NDLI: On-demand aggregation of gridded data over user-specified spatio-temporal domains

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Activity-based ridesharing: increasing flexibility by time geography

A traffic flow approach to early detection of gathering events

BigGIS: a continuous refinement approach to master heterogeneity and uncertainty in spatio-temporal big data (vision paper)

From verbal route descriptions to sketch maps in natural environments

A Markov chain based pruning method for predictive range queries

MultiCalib: national-scale traffic model calibration in real time with multi-source incomplete data

Enhancing scene parsing by transferring structures via efficient low-rank graph matching

Massively parallel algorithms for computing TIN DEMs and contour trees for large terrains

Spatiotemporal topic association detection on tweets

A topological algorithm for determining how road networks evolve over time

Knowledge-based trajectory completion from sparse GPS samples

Finding multiple new optimal locations in a road network

Fast transportation network traversal with hyperedges: (industrial paper)

Predicting interactions and contexts with context trees

A spatial column-store to triangulate the Netherlands on the fly.

Bicycle-sharing systems expansion: station re-deployment through crowd planning

Particle filter for real-time human mobility prediction following unprecedented disaster

On supporting compilation in spatial query engines: (vision paper)

Deducing individual driving preferences for user-aware navigation

Efficient in-memory indexing of network-constrained trajectories

Scalable spatial scan statistics through sampling

Temporal map labeling: a new unified framework with experiments

Implementing data-dependent triangulations with higher order Delaunay triangulations

Data depth based clustering analysis

Large-scale geolocalization of overhead imagery

Privacy-friendly mobility analytics using aggregate location data

Coverage and diversity aware top-k query for spatio-temporal posts

Demand driven store site selection via multiple spatial-temporal data

k-Optimal meeting points based on preferred paths

CrimeStand: spatial tracking of criminal activity

Price-aware real-time ride-sharing at scale: an auction-based approach

FCCF: forecasting citywide crowd flows based on big data

Autonomous car and ride sharing: flexible road trains: (vision paper)

Finding non-dominated paths in uncertain road networks

GCMF: an efficient end-to-end spatial join system over large polygonal datasets on GPGPU platform

A simple efficient approximation algorithm for dynamic time warping

Automatic geographic metadata correction for sensor-rich video sequences

Scalable estimation of precision maps in a MapReduce framework

A concise summary of spatial anomalies and its application in efficient real-time driving behaviour monitoring

Differentially private publication of location entropy

Prediction of meteorological parameters: an a-posteriori probabilistic semantic kriging approach

Managing massive trajectories on the cloud

Mining city-wide encounters in real-time

MoTrIS: a framework for route planning on multimodal transportation networks

GeoTrend: spatial trending queries on real-time microblogs

Knowing without telling: integrating sensing and mapping for creating an artificial companion

SAGEL: smart address geocoding engine for supply-chain logistics

Who goes there?: approaches to mapping facial appearance diversity

Progressive streaming and massive rendering of 3D city models on web-based virtual globe

A vision for micro and macro location aware services

Gloria: a batch friendly indexing and storage framework

An online localization method for a subway train utilizing the barometer on a smartphone

CDO: extremely high-throughput road distance computations on city road networks

A framework for evacuation hotspot detection after large scale disasters using location data from smartphones: case study of Kumamoto earthquake

Mining the most influential k-location set from massive trajectories

Towards interactive analytics and visualization on one billion tweets

Atlas: on the expression of spatial-keyword group queries using extended relational constructs

Scalable 3D spatial queries for analytical pathology imaging with MapReduce

Simba: spatial in-memory big data analysis

LEDS: local event discovery and summarization from tweets

Automatic detection and matching of geospatial properties in transportation data sources (demo paper)

Predicting irregular individual movement following frequent mid-level disasters using location data from smartphones

Immersive tangible geospatial modeling

A SMART approach to quality assessment of site-based spatio-temporal data

Assisted journey recollections from photo streams: (demo paper)

A visual and computational analysis approach for exploring significant locations and time periods along a bus route

SOLEV: a video generation framework for solar events from mixed data sources (demo paper)

Real-time urban population monitoring using pervasive sensor network

A framework for updating multi-criteria optimal location query (demo paper)

ADCN: an anisotropic density-based clustering algorithm

DNN-based prediction model for spatio-temporal data

Unsupervised annotated city traffic map generation

Pyspatiotemporalgeom: a python library for spatiotemporal types and operations

Location corroborations by mobile devices without traces

Demonstrating PlanetSense: gathering geo-spatial intelligence from crowd-sourced and social-media data

A simple baseline for travel time estimation using large-scale trip data

A demonstration of SHAREK: an efficient matching framework for ride sharing systems

On-demand aggregation of gridded data over user-specified spatio-temporal domains

Quantitative evaluation of public spaces using crowd replication

RxSpatial: the reactive spatial library

Spatio-temporal modeling of the topology of swarm behavior with persistence landscapes

Polygon consensus: smart crowdsourcing for extracting building footprints from historical maps

Personalized location models with adaptive mixtures

A spatio-temporal, Gaussian process regression, real-estate price predictor

Interpreting traffic dynamics using ubiquitous urban data

City form and well-being: what makes London neighborhoods good places to live?

User identification in cyber-physical space: a case study on mobile query logs and trajectories

Multi-user routing to single destination with confluence

Location privacy for group meetups

A distantly supervised method for extracting spatio-temporal information from text

Scalable user assignment in power grids: a data driven approach

Spatio-temporal sentiment hotspot detection using geotagged photos

Cleansing indoor RFID data using regular expressions

LOCAl: a personalized cache mechanism for location-based social networks

Real-time detection and classification of traffic jams from probe data

On-demand aggregation of gridded data over user-specified spatio-temporal domains

Content Provider	ACM Digital Library
Author	Tosado, Joel E. Guzun, Gheorghi Canahuate, Guadalupe Mantilla, Ricardo
Abstract	The advent of satellite imagery, remote sensing products, and global scale numerical climate models over the last two decades has created an explosion of available gridded environmental data. These space-time explicit datasets are produced and distributed using different spatial and temporal resolutions. Current approaches for comparing two different products generally involve offline pre-computation of aggregations to a common spatio-temporal resolution. This limits the user's ability to interactively compare different data products or transform data products into the required input resolution for modeling. The goal of this work is to enable end users to perform on- the-fly transformations of gridded data products to different spatio-temporal resolutions to facilitate exploratory analyses and comparison of different data products. In this paper we propose a compressed columnar indexing and query processing to support online aggregation of gridded data over user-specified spatio-temporal domains. Our approach requires up to two orders of magnitude less space than more traditional indexing while maintaining competitive execution time for different aggregations in time and space.
Starting Page	1
Ending Page	4
Page Count	4
File Format	PDF
ISBN	9781450345897
DOI	10.1145/2996913.2996944
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-10-31
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Spatio-temporal domains Gridded data Data aggregation
Content Type	Text
Resource Type	Article

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