Rapid Imagery Tile Generation for Remotely Sensed Time-seriesData in the Cloud Environment

Imagery tile caching is becoming an important technique for online Earth observation information sharing .Dynamic disaster and environment monitoring places great pressure on cached tiles for the generation of imagery acquired in real time or recent time. A rapid imagery tile generation approach for time-series imagery is proposed to update a Web map service based on the computing power provided by Map-Reduce，a popular parallel computing paradigm on the cloud. Based on the data locality of Map-Reduce，a strategy for dynamic data partitioning is used to reduce redundant work while spatial distribution and physical storage consistentcy is maintained to improve the data locality. These optimizations aim to provide in a timely way cached tiles for dynamic environment monitoring.Performance testing indicates that this approach is more efficient and scalable than existing similar methods.