A performance comparison of distance-based query algorithms using R-trees in spatial databases

Corral, Antonio; Almendros-Jiménez, Jesús Manuel

doi:10.1016/j.ins.2006.12.012

Cited by 27 publications

(14 citation statements)

References 38 publications

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“…The R-tree and PR-tree implementations under test were not specifically designed to hold large numbers of items (nevertheless, the PRtree performed competitively for the largest dataset in terms of query time). There are many ways of constructing [1,5] and querying [4] R-trees and so it may be possible to choose more efficient algorithms for the situation at hand.…”

Section: Discussionmentioning

confidence: 99%

Fast regridding of large, complex geospatial datasets

Blower

Clegg

2011

Proceedings of the 2nd International Conference on Computing for Geospatial Research &Amp; Applications - COM.Geo '11

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In the earth sciences, data are commonly cast on complex grids in order to model irregular domains such as coastlines, or to evenly distribute grid points over the globe. It is common for a scientist to wish to re-cast such data onto a grid that is more amenable to manipulation, visualization, or comparison with other data sources. The complexity of the grids presents a significant technical difficulty to the regridding process. In particular, the regridding of complex grids may suffer from severe performance issues, in the worst case scaling with the product of the sizes of the source and destination grids. We present a mechanism for the fast regridding of such datasets, based upon the construction of a spatial index that allows fast searching of the source grid. We discover that the most efficient spatial index under test (in terms of memory usage and query time) is a simple lookup table. A kd-tree implementation was found to be faster to build and to give similar query performance at the expense of a larger memory footprint. Using our approach, we demonstrate that regridding of complex data may proceed at speeds sufficient to permit regridding on-the-fly in an interactive visualization application, or in a Web Map Service implementation. For large datasets with complex grids the new mechanism is shown to significantly outperform algorithms used in many scientific visualization packages.

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Section: Discussionmentioning

confidence: 99%

Fast regridding of large, complex geospatial datasets

Blower

Clegg

2011

Proceedings of the 2nd International Conference on Computing for Geospatial Research &Amp; Applications - COM.Geo '11

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“…In [10], additional techniques as sorting and application of plane-sweep during the expansion of node pairs, and the use of the estimation of the distance of the K-th closest pair to suspend unnecessary computations of MBR distances are included to improve [16]. A Recursive Best-First Search (RBF) algorithm for DBQ between spatial objects indexed in R-trees was presented in [29], with an exhaustive experimental study that compares DF, BF and RBF for several distance-based queries (Range Distance, K-Nearest Neighbors, K-Closest Pairs and Range Distance Join). Recently, in [30], an extensive experimental study comparing the R*-tree and Quadtree-like index structures for K-Nearest Neighbors and K-Distance Join queries together with index construction methods (dynamic insertion and bulk-loading algorithm) is presented.…”

Section: Kcpq and εDjqmentioning

confidence: 99%

New plane-sweep algorithms for distance-based join queries in spatial databases

et al. 2016

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Efficient and effective processing of the distance-based join query (DJQ) is of great importance in spatial databases due to the wide area of applications that may address such queries (mapping, urban planning, transportation planning, resource management, etc.). The most representative and studied DJQs are the K Closest Pairs Query (KCPQ) and εDistance Join Query (εDJQ). These spatial queries involve two spatial data sets and a distance function to measure the degree of closeness, along with a given number of pairs in the final result (K) or a distance threshold (ε). In this paper, we propose four new plane-sweep-based algorithms for KCPQs and their extensions for εDJQs in the context of spatial databases, without the use of an index for any of the two disk-resident data sets (since, building and using indexes is not always in favor of processing performance). They employ a combination of plane-sweep algorithms and space partitioning techniques to join the data sets. Finally, we present results of an extensive experimental study, that compares the efficiency and effectiveness of the proposed algorithms for KCPQs and εDJQs. This performance study, conducted on medium and big spatial data sets (real and synthetic) validates that the proposed plane-sweepbased algorithms are very promising in terms of both efficient and effective measures, when neither inputs are indexed. Moreover, the best of the new algorithms is experimentally compared to the best algorithm that is based on the R-tree (a widely accepted access method), for KCPQs and εDJQs, using the same data sets. This comparison shows that the new algorithms outperform R-tree based algorithms, in most cases.

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“…This procedure allows obtaining the average length of the line segments. Then, the R-tree indexes for these line segments were built and stored the elevation in the R-tree (Huang, P. Lin and H. Lin, 2001;Corral and Almendros-Jiménez, 2007;Zhu, Gong and Zhang, 2007). Finally, each interpolated point A was processed as follows.…”

Section: Algorithm Workflowmentioning

confidence: 99%

An algorithm for generation of DEMs from contour lines considering geomorphic features

Rui¹,

Yu²,

Lu³

et al. 2016

Earth sci. res. j.

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Geomorphic information is omitted from many existing methods of generating gridded digital elevation models (DEMs) from contour lines, resulting in significant errors during interpolation. Here, we present an advanced schema for improvement of the comprehensive regionalized method of linear interpolation. This approach uses a moving fitting method for an interpolated point and selects elevation points that are representative of geomorphic features as a whole to improve interpolation quality. A total of 16 points are selected, according to certain criteria, in eight directions surrounding the interpolated point; thus, there are two points in each direction, which is sufficient to provide an accurate representation of the geomorphic features of the DEM. Our method introduces virtual control points to prevent sudden changes in the interpolation results, which helps to overcome problems related to the distortion of the local geospatial distribution in areas where feature geomorphic information is inadequate. We construct the spline interpolation function using intersection points and virtual control points, all of which are applied to compute the point elevation. Moreover, we index all elevation values and spatial points of linear features using the R-tree method to ensure that points related to an interpolated position can be retrieved as quickly as possible. Finally, we test our method using a coal mine elevation dataset. The results confirm that our proposed method can generate DEMs smoothly and, in particular, avoid problems related to local distortion.La información geomórfica se omite en muchos de los métodos de generación de Modelos Digitales de Elevación (DEM, en inglés) que se elaboran a partir de líneas de contorno, lo que resulta en errores significativos durante la interpolación. En este trabajo se presenta un esquema avanzado para el mejoramiento del método comprensivo regionalizado de interpolación lineal. Esta aproximación utiliza un método de ajuste movil para un punto interpolado y selecciona puntos de elevación representativos o características geomórficas como un todo para mejorar la calidad de la interpolación. Se seleccionaron 16 puntos de acuerdo con ciertos criterios, en ocho direcciones alrededor del punto interpolado; por lo tanto, hay dos puntos en cada dirección, lo que es suficiente para proveer una representación precisa de las características geomórficas del DEM. El método propuesto consta de puntos virtuales de control para prevenir cambios repentinos en los resultados de la interpolación, lo que ayuda a vencer los problemas relacionados a la distorsión de la distribución geoespacial local en áreas donde la información de las características geomórficas es inadecuada. Se utilizó una función de interpolación spline con puntos de intersección y puntos de control virtual, que fueron utilizados para calcular el punto de elevación. Además, se indexaron todos los valores de elevación y los puntos espaciales de las características lineales con el método de árbol-R para asegurar que los puntos...

show abstract

A performance comparison of distance-based query algorithms using R-trees in spatial databases

Cited by 27 publications

References 38 publications

Fast regridding of large, complex geospatial datasets

Fast regridding of large, complex geospatial datasets

New plane-sweep algorithms for distance-based join queries in spatial databases

An algorithm for generation of DEMs from contour lines considering geomorphic features

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