Name
Abstract | ||
|---|---|---|
Since the traditional approaches of managing remote sensing image data could no longer deal with the massive data challenges nowadays, we present a method to divide remote sensing image data into blocks based on GeoSOT global discrete grid system and store the data blocks into HBase. Also, a distributed processing method using parallel programming model MapReduce, is designed to deal with the image data blocks. In the end, we verifies the feasibility and efficiency of the proposed approaches in HBase cluster. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | Image management, GeoSOT, HBase, MapReduce |
Field | DocType | ISSN |
Data modeling,Central processing unit,Data-intensive computing,Computer science,Remote sensing,Parallel programming model,Distributed database,Grid system,Data management,Distributed computing | Conference | 2153-6996 |
Citations | PageRank | References |
2 | 0.37 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lin Wang | 1 | 2 | 0.71 |
| Chengqi Cheng | 2 | 19 | 18.71 |
| Shangzhu Wu | 3 | 2 | 0.37 |
| Feilong Wu | 4 | 2 | 0.37 |
| Wan Teng | 5 | 2 | 0.37 |