SANET

The SANET toolbox: new methods for network spatial analysis. This paper describes new methods, called network spatial methods, for analyzing spatial phenomena that occur on a network or alongside a network (referred to as network spatial phenomena). First, the paper reviews network spatial phenomena discussed in the related literature. Second, the paper shows the uniform network transformation, which is used in the study of non-uniform distributions on a network, such as the densities of traffic and population. Third, the paper outlines a class of network spatial methods, including nearest neighbor distance methods, K-function methods, cell count methods, clumping methods, the Voronoi diagrams and spatial interpolation methods. Fourth, the paper shows three commonly used computational methods to facilitate network spatial analysis. Fifth, the paper describes the functions of a GIS-based software package, called SANET, that perform network spatial methods. Sixth, the paper compares network spatial methods with the corresponding planar spatial methods by applying both methods to the same data set. This comparison clearly demonstrates how different conclusions can result. The conclusion summarizes the major findings.


References in zbMATH (referenced in 31 articles , 1 standard article )

Showing results 1 to 20 of 31.
Sorted by year (citations)

1 2 next

  1. Eckardt, Matthias; Mateu, Jorge: Second-order and local characteristics of network intensity functions (2021)
  2. James D. Gaboardi, Sergio Rey, Stefanie Lumnitz: spaghetti: spatial network analysis in PySAL (2021) not zbMATH
  3. Liu, Yang; Ruppert, David: Density estimation on a network (2021)
  4. Anderes, Ethan; Møller, Jesper; Rasmussen, Jakob G.: Isotropic covariance functions on graphs and their edges (2020)
  5. Bonnet, Édouard; Cabello, Sergio; Mohar, Bojan; Pérez-Rosés, Hebert: The inverse Voronoi problem in graphs. I: Hardness (2020)
  6. Cronie, Ottmar; Moradi, Mehdi; Mateu, Jorge: Inhomogeneous higher-order summary statistics for point processes on linear networks (2020)
  7. McSwiggan, Greg; Baddeley, Adrian; Nair, Gopalan: Estimation of relative risk for events on a linear network (2020)
  8. Moradi, M. Mehdi; Mateu, Jorge: First- and second-order characteristics of spatio-temporal point processes on linear networks (2020)
  9. Uppala, Medha; Handcock, Mark S.: Modeling wildfire ignition origins in southern California using linear network point processes (2020)
  10. Moradi, M. Mehdi; Cronie, Ottmar; Rubak, Ege; Lachieze-Rey, Raphael; Mateu, Jorge; Baddeley, Adrian: Resample-smoothing of Voronoi intensity estimators (2019)
  11. Suman Rakshit; Adrian Baddeley; Gopalan Nair: Efficient Code for Second Order Analysis of Events on a Linear Network (2019) not zbMATH
  12. Bielik, M.; König, R.; Schneider, S.; Varoudis, T.: Measuring the impact of street network configuration on the accessibility to people and walking attractors (2018)
  13. Eckardt, Matthias; Mateu, Jorge: Point patterns occurring on complex structures in space and space-time: an alternative network approach (2018)
  14. Jentsch, Peter C.; Anand, Madhur; Bauch, Chris T.: Spatial correlation as an early warning signal of regime shifts in a multiplex disease-behaviour network (2018)
  15. Moradi, M. Mehdi; Rodríguez-Cortés, Francisco J.; Mateu, Jorge: On kernel-based intensity estimation of spatial point patterns on linear networks (2018)
  16. van Lieshout, M. N. M.: Nearest-neighbour Markov point processes on graphs with Euclidean edges (2018)
  17. Bai, Hexiang; Li, Deyu; Ge, Yong; Wang, Jinfeng: Detecting nominal variables’ spatial associations using conditional probabilities of neighboring surface objects’ categories (2016)
  18. Bose, Prosenjit; De Carufel, Jean-Lou; Grimm, Carsten; Maheshwari, Anil; Smid, Michiel: Optimal data structures for farthest-point queries in cactus networks (2015)
  19. Blanquero, Rafael; Carrizosa, Emilio: Solving the median problem with continuous demand on a network (2013)
  20. Ang, Qi Wei; Baddeley, Adrian; Nair, Gopalan: Geometrically corrected second order analysis of events on a linear network, with applications to ecology and criminology (2012)

1 2 next