Oil pollution is a very important aspect in the environmental field. Oil pollution is an important subject due to its capacity to adversely affect animals, aquatic life, vegetation and drinking water. The movement of open water oil spills can be affected by mind, waves and tides. Land based oil spills are often affected by rain and temperature. It is important to have an accurate management of the cleanup. Remote sensing and in particular hyper-spectral capabilities, are being use to identify oil spills and prevent worse problems. In addition to this capability, this technology can be used for federal and state compliance of petroleum related companies. There are several hyper-spectral sensors used in the identification of oil spills. One commonly use sensor is the Airborne Imaging Spectroradiometer for Applications (AISA). The main concern associated with the use of these sensors is the potential for false identification of oil spills. The use of AISA to identify an oil spill over the Patuxent River is an example of how this tool can assist with investigating an oil pipeline accident, and its potential to affect the surrounding environment. A scenario like this also serves as a good test of the accuracy with which spills may be identified using new airborne sensors.
This paper analyzes the feasibility and performance of HSI systems for medical diagnosis as well as for food safety. Illness prevention and early disease detection are key elements for maintaining good health. Health care practitioners worldwide rely on innovative electronic devices to accurately identify disease. Hyperspectral imaging (HSI) is an emerging technique that may provide a less invasive procedure than conventional diagnostic imaging. By analyzing reflected and fluorescent light applied to the human body, a HSI system serves as a diagnostic tool as well as a method for evaluating the effectiveness of applied therapies. The safe supply and production of food is also of paramount importance to public health illness prevention. Although this paper will focus on imaging and spectroscopy in food inspection procedures -- the detection of contaminated food sources -- to ensure food quality, HSI also shows promise in detecting pesticide levels in food production (agriculture.)
The Squeezed Signature Analysis (SSA) hyperspectral classification method is presented as a fast method to compare the target spectral signature to all the signatures in the spectral library. This discussion includes the possible use of this technique on-board a hypothetical remote sensing system that could take advantage of parallel computations.
KEYWORDS: Roads, Global Positioning System, Geographic information systems, Hyperspectral imaging, Remote sensing, Feature extraction, Receivers, Safety, Chemical elements, Decision support systems
Public Works facilities require up-to-date information on the health status of the road network they maintain. However, roadway maintenance and rehabilitation involves the greatest portion of a municipality's annual operating budget. Government officials use various technologies such as a pavement management system to assist in making better decisions about their roadways systems, pavement condition, history, and projects. Traditionally, manual surveying has served as the method of obtaining this information. To better assist in decision-making, a regionally specific spectral library for urban areas is being developed and used in conjunction with hyperspecrtal imaging, to map urban materials and pavement conditions. A Geographical Information and Positioning System (GIS/GPS) will also be implemented to overlay relative locations. This paper will examine the benefits of using hyperspectral imaging over traditional methods of roadway maintenance and rehabilitation for pavement management applications. In doing so, we will identify spatial and spectral requirements for successful large-scale road feature extraction.
Despite the considerable slowdown of wetlands loss in conterminous U.S., management of these valuable resources continues to be an area of interest for environmental professionals. The development of remote sensing technologies, particularly hyperspectral, offers an alternative for ecological and functional assessment of these sites. Extensive hyperspectral data image collected from the various sensor types can be analyzed by discriminatory techniques for reflectance analysis. Although data processing can become tedious, it enables scientists to target the various inherited characteristics of large wetland areas such as vegetative species and habitats. This information can be applied to determine the health and functionality of the nation's wetlands for means of wetland characterization, assessment, management and possible restorative efforts to bring a consistent and fundamental change on how these are managed today.
Precision farming relies on the cost effectiveness of collecting and interpreting data, which describes the variations of agricultural conditions such as crop stresses, nutrient deficiencies, water stresses, or pest infestation. Hyperspectral remote sensing from satellites and airborne sensors can be a way to obtain data needed to develop site-specific farming management strategies. The primary objective of the hyperspectral applications in precision farming is to provide farmers with a technology, which can detect specific crop conditions that can be used to program variable-rate applications. Applications of water, pesticides, and fertilizer can be tailored to the needs of the agricultural crops, based on the conditions reflected on the imagery. This paper presents an experimental study performed in Beltsville, Maryland for assessing the plant density and nutrient uptake of corn using a simple photographic method from a model airplane versus obtaining hyperspectral imagery from an airborne sensor. The hyperspectral sensor utilized in this study was the AISA sensor. These remote sensors can measure the temperature of plants; or to be more specific, they can measure how much energy plants emit at the visible and near-infrared wavelengths of the spectrum, such as water and vegetation.
KEYWORDS: Sensors, Telecommunications, Information security, Network security, Geographic information systems, Control systems, Computer security, Intelligence systems, Data communications, Sensor networks
An overview is given of the Home of the 21st Century Laboratory. The laboratory is operated as a joint program with America On-Line and George Washington University. The program is described with illustrations and discussion of the systems that are part of the laboratory. A Geospatial Information Systems (GIS) was developed as an integrating data management framework for activities and data management functions within the home. A variety of household information is collected and stored in multiple layers of information within the GIS system for easy access by members of the home. Technology options currently available for application in the home are described and assessed.
A wide variety of hyper-spectral (HS) sensors and collection platforms are in existence. This paper investigates hyper-spectral imaging systems (HIS) worldwide in order to compose a comprehensive listing of these systems. A meta-data structure was developed to identify basic parameter information for all sensors that were reviewed. Systems were grouped into two primary categories of space borne and air borne. Sensors were further grouped into three types of imaging spectrometers; whiskbroom line array band interleaved by pixel, push broom area array band interleaved by line and framing camera band sequential methodology. Several sensor systems are presented using the meta-data structure and parameters developed for the analysis. A summary table identifying all sensor systems that were evaluated is presented. Applications include geo-environmental studies, aerosol release, materials identification, agricultural studies, atmospheric studies, and many others.
Hyperspectral imagining has been recently been used to obtain several water quality parameters in water bodies either inland or in oceans. Optical and thermal have proven that spatial and temporal information needed to track and understand trend changes for these water quality parameters will result in developing better management practices for improving water quality of water bodies. This paper will review water quality parameters Chlorophyll (Chl), Dissolved Organic Carbon (DOC), and Total Suspended Solids (TSS) obtained for the Sakonnet River in Narragansett Bay, Rhode Island using the AVIRIS Sensor. The AVIRIS Sensor should improve the assessment and the definition of locations and pollutant concentrations of point and non-point sources. It will provide for necessary monitoring data to follow the clean up efforts and locate the necessary water and wastewater infrastructure to eliminate these point and non-point sources. This hyperspectral application would enhance the evaluation by both point and non-point sources, improve upon and partially replace expenses, labor intensive field sampling, and allow for economical sampling and mapping of large geographical areas.
A wide variety of hyper-spectral (HS) sensors and collection platforms are in existence. This paper investigates hyper-spectral imaging systems (HIS) worldwide in order to address issues associated with the better both airborne and space based systems are included in the review. Examples of the sensors include ENVISAT, SCIAMACHY, TERRA, AQUA, MOPITT, MIPAS, AVIRIS, LIDAR, Landsat 7 and others. Applications include geo-environmental studies, aerosol release, materials identification, agricultural studies, atmospheric studies, and many others. Two case studies are presented that address the evaluation of African smog and its effect on the African ecosystem and the evaluation of aerosol pollution in the northeastern region of the United states with particular attention to particulate matter.
KEYWORDS: Cladding, Visualization, 3D modeling, LIDAR, 3D displays, Homeland security, Earth observing sensors, 3D visualizations, 3D vision, Photography
A variety of source data, hardware/software packages, methodology, and techniques exist for the capture, rendering, and navigation of complex three-dimensional (3D) urban terrain. This paper investigates issues, options, and concerns inherent in the movement from 2D to 3D visualization and finally to a display environment in advanced virtual worlds exhibiting four-dimensional (4D) urban terrain, the fourth dimension being time. Methodology options are presented as a matrix for 3D feature development. Proposals and recommendations as to future avenues of research in the subject arena are presented as a roadmap to meeting the challenges of visualization for urban operational planning. Applications include humanitarian, emergency, recovery and relief operations, force protection, threat assessment, pre- and post-incident response, mission planning and rehearsal, law enforcement, and Homeland Defense.
The major focus of the paper is on the use of remote sensing systems in providing planning and advise in support of ground operations at the World Trade Center site and the related debris processing and disposal sites in the New York area. A summary of the World Trade Center recovery effort is presented. This was the largest most complex recovery effort of this nature ever to occur in the United States. Remote sensing was only a part of the total recovery activity but did provide important assistance throughout the recovery operation. Samples of geospatial technologies used in the recovery are reviewed. These include 3-D visualization, thermal infrared imagery, LIDAR data systems, IKONOS one- meter panchromatic imagery, SPOT imagery and the use of digital aerial imagery. The general area of disaster response management is also addressed and the findings of various studies in this area are related to the World Trade Center disaster. Observations and lessons learned from the World Trade Center disaster response are discussed with recommendations for the use of remote sensing systems and products in future disaster situations are presented.
Video imagery collection and analysis is used to understand conditions and dynamic changes within the home environment. This is part of a joint venture between George Washington University and America Online to design, develop and evaluate new technology for the Home of the 21st Century. This initial phase is focused on capture and distribution of image information within the home and over the internet to allow local and remote observation and control of in home systems.
Image spectroscopy was used to evaluate iron oxide acid mine drainage contamination at two U.S. Environmental Protection Agency Super Fund sites located in Colorado and New Mexico. The AVIRIS hyper-spectral remote sensing system developed by the Jet Propulsion Laboratory was used to collect the imagery data used in the analysis. The paper presents an overview of mining methods used in the area of the study, the environmental risks of acid mine drainage and the AVIRIS hyper-spectral sensing system. The two sites evaluated are located in Leadville, Colorado and the Ray Mine site in New Mexico. Imagery spectroscopy was evaluated at these two sites for identifying potential mineral pollutants and mapping their location for cleanup planning and monitoring applications. Results indicate the technology can be a very useful tool for this type of application and location.
KEYWORDS: Associative arrays, Natural disasters, Geographic information systems, Information fusion, Data modeling, Interfaces, Data integration, Decision support systems, Data processing, Earthquakes
Natural disasters have a major impact, globally and within the United States causing injury and loss of life, as well as economic losses. To better address disaster response needs, a task force has been established to leverage technological capabilities to improve disaster response management. Web based geospatial analysis is one of these important capabilities. Samples of geospatial technologies applicable to disaster management are presented. These include 3D visualization, hyperspectral imagery, LIDAR, use of spectral libraries, digital multispectral video, radar imaging systems, photogeologic analysis and geographic information systems. An example scenario of a hurricane with landfall at Mobile, Alabama is used to demonstrate the interoperable use of web-based geospatial information to support decision support systems and assist public information communication.
Recent advances in the field of spectral sensing technology have elucidated the benefits of multispectral and hyperspectral sensing the military and civil user community. These advancements, when properly exploited can provide the additional and improved automated terrain analysis, image understanding, object detection, and material characterization capabilities. the U.S. Army has established a Center of Excellence for Spectral Sensing Technology. This Center conducts collaborative research on, and development and demonstration of spectral sensing, processing and exploitation techniques. The Center's collaborative efforts integrate programs across multiple disciplines and form a baseline program consisting of coordinated technology thrusts. Existing efforts span the domains of sensor hardware, data processing architectures, algorithms, and signal processing and exploitation technologies across wide spectral regions. These thrusts in turn enable progress and performance improvement in the automated analysis, understanding, classification, discrimination, and identification of terrestrial objects, and materials. The participants draw upon common scientific processes and disciplines to approach similar problems related to different categories and domains of phenomenology.
Recent advances in the field of spectral sensing technology have elucidated the benefits of multi-spectral and hyperspectral sensing to the Army's user community. These advancements, when properly exploited can provide the Army with additional and improved automated terrain analysis, image understanding, object detection, and material characterization capabilities. The U.S. Army, led by the Topographic Engineering Center, has established a Center of Excellence for Spectral Sensing Technology. This Center conducts Army wide collaborative research on, and development and demonstration of spectral sensing, processing and exploitation technologies. The Center's collaborative efforts integrate Army programs across multiple disciplines and form a baseline program consisting of coordinated technology thrusts. The program's applied research and demonstration components will in turn support an Army spectral Strategic Technology Objective (STO) that will ultimately support and leverage joint service efforts starting in FY00. Existing efforts span the domains of sensor hardware, data processing architectures, algorithms, and, signal processing and exploitation technologies across wide spectral regions. These thrusts in turn enable progress and performance improvement in the automated analysis, understanding, classification, discrimination, and identification of terrestrial objects, and materials. The participants draw upon common scientific processes and disciplines to attack similar problems related to different categories and domains of phenomenology. This paper describes the Center's program and objectives along with an explanation of the Army's strategy and approach in support of its program objectives.
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