ABSTRACT:ZY-3 has been acquiring high quality imagery since its launch in 2012 and its tri-stereo (three-view or three-line-array) imagery has become one of the top choices for extracting DSM (Digital Surface Model) products in China over the past few years. The ZY-3 tristereo sensors offer users the ability to capture imagery over large regions including an entire territory of a country, such as China, resulting in a large volume of ZY-3 tri-stereo scenes which require timely (e.g., near real time) processing, something that is not currently possible using traditional photogrammetry workstations. This paper presents a high performance computing solution which can efficiently and automatically extract DSM products from ZY-3 tri-stereo imagery. The high performance computing solution leverages certain parallel computing technologies to accelerate computation within an individual scene and then deploys a distributed computing technology to increase the overall data throughput in a robust and efficient manner. By taking advantage of the inherent efficiencies within the high performance computing environment, the DSM extraction process can exploit all combinations offered from a set of tri-stereo images (forward-backword, forward-nadir and backword-nadir). The DSM results merged from all of the potential combinations can minimize blunders (e.g., incorrect matches) and also offer the ability to remove potential occlusions which may exist in a single stereo pair, resulting in improved accuracy and quality versus those that are not merged. Accelerated performance is inherent within each of the individual steps of the DSM extraction workflow, including the collection of ground control points and tie points, image bundle adjustment, the creation of epipolar images, and computing elevations. Preliminary experiments over a large area in China have proven that the high performance computing system can generate high quality and accurate DSM products in a rapid manner.

In this paper, we focus on making desktop Grids adapted to remote sensing application. The initial efforts were made to build a remote sensing retrieval application on the RSIN framework for dealing with climate change, named High Performance Aerosol property Retrieval Software (HiPARS). HiPARS uses integration of applications that access the backend of desktop Grid comprising of office PCs with a client. The HiPARS remote sensing application was built on RSIN framework, which uses the loosecoupled architecture of a desktop client and high throughput computing (HTC) and Grid backend. It allows for fast development by enabling existing code and new algorithms, and provides a familiar graphical environment for remote sensing users. The proposed solution is to transition the current PCs to a desktop Grid that can be cost-effectively sustained. It will be accessible for processing satellite data in quasi real-time, for parameter retrieving or for parallel processing efforts.

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