Thornthwaite’s water balance approach serves as a fundamental tool for assessing hydrological dynamics, particularly in regions vulnerable to aridity and water stress. This study evaluates the performance of gridded datasets in estimating Thorn...
Accurate spatial and temporal representation of precipitation is of utmost importance for hydrological applications. Uncertainties in available data sets increase with spatial resolution due to small-scale processes over complex terrain. As previous...
Racial geography, mapping spatial distributions of different racial groups, is of keen interest in a multiracial society like the United States. A racial dot map is a method of visualizing racial geography, which depicts spatial distribution, populat...
We developed a mechanism for seamlessly providing weather data and long-term historical climate data from a gridded data source through an international standard web API, which was the Sensor Observation Service (SOS) defined by the Open Geospatial C...
The increasing availability of high-resolution gridded meteorological data poses significant challenges for efficient storage and rapid data access. This study proposes a route-aware adaptive variable-resolution storage (AVRS) strategy for gridded me...
This study assessed the uncertainty in the spatial pattern of rainfall trends in six widely used monthly gridded rainfall datasets for 1979–2010. Bangladesh is considered as the case study area where changes in rainfall are the highest concern due to...
In this study, 10 min and 2 km high-resolution blended fog data (HRBFD) were generated using grid visibility data (GVD) and data from a GK2A (GEO-KOMPSAT-2A) fog product (GKFP) in Korea. As the blending method, the decision tree method (DTM) was used...
Agrometeorological models are great tools for predicting yields and improving decision-making. High-quality climatic data are essential for using these models. However, most developing countries have low-quality data with low frequency and spatial co...
Large-scale gridded climatic data can be useful for the assessment of climate variability and change as a basis for understanding and monitoring natural hazards, as well as for determining appropriate coping strategies. However, an evaluation of the...
The state-of-art satellite observations of atmospheric aerosols over the last two decades from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) instruments have been extensively utilized in climate change and air quality research an...
The evaluation of community livability quantifies the demands of human settlement at the micro scale, supporting urban governance decision-making at the macro scale. Big data generated by the urban management of government agencies can provide an acc...
The aim of this paper was to present a precipitation trend analysis using gridded data at annual, seasonal and monthly time scales over the Fez-Meknes region (northern Morocco) for the period 1961–2019. Our results showed a general decreasing t...
Inadequate climate data stations often make hydrological modelling a rather challenging task in data-sparse regions. Gridded climate data can be used as an alternative; however, their accuracy in replicating the climatology of the region of interest...
The traditional station-based drought index is vulnerable because of the inadequate spatial distribution of the station, and also, it does not fully reflect large-scale, dynamic drought information. Thus, large-scale drought monitoring has been widel...
Water resources are a key factor for regional sustainable development. However, the published water resource data in China is based on a large geographical scale, such as watershed units, and the data cannot reflect subtle differences in water resour...
The spatial and temporal performance of an ensemble of five gridded climate datasets (precipitation) (North American Regional Reanalysis, European Centre for Medium-Range Weather Forecasts interim reanalysis, European Union Water and Global Change (W...
Gross primary production (GPP) is a useful metric for determining trends in the terrestrial carbon cycle. To estimate daily GPP, the cloud-adjusted light use efficiency model (LUEc) was developed by adapting a light use efficiency (LUE, ε) mo...
Accurate site-specific estimations of surface wind speeds (SWS) would greatly aid clean energy development. The quality of estimation depends on the method of interpolating gridded SWS data to derive the wind speed at a given location. This work uses...
The monthly CHIRPS ver. 2 gridded rainfall dataset from 1981 to 2016 was employed to analyze distinct precipitation variability patterns and regimes in semi-arid Botswana. An S-mode eigen analysis was performed on the correlation matrix of the rainfa...
In areas with a limited or non-existent network of observing stations, it is critical to assess the applicability of gridded datasets. This study examined the agreement of Agri4Cast and E-OBS at two spatial resolutions (10 km (EOBS-0.1) and 25 km (EO...
Precipitation is crucial for the hydrological cycle and is directly related to many ecological processes. Historically, measurements of precipitation totals were made at weather stations, but spatial and temporal coverage suffered due to the lack of...
An objective method was developed to analyze longwave and shortwave trough lines in wind field data using different methods, given that these trough lines were researched in different ways. Longwave trough lines were analyzed by locating the cyclonic...
The release of global gridded population datasets, including the Gridded Population of the World (GPW), Global Human Settlement Population Grid (GHS-POP), WorldPop, and LandScan, have greatly facilitated cross-comparison for ongoing research related...
This paper proposes a novel approach, EA2-IMDG (Efficient Approach of Using an In-Memory Data Grid) to improve the performance of replication and scheduling in grid environment systems. Grid environments are widely used for distributed computing, but...
The role of energy is cardinal for achieving the Sustainable Development Goals (SDGs) through the enhancement and modernization of energy generation and management practices. The smart grid enables efficient communication between utilities and the en...
With the continuous advancement of technology for obtaining geographic spatial data, the accumulated volume of such data has been increasing, thus imposing higher demands on the storage, organization, and management of such data. As a new form of dat...
Battery Electric Vehicles (BEVs) have increasingly become prevalent over the past years. BEVs can be regarded as a grid load and as a way to support the grid (energy buffering), provided this extensive battery usage does not affect the BEV’s pe...
Defined in the early 1990s for use with gridded satellite passive microwave data, the Equal-Area Scalable Earth Grid (EASE-Grid) was quickly adopted and used for distribution of a variety of satellite and in situ data sets. Conceptually easy to under...
Finding a more efficient use of energy is an important problem that needs attention. Compared with the traditional power grid, a smart grid can monitor users’ electricity situation and electricity consumption instantly. However, it involves man...
Uniform grid data are widely used in climate science and related interdisciplinary fields. Such data usually describe the hydrometeorological states averaged over uniform latitude–longitude grids. While these data have larger grid areas in the...
Significant amounts of data need to be transferred in order to optimize the operation of power grids. The development of advanced metering and control infrastructure ensures a growth in the amount of data transferred within smart grids. Data compress...
Environmental monitoring applications are designed for supplying derived and often integrated information by tracking and analyzing phenomena. To determine the condition of a target place, they employ a geosensor network to get the heterogeneous sens...
In this paper a new mathematical optimization model is proposed to optimize the number of data aggregators in smart grids and assign each smart meter to at least one data aggregator. The model is based on a Set-Covering Problem, which aims to find th...
An electrical power grid, is an interconnected network for delivering electricity from producers to consumers. Electrical grids vary in size from covering a single building through national grids (which cover whole countries) to transnational grids (...
Scientific datasets from global-scale earth science models and remote sensing instruments are becoming available at greater spatial and temporal resolutions with shorter lag times. Water data are frequently stored as multidimensional arrays, also cal...
Smart grid operations require accurate information on network topology and electrical equipment parameters. This paper proposes estimating such information with data from the smart grid. Assuming that the availability of bus voltage data is restricte...
In recent years, with the development of sensor technology, the volume of spatial data has grown exponentially. However, this data is often unevenly distributed, and traditional indexing methods cannot predict the overall data distribution when data...
The motivation for improving gridded precipitation data lies in weather now-casting and flood forecasting. Therefore, over the past decade, Commercial Microwave Link (CML) attenuation data have been used to determine rain rates between microwave ante...
The integration of the smart grid with the cloud computing environment promises to develop an improved energy-management system for utility and consumers. New applications and services are being developed which generate huge requests to be processed...
With the increasing popularization and application of the smart grid, the harm of the data silo issue in the smart grid is more and more prominent. Therefore, it is especially critical to promote data interoperability and sharing in the smart grid. E...
Achieving the seventeen United Nations Sustainable Development Goals (SDGs) requires accurate, consistent, and accessible population data. Yet many low- and middle-income countries lack reliable or recent census data at the sufficiently fine spatial...
The smart grid has become a cyber-physical system and the more cyber it becomes, the more prone it is to cyber-attacks. One of the most important cyber-attacks in smart grids is false data injection (FDI) into its measurement infrastructure. This att...
The tremendous growth of about 8 billion devices connected to each other in various domains of Internet of Things (IoT)-based applications have attracted researchers from both industry and academia. IoT is a network of several devices connected with...
This paper presents the design and implementation of a communication and control infrastructure for smart grid operation. The proposed infrastructure enhances the reliability of the measurements and control network. The advantages of utilizing the da...
With the accelerated warming of the arctic and the gradual opening of the Arctic passages, more and more attention has been paid to assessing the risk of the navigation environment in the Arctic. Due to the scarcity of visibility data in the Arctic,...
The rapid advancement of smart grids, while enhancing the efficiency of power systems, has also raised serious concerns regarding the privacy and security of end-users’ electricity consumption data. Traditional privacy protection methods strugg...
Accessibility has drawn extensive attention from city planners and transportation researchers for decades. With the benefits of large-scale and varying time, this study aims to combine the taxi global positioning system (GPS) data with a cumulative o...
Statistical partitioning and publishing is commonly used in location-based big data services to address queries such as the number of points of interest, available vehicles, traffic flows, infected patients, etc., within a certain range. Adding noise...
The resilience of electricity networks to extreme weather is an essential component of sustainable energy systems, as power interruptions can affect essential services, economic activities, public safety, and the integration of renewable energy sourc...
Accurate transmission-line parameters are essential for reliable, efficient, and sustainable smart grid operation, especially under increasing renewable-energy integration and data-driven grid management. However, line aging, temperature variations,...
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