Automated backdating of transportation networks with Landsat imagery

Author(s):  
Guillermo Castilla ◽  
Greg McDermid
Author(s):  
Jeffrey L. Adler

For a wide range of transportation network path search problems, the A* heuristic significantly reduces both search effort and running time when compared to basic label-setting algorithms. The motivation for this research was to determine if additional savings could be attained by further experimenting with refinements to the A* approach. We propose a best neighbor heuristic improvement to the A* algorithm that yields additional benefits by significantly reducing the search effort on sparse networks. The level of reduction in running time improves as the average outdegree of the network decreases and the number of paths sought increases.


2009 ◽  
Vol 24 (4) ◽  
pp. 214-222 ◽  
Author(s):  
Jeffrey D. Kline ◽  
Alissa Moses ◽  
David Azuma ◽  
Andrew Gray

Abstract Forestry professionals are concerned about how forestlands are affected by residential and other development. To address those concerns, researchers must find appropriate data with which to describe and evaluate rates and patterns of forestland development and the impact of development on the management of remaining forestlands. We examine land use data gathered from Landsat imagery for western Washington and evaluate its usefulness for characterizing low-density development of forestland. We evaluate the accuracy of the satellite imagery‐based land use classifications by comparing them with other data from US Forest Service's Forest Inventory and Analysis inventories and the US census. We then use the data to estimate an econometric model describing development as a function of socioeconomic and topographic factors and project future rates of development and forestland loss to 2020. We conclude by discussing how best to meet the land use data needs of researchers, forestry policymakers, and managers.


2021 ◽  
Vol 13 (2) ◽  
pp. 22
Author(s):  
Xavier Boulet ◽  
Mahdi Zargayouna ◽  
Gérard Scemama ◽  
Fabien Leurent

Modeling and simulation play an important role in transportation networks analysis. In the literature, authors have proposed many traffic and mobility simulations, with different features and corresponding to different contexts and objectives. They notably consider different scales of simulations. The scales refer to the represented entities, as well as to the space and the time representation of the transportation environment. However, we often need to represent different scales in the same simulation, for instance to represent a neighborhood interacting with a wider region. In this paper, we advocate for the reuse of existing simulations to build a new multi-scale simulation. To do so, we propose a middleware model to couple independent mobility simulations, working at different scales. We consider all the necessary processing and workflow to allow for a coherent orchestration of these simulations. We also propose a prototype implementation of the middleware. The results show that such a middleware is capable of creating a new multi-scale mobility simulation from existing ones, while minimizing the incoherence between them. They also suggest that, to have a maximal benefit from the middleware, existing mobility simulation platforms should allow for an external control of the simulations, allowing for executing a time step several times if necessary.


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