2015 Proceeding- Editors:
- Varun Chandola,
- Ranga Raju Vatsavai
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.
Proceeding Downloads
DisasterMapper: A CyberGIS framework for disaster management using social media data
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 ...
A SciDB-based Framework for Efficient Satellite Data Storage and Query based on Dynamic Atmospheric Event Trajectory
Current research in climate informatics focuses mainly on the development of novel (machine learning, data mining, or statistical) techniques to analyze climate data (e.g. model, in-situ, or satellite) or to make prediction based on these climate data. ...
Elliptical Hotspot Detection: A Summary of Results
Given a set of points in Euclidean space, a minimum log likelihood ratio threshold, and a statistical significance threshold, Elliptical Hotspot Detection (EHD) finds elliptical hotspot areas where the concentration of activities inside is significantly ...
A Fast Algorithm for Matching Planar Maps with Minimum Fréchet Distances
In this paper, we present a fast and practical algorithm for a map-matching problem searching a path on a given graph that minimizes Fréchet distance from a given trajectory, which is a natural measurement based on the sequential order of the ...
Efficient Parallel Zonal Statistics on Large-Scale Global Biodiversity Data on GPUs
Analyzing how species are distributed on the Earth has been one of the fundamental questions in the intersections of environmental sciences, geosciences and biological sciences. With world-wide data contributions, more than 375 million species ...
Fast exact parallel map overlay using a two-level uniform grid
We present EPUG-Overlay (Exact Parallel Uniform Grid Overlay), an algorithm to overlay two maps that is fast and parallel, has no roundoff errors, and is freely available. EPUG-Overlay combines several novel aspects. It represents coordinates with ...
Index Terms
- Proceedings of the 4th International ACM SIGSPATIAL Workshop on Analytics for Big Geospatial Data
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Acceptance Rates
| Year | Submitted | Accepted | Rate |
|---|---|---|---|
| BigSpatial '22 | 14 | 5 | 36% |
| BigSpatial '20 | 9 | 7 | 78% |
| BigSpatial '19 | 8 | 4 | 50% |
| BigSpatial '16 | 14 | 8 | 57% |
| BigSpatial '14 | 13 | 8 | 62% |
| Overall | 58 | 32 | 55% |