ACM Transactions on

Spatial Algorithms and Systems (TSAS)

Latest Articles

A General Framework for MaxRS and MaxCRS Monitoring in Spatial Data Streams

This article addresses the MaxRS (Maximizing Range Sum) monitoring problem. Given a set of weighted spatial stream objects, this problem is to monitor... (more)

Estimating People Flow from Spatiotemporal Population Data via Collective Graphical Mixture Models

Thanks to the prevalence of mobile phones and GPS devices, spatiotemporal population data can be... (more)

A Layered Approach for More Robust Generation of Road Network Maps from Vehicle Tracking Data

Nowadays, large amounts of tracking data are generated via GPS-enabled devices and other advanced tracking technologies. These constitute a rich... (more)


About TSAS

ACM Transactions on Spatial Algorithms and Systems (TSAS) is a new scholarly journal that publishes high-quality papers on all aspects of spatial algorithms and systems and closely related disciplines. It has a multi-disciplinary perspective spanning a large number of areas where spatial data is manipulated or visualized (regardless of how it is specified - i.e., geometrically or textually), such
as: geography, geographic information systems (GIS), geospatial and spatiotemporal databases, spatial and metric indexing, location-based services, web-based spatial applications, geographic information retrieval (GIR), spatial reasoning and mining, security and privacy, as well as the related visual computing areas of computer graphics, computer vision, geometric modeling, and visualization where the spatial, geospatial, and spatiotemporal data is central.  READ MORE

Call-for-papers: ACM TSAS has issued a call for papers for its inaugural issue. Please use manuscriptcentral ( to submit articles, check the status of articles and for reviewing tasks.

Forthcoming Articles
Spatial Partition-based Particle Filtering for Data Assimilation in Wildfire Spread Simulation

Particle Filters (PFs) hold great promise to support data assimilation for spatial temporal simulations to achieve more accurate simulation or prediction results. However, PFs face major challenges to work effectively for complex spatial temporal simulations due to the high dimensional state space of the simulation models, which typically cover large areas and have a large number of spatially dependent state variables. To effectively support data assimilation for large-scale spatial temporal simulations, this paper develops a spatial partition-based particle-filtering framework that breaks the system state and observation data into smaller spatial regions and then carries out localized particle filtering based on these spatial regions. The developed framework exploits the spatial locality property of system state and observation data, and employs the divide-and-conquer principle to reduce state dimension and data complexity. Within this framework, a two-level automated spatial partitioning method is presented to provide automated and balanced spatial partitions with less boundary sensors. The developed framework is applied to a case study of wildfire spread simulations and achieved improved results compared to using standard PFs-based data assimilation methods.


Publication Years 2015-2017
Publication Count 27
Citation Count 13
Available for Download 27
Downloads (6 weeks) 252
Downloads (12 Months) 2315
Downloads (cumulative) 3675
Average downloads per article 136
Average citations per article 0
First Name Last Name Award
Chang-Tien Lu ACM Distinguished Member (2015)
Timoleon Sellis ACM Senior Member (2008)
Cyrus Shahabi ACM Distinguished Member (2009)

First Name Last Name Paper Counts
Dieter Pfoser 3
Lars Kulik 2
Maria Damiani 2
Fabio Valdes 1
Wouter Meulemans 1
Mauro Negri 1
Kyle Hickmann 1
Carola Wenk 1
Benedikt Budig 1
Wei Niu 1
Alexandros Efentakis 1
Pankaj Agarwal 1
Salles Magalhães 1
Timos Sellis 1
Bettina Speckmann 1
Peter Scheuermann 1
Cyrus Shahabi 1
Feng Chen 1
Hitoshi Shimizu 1
Wangchien Lee 1
Juan Banda 1
Petrus Martens 1
Alex Beutel 1
Karthik Pillai 1
Stylianos Sideridis 1
Yi Yu 1
Preeti Goel 1
Sara Migliorini 1
Martin Nöllenburg 1
Chung Kuo 1
Dimitrios Skoutas 1
Tomoharu Iwata 1
Naonori Ueda 1
Elisa Bertino 1
Nikos Pelekis 1
Sadao Obana 1
Karine Zeitouni 1
André Van Renssen 1
Liang Zhao 1
Denian Yang 1
Claudio Silvestri 1
Marcus Andrade 1
Suhua Tang 1
Janne Kovanen 1
Mohammed Ali 1
Sarana Nutanong 1
Leyla Kazemi 1
Mark Mckennney 1
Andreas Gemsa 1
Jan Haunert 1
Thomas Van Dijk 1
Daichi Amagata 1
Takahiro Hara 1
Futoshi Naya 1
Rafal Angryk 1
Berkay Aydin 1
Thomas Mølhave 1
Chaulio Ferreira 1
Georgios Skoumas 1
Ralf Güting 1
Kotagiri Ramamohanarao 1
Egemen Tanin 1
Giuseppe Pelagatti 1
Hien To 1
Roger Frye 1
Alexander Wolff 1
Sophia Karagiorgou 1
Huiju Hung 1
Christodoulos Efstathiades 1
Dustin Kempton 1
Gabriel Ghinita 1
Dai That 1
Mahmuda Ahmed 1
Brittany Fasy 1
Sanjay Purushotham 1
Changtien Lu 1
Naren Ramakrishnan 1
Panagiotis Tampakis 1
Anastasios Kyrillidis 1
Roger Zimmermann 1
Tapani Sarjakoski 1
Iulian Popa 1
Kevin Buchin 1
Alberto Belussi 1
Zhijiao Liu 1
James Caverlee 1
Wm Franklin 1
Yannis Theodoridis 1

Affiliation Paper Counts
Bangladesh University of Engineering and Technology 1
Rensselaer Polytechnic Institute 1
Montana State University - Bozeman 1
University of Massachusetts Boston 1
Duke University 1
Purdue University 1
University of Osnabruck 1
Swinburne University of Technology 1
University of Texas at San Antonio 1
State University of New York at Albany 1
Carnegie Mellon University 1
Microsoft Corporation 1
Stanford University 1
University of Texas at Austin 1
Ca' Foscari University of Venice 1
City University London 1
City University of Hong Kong 1
Academia Sinica Taiwan 1
National University of Singapore 1
Northwestern University 1
University of Hagen 2
Southern Illinois University at Edwardsville 2
Athena Research and Innovation Center in Information, Communication and Knowledge Technologies 2
Pennsylvania State University 2
National Technical University of Athens 2
Karlsruhe Institute of Technology 2
Eindhoven University of Technology 2
University of Electro-Communications 2
University of Verona 2
University of Milan 2
Research Organization of Information and Systems National Institute of Informatics 2
Virginia Tech 2
Osaka University 2
Politecnico di Milano 2
Texas A and M University System 3
Universite de Versailles Saint-Quentin-en-Yvelines 3
Tulane University 3
University of Wurzburg 3
Federal University of Vicosa 3
Georgia State University 4
Nippon Telegraph and Telephone Corporation 4
University of Southern California 4
George Mason University 4
University of Piraeus 4
University of Melbourne 5

ACM Transactions on Spatial Algorithms and Systems (TSAS) - Regular Papers and SIGSPATIAL Paper

Volume 3 Issue 1, May 2017 Regular Papers and SIGSPATIAL Paper

Volume 2 Issue 4, November 2016 Regular Papers and SIGSPATIAL Paper
Volume 2 Issue 3, October 2016
Volume 2 Issue 2, July 2016 Invited Papers from ACM SIGSPATIAL
Volume 2 Issue 1, April 2016

Volume 1 Issue 2, November 2015
Volume 1 Issue 1, August 2015 Inaugural Issue
All ACM Journals | See Full Journal Index

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