to its typical mountainous terrain and pressing groundwater demands. To address the limitations of conventional groundwater mapping methods in large-scale areas with sparse data, this study integrates remote sensing (RS), geographic information systems (GIS), and multi-criteria decision analysis (MCDA) techniques to delineate groundwater potential zones (GWPZs) in YDC. Following a series of correlation tests, seven assessment indicators were selected from various groundwater influencing factors, including two innovative ones: terrestrial water storage change (TWSC) and spring flow. The analytic hierarchy process (AHP) and fuzzy AHP (FAHP) models were employed to calculate factor weights, and GWPZ maps were generated using weighted overlay analysis in GIS. The model performance was validated using borewell data, receiver operating characteristic (ROC) curves, and yield prediction models. Additionally, four water enrichment types and their spatial distribution were identified by field investigations and yield prediction assessments. Results indicated a remarkable similarity between GWPZs delineated by AHP and FAHP, categorized into five classes: very high (13.92% for AHP and 14.33% for FAHP), high (26.29 and 27.55%), medium (29.33 and 28.14%), low (20.66 and 21.50%), and very low (9.80 and 8.48%). The area under the curve (AUC) for FAHP was 85.09%, slightly higher than the 84.41% of AHP, while the correlation coefficient (R² of the prediction model improved from 0.747 to 0.817 with FAHP. These findings confirmed the reliability of combining GIS and MCDA methods to delineate GWPZs, with FAHP demonstrating an advantage over AHP. The proposed methodology and resulting mapping significantly enhance sustainable water resource management and development in YDC, offering a practical framework for rapid groundwater investigations in disaster response, as well as for long-term water security planning in similar mountainous environments.

The Tibetan Plateau is considered to be one of the best natural laboratories for seismological research. This study sought to determine the spatial variations of b-values in the western part of the Tibetan Plateau, along with its surrounding areas, and the relation with the region’s fault blocks. The study region lies within 27–36.5° N, 78–89° E, and its fracture structure consists of strike-slip faults, as well as normal and thrust faults. A catalog record from 2009–2019 provided 4431 well-centered earthquakes that varied in magnitude from 0.1 to 8.2 M. The record was obtained from China’s seismological network, which is capable of recording low magnitudes to analyze b-values in the study area. The key findings of this study are as follows: (1) the range of earthquake depth in the region was 0–256 km, with the depth histogram showing a high frequency occurrence of shallow earthquakes in the area; (2) a time histogram showed that the major earthquakes occurred between 2014–2015, including the notable 2015 Gorkha earthquake (M = 8.2); (3) the b-value computed in the study area was 0.5 to 1.6, but in most of the study area, the b-value ranged from 0.6 to 0.9, which was a low to intermediate value, due to the presence of strike-slip faults in the central part of the study area and underthrusting in the region (south of the study area); and (4) a high b-value was found in the northwestern and eastern regions of the area, which proved that the area is prone to small earthquakes in the near future. The study also showed that the central and southern areas of the study region had low to intermediate b-values, meaning that it is prone to destructive and massive earthquakes with high magnitudes, such as the Gorkha earthquake (southern part of the study area). Low b-values revealed the degree of variation in rock properties, including large stress and strain, a fractured medium, a high deformation rate, and large faults. Small b-values were observed when the stress level was high in the investigated region, which might be used to predict a massive high-magnitude earthquake in the near future.

Formation flying synthetic aperture radar (FF-SAR) systems, as an important development direction of multichannel SAR, can achieve high-resolution wide-swath (HRWS) imaging. Coherently combining data from satellite receivers puts a strain on traditional real-time processing systems based on individual satellites. Characteristics such as the power of real-time on-orbit processing platform must be properly balanced with constrained memory and parallel computational resources. This paper proposes a distributed SAR real-time imaging method based on embedded Graphics Processing Units (GPUs). The parallel computing method of chirp scaling (CS) algorithm is designed based on parallel programming model of compute unified device architecture (CUDA), and the optimization methods of memory and performance are proposed for the hardware architecture of embedded GPUs. In particular, unified memory management method is used to avoid data copying and communication delays between the CPU and GPU. A hardware verification system for distributed SAR real-time imaging processing based on multiple embedded GPUs is constructed. The proposed algorithm takes 5.86 seconds to process single-precision floating-point complex imaging with a data size of 8192 × 8192 on a single Jetson Nano platform. The actual power consumption is less than 5 W, and the performance-to-power ratio is greater than 1.7%. The experimental results show that the real-time processing method based on embedded GPUs proposed in this paper has high performance and low power consumption.

In this article, an effective clutter suppression and moving target imaging approach is proposed for the geosynchronous-low earth orbit (GEO-LEO) bistatic multichannel synthetic aperture radar (SAR) system, which is robust for the fast moving target with Doppler centroid ambiguity. For the GEO-LEO bistatic multichannel SAR system, the characteristic of baseline with azimuth invariant in Doppler Fourier transform domain is not tenable. It is difficult to implement clutter suppression by the unified baseline compensation in azimuth Doppler Fourier transform domain. Fortunately, we discover that the baseline can be approximately regarded as a constant in chirp Fourier transform domain for the GEO-LEO bistatic multichannel SAR system. Hence, the corresponding baseline compensation can be achieved in the azimuth chirp Fourier transform domain for the clutter. With an orthogonality vector of clutter, the clutter can be well suppressed and the moving target is extracted. After that, the moving target imaging approach is developed with the baseband Doppler centroid estimation and Doppler ambiguity number estimation. Finally, the theoretical investigations and the proposed approach in this article are validated by some experiments, where the experiments for clutter suppression and experiments for fast moving targets are included. Especially, an experiment with real SAR scattering scene is involved. In addition, some discussions for blind velocity targets are presented.

Mianyang City is located in the varied topographic areas of Sichuan Province in southwestern China and is characterized by a complex geological background. This area is prone to disasters and its varied topography is inconvenient for emergency water storage and supply. Groundwater is essential for alleviating the demand for water and post-disaster emergency water supply in this area. This study applied AHP to integrate remote sensing, geological and hydrological data into GIS for the assessment of groundwater potential, providing a plan for the rational exploitation of groundwater and post-disaster emergency water supply in the area. Nine factors, including the spring calibration related to groundwater, were integrated by AHP after multicollinear checks. As a result, the geology-controlled groundwater potential map was classified into five levels with equal intervals. All the results were validated using borehole data, indicating the following: the areas with yield rates of $<1\mathrm{t}/\mathrm{d}·\mathrm{m}$, 1–20 $\mathrm{t}/\mathrm{d}·\mathrm{m}$, and 20–400 $\mathrm{t}/\mathrm{d}·\mathrm{m}$ accounted for 2.66%, 36.1%, and 39.62%, respectively, whereas the areas with yield rates of 400–4000 $\mathrm{t}/\mathrm{d}·\mathrm{m}$ and $>4000\mathrm{t}/\mathrm{d}·\mathrm{m}$ accounted for only 20.88% and 0.75% of the overall area. The flexibility of this quick and efficient method enables its application in other regions with a similar geological background.

Multichannel Synthetic Aperture Radar Ground Moving Target Indication (SAR-GMTI) has been widely used and get great attention nowadays. Traditional adaptive methods like Space-time adaptive processing (STAP) need to calculate and search the maximum of the test statistic pixel by pixel over a large range of radial velocity, which will cause great computational burden. Non-adaptive methods like Displaced Phase Center Antenna (DPCA) will cause signal loss of moving targets, thereby degrading the performance of moving targets detection and radial velocity estimation. To improve the problem mentioned above, this paper proposes a novel two-step scheme based on Greatest Of (GO)-DPCA and Local STAP. In step I, GO-DPCA utilizes the complex images of the channels with different baselines for joint moving target detection. Then in step II, only the local data of moving targets detected in step I needs to be extracted from the original image domain for clutter suppression and radial velocity estimation simultaneously by STAP. Since the processing gain of moving targets depends on the radial velocity and baseline length, the detection performance of moving targets with different radial velocity can be improved by proposed GO-DPCA compared to conventional DPCA. And considering the moving targets usually distribute sparsely in the scene, step II can avoid most computational burden caused by processing pixel by pixel. Finally, the experimental results of both simulated and acquired data are given to validate the effectiveness of the proposed method.