Gridded precipitation data with a high spatiotemporal resolution are of great importance for studies in hydrology, meteorology, and agronomy. Observational data from meteorological stations cannot accurately reflect the spatiotemporal distribution an...
Rainfall is one of the most basic meteorological and hydrological elements. Quantitative rainfall estimation has always been a common concern in many fields of research and practice, such as meteorology, hydrology, and environment, as well as being o...
This study developed a satellite, reanalysis, and gauge data merging model for daily-scale analysis using a random forest algorithm in Sichuan province, characterized by complex terrain. A high-precision daily precipitation merging dataset (MSMP) wit...
Urban residential greening provides opportunities for social integration and physical exercise. These activities are beneficial to promoting citizens’ mental health, relieving stress, and reducing obesity and violent crimes. However, how to mea...
Climate data derived from long-term, multisource altimeter significant wave height (SWH) measurements are more valuable than those obtained from a single altimeter source. Such data facilitate exploration of long-term air–sea momentum transfer...
High accuracy and a high spatiotemporal resolution of precipitation are essential for the hydrological, ecological, and environmental fields. However, the existing daily gridded precipitation datasets, such as remote sensing products, are limited bot...
Flood monitoring in the Chaohe River Basin is crucial for the timely and accurate forecasting of flood flow. Hydrological models used for the simulation of hydrological processes are affected by soil moisture (SM) data and uncertain model parameters....
The recently developed gauge-radar-satellite merged hourly precipitation dataset (CMPAS-NRT) offers broad applications in scientific research and operations, such as intelligent grid forecasting, meteorological disaster monitoring and warning, and nu...
Precipitation plays a vital role in the hydrological cycle, directly affecting water resource management and influencing flood and drought risk prediction. This study proposes a Bayesian Model Averaging (BMA) framework to integrate multiple precipita...
Precipitation products play an important role in monitoring rainstorm processes. This study takes a rare historical event of extreme, heavy precipitation that occurred in Henan Province, China, in July 2021 as a research case. By analyzing the distri...
Precipitation is a key component of the water cycle. Different precipitation data sources have strengths and weaknesses. To combine these strengths and achieve accurate precipitation data, this study introduces a dual-layer neural network (D-ConvLSTM...
The authors wish to make the following corrections to this paper [...]
25 October 2022
Accurately estimating the spatial and temporal distribution of precipitation is crucial for hydrological modeling. However, precipitation products based on a single source have their advantages and disadvantages. How to effectively combine the advant...
The sensing system consisting of Light Detection and Ranging (LiDAR) and a camera provides complementary information about the surrounding environment. To take full advantage of multi-source data provided by different sensors, an accurate fusion of m...
Satellite and reanalysis precipitation estimates of high quality are widely used for hydrological modeling, especially in ungauged or data-scarce regions. To improve flood simulations by merging different precipitation inputs or directly merging stre...
The Jinsha River Basin constitutes the largest hydropower base in China. However, its complex terrain results in insufficient accurate data support for numerical forecasts, leading to low accuracy in precipitation predictions. To investigate the spat...
To deal with the complexities associated with the rapid growth in a merged concept lattice, a formal method based on an entropy-based weighted concept lattice (EWCL) is proposed as a mechanism for merging multi-source geographic ontologies (geo-onto...
Sea surface temperature (SST) is vital for climate monitoring and extreme weather forecasting. Existing global SST datasets are typically provided at daily to seasonal resolutions, while hourly data remain limited to regional scales. Polar-orbiting s...
Obtaining precipitation estimates with high resolution and high accuracy is critically important for regional meteorological, hydrological, and other applications. Although satellite precipitation products can provide precipitation fields at various...
Following the occurrence of a substation fault, alarm systems frequently exhibit issues such as high-density redundancy, spurious alerts, undetected alarms, and temporal inconsistencies. In addition, the effective integration of heterogeneous multi-s...
The interpretation of geophysical multi-attribute surveys is often subjective and complicated by large datasets, prompting the need for automated fusion methods that preserve structures and enhance anomalies. This study introduces an image fusion app...
Based on the long series of gauge rainfall data from 1979 to 2015, the performance of Multi-Source Weighted-Ensemble Precipitation (MSWEP) precipitation dataset in the Zhoushan Archipelago and its surrounding sea area in Southeast China was evaluated...
We present a new automatic procedure for updating digital topographic data from multi-source satellite imagery, which consists in the production of Digital Surface Models (DSMs) from high resolution optical satellite images, followed by a context-awa...
Satellite remote sensing precipitation is useful for many hydrological and meteorological applications such as rainfall-runoff forecasting. However, most studies have focused on the use of satellite precipitation on daily, monthly, or larger time sca...
Many radar-gauge merging methods have been developed to produce improved rainfall data by leveraging the advantages of gauge and radar observations. Two popular merging methods, Regression Kriging and Bayesian Regression Kriging were utilized and com...
Seat selection in learning spaces intuitively reflects user preferences for micro-environments and facilities. To address the lack of integrated analysis of multi-dimensional factors in existing research, this study constructs a framework merging mul...
Climate wave data, derived from significant wave height (SWH) altimetry, provide accurate information towards nearshore and coastal areas. Their use is crucial to enhance our capabilities of observing, understanding, and forecasting storm waves, even...
Accurate precipitation estimation is essential for hydrological modeling and water resource management in arid regions; however, complex terrain and sparse meteorological station networks introduce substantial uncertainties into gridded precipitation...
Effectively simulating the variation in suspended sediment concentration (SSC) in estuaries during typhoons is significant for the water quality and ecological conditions of estuarine shoal wetlands and their adjacent coastal waters. During typhoons,...
Accurate estimation of global terrestrial evapotranspiration (ET) is fundamental for understanding the Earth’s water and energy cycles, yet existing multi-source ET products inevitably contain uncertainties that require spatially explicit chara...
Multi-scale object matching is the key technology for upgrading feature cascade and integrating multi-source spatial data. Considering the distinctiveness of data at different scales, the present study selects residential areas in a multi-scale datab...
Vector road networks are vital components of intelligent transportation systems and electronic navigation maps. There is a pressing need for efficient and rapid dynamic updates for road network data. In this paper, we propose a series of methods desi...
As satellite rainfall data has the advantages of wide spatial coverage and high spatial and temporal resolution, it is an important means to solve the problem of flood forecasting in ungauged basins (PUB). In this paper, two catchments under differen...
In recent decades, the application of GIS and RS in archaeological and cultural heritage (ACH) has witnessed a notable surge both in terms of quantity and scope. During the initial implementation period (2016–2021) of the Digital Belt and Road...
Bearing in mind the stringent problem of limited and inefficiently used radio resources, a multi-source mechanism for the dynamic adjustment of occupied frequency bands is proposed. Instead of relying only on radio-related information, the system tha...
High-spatiotemporal resolution soil moisture (SM) plays an essential role in optimized irrigation, agricultural droughts, and hydrometeorological model simulations. However, producing high-spatiotemporal seamless soil moisture products is challenging...
To improve the efficiency, accuracy, and intelligence of target detection and recognition, multi-sensor information fusion technology has broad application prospects in many aspects. Compared with single sensor, multi-sensor data contains more target...
In recent years, there is an exponential explosion of data generation, collection, and processing in computer networks. With this expansion of data, network attacks have also become a congenital problem in complex networks. The resource utilization,...
Reliable precipitation data are essential for studying water cycle patterns and climate change. However, there are always temporal or spatial errors in precipitation data from various sources. Most precipitation fusion methods are influenced by high-...
Precipitation monitoring is important for earth system modeling and environmental management. Low spatial representativeness limits gauge measurements of rainfall and low spatial resolution limits satellite-derived rainfall. SM2RAIN-based products, w...
Based on the high-density gauged rainfall, the geographically weighted regression (GWR) was used to fuse the daily precipitation of rain gauges with those of Multi-source Weighted-Ensemble Precipitation V2.1 (MSWEP V2.1) and a new merged daily precip...
Mesoscale convective systems (MCSs) are organized convective precipitation regions that produce severe weather hazards, including heavy rainfall, flooding, and strong winds. Objective identification and tracking remain essential for MCS statistical a...
Tree species classification based on multi-source remote sensing data is essential for ecological evaluation, environmental monitoring, and forest management. The optimization of classification features and the performance of classification methods a...
Improving the accuracy of DEMs is a critical goal in digital terrain analysis. The combination of multi-source data can be used to increase DEM accuracy. Five typical geomorphic study areas in the Loess Plateau in Shaanxi were selected for a case stu...
A quantitative precipitation estimate (QPE) provides basic information for the modelling of many kinds of hydro-meteorological processes, e.g., as input to rainfall-runoff models for flash flood forecasting. Weather radar observations are crucial in...
Ensuring road safety is heavily reliant on the effective maintenance of vehicles. Accurate predictions of maintenance requirements can substantially reduce ownership costs for vehicle owners. Consequently, this field has attracted increasing attentio...
Against the background of intensified climate change and enhanced human activities, the occurrence mode of landslides is becoming more complex and changeable, showing a trend of clustering, contiguous, and frequent occurrences. Yining County is locat...
The ability to build more robust clustering from many clustering models with different solutions is relevant in scenarios with privacy-preserving constraints, where data features have a different nature or where these features are not available in a...
Accurate estimation of aboveground biomass (AGB) in dryland savanna woodlands is constrained by sparse field data, which has motivated widespread fusion of field plots with spaceborne LiDAR reference data from the Global Ecosystem Dynamics Investigat...
Ensuring the security of germplasm resources is of great significance for the sustainable development of agriculture and ecological balance. By combining the morphological characteristics of maize seeds with hyperspectral data, maize variety classifi...
of 3