Mapping the risks : assessing the homeland security implications of publicly available geospatial information
Assesses the homeland security implications of publicly available geospatial data and information. Following the attacks of September 11, 2001, many agencies within the federal government began restricting some of their publicly available geospatial data and information from such sources as the World Wide Web. As time passes, however, decisionmakers have begun to ask whether and how such information specifically helps potential attackers, including terrorists, to select U.S. homeland sites and prepare for better attacks. The research detailed in this book aims to assist decisionmakers tasked with the responsibility of choosing which geospatial information to make available and which to restrict.
Extended Abstract Commercial High-Resolution Satellite Imagery: Access, Privacy, and Security Issues for Indian Nations and Tribes in the United States
Over the last few years, a number of high-resolution commercial remote sensing satellites have been deployed, producing images of objects on the ground as small as two feet (0.6-m) in near real-time.1 Future satellites will support even higher resolutions. For example, the U.S. National Oceanic and Atmospheric Administration (NOAA) recently granted Space Imaging, Inc. a license to build and launch a satellite with a ground resolution of less than one foot (0.25-m).2 The United States (U.S.), however, is not alone in developing remote sensing technology. Other countries, including Canada, France, Israel, Japan, China, Brazil, India, and Australia, have functioning or proposed Earth observation satellites.3
Detection of Fractures Based on Directional Filtering in Image Logging
According to the feature of the direction of fractures in image logging, a method of fracture detection in image logging based on directional filtering is presented in this paper. The fracture image is filtered by the corresponding filter based on the local direction of fractures, which enhances the fracture traces in the direction of fractures in image logging. The final fracture traces are extracted by the combination of the results of both directional filtering and the threshold segmentation. Experimental results show this method effectively detect the fractures in image logging.