TY - GEN
T1 - DisasterMapper
T2 - 4th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial 2015
AU - Huang, Qunying
AU - Cervone, Guido
AU - Jing, Duangyang
AU - Chang, Chaoyi
N1 - Publisher Copyright:
Copyright 2015 ACM.
PY - 2015/11/3
Y1 - 2015/11/3
N2 - Traditional GIS tools and systems are powerful for analyzing geographic information for various applications but they are not designed for processing dynamic streams of data. This paper presents a CyberGIS framework that can automatically synthesize multi-sourced data, such as social media and socioeconomic data, to track disaster events, to produce maps, and to perform spatial and statistical analysis for disaster management. Within our framework, Apache Hive, Hadoop, and Mahout are used as scalable distributed storage, computing environment and machine learning library to store, process and mine massive social media data. The proposed framework is capable of supporting big data analytics of multiple sources. A prototype is implemented and tested using the 2011 Hurricane Sandy as a case study.
AB - Traditional GIS tools and systems are powerful for analyzing geographic information for various applications but they are not designed for processing dynamic streams of data. This paper presents a CyberGIS framework that can automatically synthesize multi-sourced data, such as social media and socioeconomic data, to track disaster events, to produce maps, and to perform spatial and statistical analysis for disaster management. Within our framework, Apache Hive, Hadoop, and Mahout are used as scalable distributed storage, computing environment and machine learning library to store, process and mine massive social media data. The proposed framework is capable of supporting big data analytics of multiple sources. A prototype is implemented and tested using the 2011 Hurricane Sandy as a case study.
UR - http://www.scopus.com/inward/record.url?scp=84982813812&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84982813812&partnerID=8YFLogxK
U2 - 10.1145/2835185.2835189
DO - 10.1145/2835185.2835189
M3 - Conference contribution
AN - SCOPUS:84982813812
T3 - Proceedings of the 4th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial 2015
SP - 1
EP - 6
BT - Proceedings of the 4th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial 2015
A2 - Chandola, Varun
A2 - Vatsavai, Ranga Raju
PB - Association for Computing Machinery, Inc
Y2 - 3 November 2015
ER -