原文传递
Using Neural Networks to Correlate Satellite Imagery and Ground-Truth Data; Final rept
| 题名： | Using Neural Networks to Correlate Satellite Imagery and Ground-Truth Data; Final rept |
| 作者： | Wu, X.; Westervelt, J. D. |
| 关键词： | Image processing; Natural resources; Neural nets; Correlation; Nonlinear systems; Land areas; Army training; Artificial satellites; Germany; Images; Installation; Maps; Measurement; Standards; Tools; Training; Military applications; Systems approach |
| 摘要： | Current approaches to evaluating the condition of natural resources on Army training and testing lands are statistically based and attempt to generate rational mathematical formulae that characterize the relationship between satellite imagery and ground-truth data. Even in the hands of a well trained image processing expert, the application of standard image processing tools can yield varying results. Army land managers need an alternate approach for correlating satellite imagery to ground-truth measurements. This approach can be found in the application of neural networks. This report presents the research results of using neural networks as a computational tool to correlate ground-truth data with satellite imagery for Hohenfels, Germany, and to turn the imagery into maps of the installation. Satellite imagery, Neural networks, Land Condition Trend Analysis (LCTA), Geographic Resource Analysis Support System (GRASS). |
| 总页数： | 55p |
| 报告类型： | 科技报告 |
相关文献
- Flight data acquisition methodology for validation of passive ranging algorithms for obstacle avoidance
- Assessing Installation Ethnobotanical Resources Using Land Condition Trend Analysis (LCTA) Data: A Fort Riley, Kansas, Case Study; Final rept
- Convolutional Neural Networks For Detection And Classification Of Maritime Vessels In Electro-Optical Satellite Imagery.
- Land Condition Trend Analysis Data: Power Analysis; Final rept
- Super synchronization for fused video and time-series neural network training
- DEVELOPMENT OF THE LTPP CLIMATIC DATABASE.
检索历史
应用推荐
