During recent years, cluster systems have played a more important role in the architecture design of high-performance computing area which is cost-effective and efficient parallel computing system able to satisfy specific computational requirements in the earth and space sciences communities. This paper presents a powerful cluster system built by Satellite Environment Center, Ministry of Environment Protection of China that is designed to process massive remote sensing data of HJ-1 satellites automatically everyday. The architecture of this cluster system including hardware device layer, network layer, OS/FS layer, middleware layer and application layer have been given. To verify the performance of our cluster system, image registration has been chose to experiment with one scene of HJ-1 CCD sensor. The experiments of imagery registration shows that it is an effective system to improve the efficiency of data processing, which could provide a response rapidly in applications that certainly demand, such as wild land fire monitoring and tracking, oil spill monitoring, military target detection, etc. Further work would focus on the comprehensive parallel design and implementations of remote sensing data processing.
The increasing volume of industrial solid wastes presents a critical problem for the global environment. In the detection and monitoring of these industrial solid wastes, the traditional field methods are generally expensive and time consuming. With the advantages of quick observations taken at a large area, remote sensing provides an effective means for detecting and monitoring the industrial solid wastes in a large scale. In this paper, we employ an object-oriented method for detecting the industrial solid waste from HJ satellite imagery. We select phosphogypsum which is a typical industrial solid waste as our target. Our study area is located in Fuquan in Guizhou province of China. The object oriented method we adopted consists of the following steps: 1) Multiresolution segmentation method is adopted to segment the remote sensing images for obtaining the object-based images. 2) Build the feature knowledge set of the object types. 3) Detect the industrial solid wastes based on the object-oriented decision tree rule set. We analyze the heterogeneity in features of different objects. According to the feature heterogeneity, an object-oriented decision tree rule set is then built for aiding the identification of industrial solid waste. Then, based on this decision tree rule set, the industrial solid waste can be identified automatically from remote sensing images. Finally, the identified results are validated using ground survey data. Experiments and results indicate that the object-oriented method provides an effective method for detecting industrial solid wastes.
As a kind of huge environmental risk source, tailings pond could cause a huge environmental disaster to the downstream area once an accident happened on it. Therefore it has become one key target of the environmental regulation in china. Especially, recently environmental emergencies caused by tailings pond are growing rapidly in China, the environmental emergency management of the tailings pond has been confronting with a severe situation. However, the regulatory agency is badly weak in the environmental regulation of tailings pond, due to the using of ground surveys and statistics which is costly, laborious and time consuming, and the lacking of strong technical and information support. Therefore, in this paper, according to the actual needs of the environmental emergency management of tailings pond, we firstly make a brief analysis of the characteristics of the tailings pond and the advantages and capability of remote sensing technology, and then proposed a comprehensive and systematic indexes system and the method of environmental risk monitoring of tailings pond based on remote sensing and GIS. The indexes system not only considers factors from the upstream area, the pond area and the downstream area in a perspective of the risk space theory, but also considers factors from risk source, risk receptor and risk control mechanism in a perspective of risk systems theory. Given that Zhangjiakou city has up to 580 tailings pond and is nearly located upstream of the water source of Beijing, so finally we apply the proposed indexes system and method in Zhangjiakou area in China to help collect environmental risk data of tailings pond in that area and find out it works well. Through the use case in Zhajiakou, the technique of using remote sensing to monitor environmental risk of tailings pond is feasible and effective, and would contribute to the establishment of ‘Space-Ground’ monitoring network of tailings pond in future.
The application of High Performance Computing (HPC) technology to remote sensing data processing is one solution to
meet the requirements of remote sensing real- or near-real-time processing capabilities. We presented a cluster-based
parallel processing system for HJ-1 satellites data, named Cluster Pro. This paper presents the basic architecture and
implementation of the system. We did imagery mosaic experiment with the Cluster Pro, where the HJ-1 CCD data in
Beijing city was used. The experiments showed that the Cluster Pro was a useful system to improve the efficiency of data
processing. Further work would focus on the comprehensive parallel design and implementations of remote sensing data