Dịch từ: Tiếng Việt 40 Trọng Nam bốn, bạn cũng cam cua xa Trãi Jat ADI từ len su tang truong trong Liên tuc kha nang cua cac bi Thiết Đỗ đắc (đã tinh, Khong Chi, sẽ bo nhiều trên cam mờ Đỗ Jat theo sẽ Đỗ doi truong lương tôi) Cac Nguyễn Đỗ Cung Bản hợp tac cac khóa học sẽ diễn ra bo Tang Trọng NAM PHÚC phan tich cua tap Việc đặt là nơi mo Hinh Đỗ Hòa bo luan án ho tro. Ty Lương Trọng Khôi các tang của nơi bạn xa cam ung tiep tuc phat trien. Ngoai ra, na sinh. | Chapter 10 Remote Sensing Grids Architecture and Implementation Samuel D. Gasster The Aerospace Corporation Craig A. Lee The Aerospace Corporation James W. Palko The Aerospace Corporation Contents Introduction .204 Remote Sensing and Sensor Webs .204 Remote Sensing System Architectures and Grid Computing . 205 Remote Sensing Grids Weather Forecasting and Climate Science Grid .209 Derived Functional Requirements and Resources .214 WFCS Grid Services Architecture .217 Remote Sensing Grids Implementation .220 Management and Policy Considerations .220 Data Management .222 Job Management and Grid Monitoring and Testing . 224 Remote Sensing Grids Examples .226 Example 1 Linked Environments for Atmospheric Discovery LEAD .226 Example 2 Landsat Data Continuity Mission LDCM Grid Prototype LGP Project . 228 Example 3 NOAA National Operational Model Archive and Distribution System NoMadS .229 Remote Sensing Grids Acronyms .231 References .232 203 2008 by Taylor Francis Group LLC 204 High-Performance Computing in Remote Sensing Introduction In the last 40 years remote sensing of the Earth has seen a continuous growth in the capabilities of the instrumentation satellites airborne and ground-based sensors that monitor and measure the environment that provides the fundamental data sets and an increase in the complexity of the data analyses and modeling that these data sets support. The rate of increase in the remote sensing data volume continues to grow. Additionally the number of organizations and users is also expanding and is now a worldwide community struggling to share data and resources. These trends necessitate a shift in the way in which remote sensing systems are designed and implemented in order to manage and process these massive data sets and support users worldwide. Grid computing as originally described by
