1 option
BigSpatial 2017 : proceedings of the 6th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data (BigSpatial-2017) : Nov 7th, 2017, Redondo Beach, CA, USA / edited by Varun Chandola, Ranga Raju Vatsavai.
- Format:
- Book
- Series:
- ACM Conferences
- Language:
- English
- Subjects (All):
- Data mining--Congresses.
- Data mining.
- Geographic information systems--Software.
- Geographic information systems.
- Physical Description:
- 1 online resource (51 pages)
- Other Title:
- BigSpatial '17
- Place of Publication:
- New York : The Association for Computing Machinery, Inc., 2017.
- Summary:
- Big data is emerging as an important area of research for data researchers and scientists. This area has also seen significant interest from the industry and federal agencies alike, as evidenced by the recent White House initiative on "Big data research and development". Within the realm of big data, spatial and spatio-temporal data is one of fastest growing types of data With advances in remote sensors, sensor networks, and the proliferation of location sensing devices in daily life activities and common business practices, the generation of disparate, dynamic, and geographically distributed spatiotemporal data has exploded in recent years. In addition, significant progress in ground, air- and space-borne sensor technologies has led to an unprecedented access to earth science data for scientists from different disciplines, interested in studying the complementary nature of different parameters. Today, analyzing this data poses a massive challenge to researchers.
- Notes:
- Description based on publisher supplied metadata and other sources.
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.