When studying geographical phenomena, different levels of spatial and temporal granularity often have to be considered. While various approaches have been proposed to analyse geographical data in a ...multi-scale perspective, they have all focused on either spatial or temporal attributes rather than on the integration of space and time over multiple scales. This study introduces the continuous spatio-temporal model (CSTM), a conceptual model that seeks to address this shortcoming. The presented model is based on (1) the continuous temporal model (CTM), a multi-scale model for temporal information, and (2) the continuous spatial model (CSM), an extension of CTM for multi-scale spatial raster data. At the core of the presented conceptual model is a spatio-temporal evolution element or, in short, stevel, which is described by four variables: (1) pixel location, (2) spatial resolution, (3) temporal interval, and (4) temporal resolution. By varying one or more of these variables, a CSTM-tree consisting of (sets of) stevel arrays is created, forming the basis of an exhaustive CSTM-typology. These arrays can then be used to systematically cluster spatio-temporal information. The value of our approach is illustrated by means of a simplified example of mean temperature evolution. Various suggestions are made for modifications to be developed in future research.
Shannon entropy is the most popular method for quantifying information in a system. However, Shannon entropy is considered incapable of quantifying spatial data, such as raster data, hence it has not ...been applied to such datasets. Recently, a method for calculating the Boltzmann entropy of numerical raster data was proposed, but it is not efficient as it involves a series of numerical processes. We aimed to improve the computational efficiency of this method by borrowing the idea of head and tail breaks. This paper relaxed the condition of head and tail breaks and classified data with a heavy-tailed distribution. The average of the data values in a given class was regarded as its representative value, and this was substituted into a linear function to obtain the full expression of the relationship between classification level and Boltzmann entropy. The function was used to estimate the absolute Boltzmann entropy of the data. Our experimental results show that the proposed method is both practical and efficient; computation time was reduced to about 1% of the original method when dealing with eight 600 × 600 pixel digital elevation models.
Prefetching is a process in which the necessary portion of data is predicted and loaded into memory beforehand. The increasing usage of geographic data in different types of applications has ...motivated the development of different prefetching techniques. Each prefetching technique serves a specific type of application, such as two-dimensional geographic information systems or three-dimensional visualization, and each one is crafted for the corresponding navigation patterns. However, as the boundary between these application types blurs, these techniques become insufficient for hybrid applications (such as digital moving maps), which embody various capabilities and navigation patterns. Therefore, a set of techniques should be used in combination to handle different prefetching requirements. In this study, a priority-based tile prefetching approach is proposed, which enables the ensemble usage of various techniques at the same time. The proposed approach manages these techniques dynamically through a fuzzy-logic-based inference engine to increase prefetching performance and to adapt to various exhibited behaviours. This engine performs adaptive decisions about the advantages of each technique according to their individual accuracy and activity level using fuzzy logic to determine how each prefetching technique performs. The results obtained from the experiments showed that up to a 25% increase in prefetching performance is achieved with the proposed ensemble usage over individual usage. A generic model for prefetching techniques was also developed and used to describe the given approach. Finally, a cross-platform software framework with four different prefetching techniques was developed to let other users utilize the proposed approach.
Rasterized representations of geometrical structures are commonplace in science and engineering. They are used in analysis and design of complex geometrical structures; however, the introduced errors ...for volume and surface estimation are often not considered in detail. To provide insight and information on these effects, in this study model geometries of porous media (simple cubic, body-centered cubic, face-centered cubic) are used to investigate the influence of resolution (voxels per length) on volume and surface approximation. The numerically obtained results are compared with analytical solutions for porosity and specific surface area. Small deviations from the real volume are found for the rasterized geometry at reasonable resolution. For the estimated surface area, in contrast, when using marching cubes considerable deviations from the analytically calculated surface area are found even at relatively fine resolutions. These findings are especially important for the use of rasterized voxel data as input for engineering correlations to estimate characteristic physical transport properties such as pressure drop or effective heat transport.
R is a free programming language that has been widely used by statisticians and data miners for statistical software development and data analysis. The number of contributed packages for handling and ...analyzing spatial data has significantly increased over the last 15 years. This paper reviews the potential for spatial data analysis using R programming. The packages related mainly to geographic information system (GIS), such as sp, sf, rgdal, raster, ggmap, tmap, gstat, and RQGIS, are selected for specific tasks along with useful examples. By referring to these examples, new R users can examine how R handles spatial data and what types of problems it can be applied to. R provides several functions that can import, export, and manipulate vector and raster data. For spatial data analysis, R acts as a GIS tool because it can perform GIS procedures effectively from basic to advanced levels. For visualization and mapping, R can produce various 2D or 3D maps from spatial data using either customized or flexible approaches. A user community needs to be developed to enhance the benefits of R programming for the public and private sectors in Japan, particularly in the field of geoinformatics.
For spatio-temporal and topologic analyses, vectorial information (carrying coordinate values defined as point sets) gives better information than its raster (grid of pixels) counterpart. The study ...presented in this paper is based on (1) recognition and extraction of an island object in a set of digital images captured by LandSat-7 satellite and (2) modelling it as a polygon (vectorial) and making it easy to process and easy to understand for computers and information science applications. Polygon representations of island images then can be stored and manipulated through object-relational spatial databases. Spatial databases have built-in functions and services for spatial objects defined with geometry types such as points, lines, and polygons. By this way we will be utilizing the rapidly changing and developing object-relational database communities’ studies and discoveries in spatio-temporal and topological analysis for the investigation of digital satellite images. This approach also enables service qualities as well as a better performance. The efficiency and feasibility of the proposed system will be examined by various scenarios such as earthquake, erosion and accretion. Scenarios are based on measuring the effects of the natural phenomena on a selected island on satellite images.
Agro-climatic data by county (ACDC) is designed to provide the major agro-climatic variables from publicly available spatial data sources to diverse end-users. ACDC provides USDA NASS annual ...(1981–2015) crop yields for corn, soybeans, upland cotton and winter wheat by county. Customizable growing degree days for 1 °C intervals between −60 °C and +60 °C, and total precipitation for two different crop growing seasons from the PRISM weather data are included. Soil characteristic data from USDA-NRCS gSSURGO are also provided for each county in the 48 contiguous US states. All weather and soil data are processed to include only data for land being used for non-forestry agricultural uses based on the USGS NLCD land cover/land use data. This paper explains the numerical and geo-computational methods and data generating processes employed to create ACDC from the original data sources. Essential considerations for data management and use are discussed, including the use of the agricultural mask, spatial aggregation and disaggregation, and the computational requirements for working with the raw data sources.
Wind is a complex phenomenon and a critical factor in assessing climatic conditions and pedestrian comfort within cities. To obtain spatial information on near-ground wind speed, 3D computational ...fluid dynamics (CFD) modelling is often used. This is a computationally intensive method which requires extensive computer resources and is time consuming. By using a simpler 2D method, larger areas can be processed and less time is required. This study attempts to model the relationship between near-ground wind speed and urban geometry using 2.5D raster data and variable selection methods. Such models can be implemented in a geographic information system (GIS) to assess the spatial distribution of wind speed at street level in complex urban environments at scales from neighbourhood to city. Wind speed data, 2 m above ground, is obtained from simulations by CFD modelling and used as a response variable. A number of derivatives calculated from high-resolution digital surface models (DSM) are used as potential predictors. A sequential variable selection algorithm followed by all-possible subset regression was used to select candidate models for further evaluation. The results show that the selected models explain general spatial wind speed pattern characteristics but the prediction errors are large, especially so in areas with high wind speeds. However, all selected models did explain 90 % of the wind speed variability (R ² ≈ 0.90). Predictors adding information on width and height ratio and alignment of street canyons with respect to wind direction are suggested for improving model performance. To assess the applicability of any derived model, the results of the CFD model should be thoroughly evaluated against field measurements.
A new raster-based GIS model that combines multi-criteria evaluation and least-cost path analysis was developed to determine the optimal haulage routes of dump trucks in large scale open-pit mines. ...The model logic can consider multiple criteria simultaneously (i.e. speed, water body, ore body, curve, visibility, haul road maintenance) and can rate the adverse factor scores of truck movement using fuzzy membership functions. After establishing the weights of five factors by pairwise comparisons, the average adverse score grid can be generated by the weighted linear combination of factor and constraint scores. New software, called Dump Traveler, was implemented to improve the availability of the developed model. An application to the Roto South pit in the Pasir open-pit coal mine, Indonesia, showed that the software can provide rational solutions to determine the optimal routes on truck haulage operations. Moreover, the layout of available haul roads can be evaluated to consider the trade-off between road maintenance costs and the potential for traffic jams. Variations of weights for factors were found to be sensitive to the optimal haulage routes determined by least-cost path analysis. The software provides both optimal routes on truck haulage operations and approximately estimated travel times along the routes, therefore it can support other truck dispatching software that mainly considers scheduling problems.
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