With the increase in amount of remote sensing data, there have been efforts to efficiently process it to help ecologists and geographers answer queries. However, they often need to process this data in combination with vector data, for example, city boundaries. Existing efforts require one dataset to be converted to the other representation, which is extremely inefficient for large datasets. In this demonstration, we focus on the zonal statistics problem, which computes the statistics over a raster layer for each polygon in a vector layer. We demonstrate three approaches, vector-based, raster-based, and raptor-based approaches. The latter is a recent effort of combining raster and vector data without a need of any conversion. This demo will allow users to run their own queries in any of the three methods and observe the differences in their performance depending on different raster and vector dataset sizes.
|Original language||English (US)|
|Number of pages||4|
|Journal||Proceedings of the VLDB Endowment|
|State||Published - 2018|
|Event||45th International Conference on Very Large Data Bases, VLDB 2019 - Los Angeles, United States|
Duration: Aug 26 2017 → Aug 30 2017
Bibliographical notePublisher Copyright:
© 2019 VLDB Endowment.