A procedure for developing an acceptance test for airborne bathymetric lidar data application to NOAA charts in shallow waters

National Oceanic and Atmospheric Administration (NOAA) hydrographic data is typically acquired using sonar systems, with a small percent acquired via airborne lidar bathymetry for near‐shore areas. This study investigated an integrated approach for meeting NOAA’s hydrographic survey requirements for near‐shore areas of NOAA charts, using the existing topographic‐bathymetric lidar data from USACE’s National Coastal Mapping Program (NCMP). Because these existing NCMP bathymetric lidar datasets were not collected to NOAA hydrographic surveying standards, it is unclear if, and under what circumstances, they might aid in meeting certain hydrographic surveying requirements. The NCMP’s bathymetric lidar data are evaluated through a comparison to NOAA’s Office of Coast Survey hydrographic data derived from acoustic surveys. As a result, it is possible to assess if NCMP’s bathymetry can be used to fill in the data gap shoreward of the navigable area limit line (0 to 4 meters) and if there is potential for applying NCMP’s bathymetry lidar data to near‐shore areas deeper than 10 meters. Based on the study results, recommendations will be provided to NOAA for the site conditions where this data will provide the most benefit. Additionally, this analysis may allow the development of future operating procedures and workflows using other topographic‐ bathymetric lidar datasets to help update near‐shore areas of the NOAA charts

Predicting Performance of Channel Assignments in Wireless Mesh Networks through Statistical Interference Estimation

Wireless Mesh Network (WMN) deployments are poised to reduce the reliance on wired infrastructure especially with the advent of the multi-radio multi-channel (MRMC) WMN architecture. But the benefits that MRMC WMNs offer viz., augmented network capacity, uninterrupted connectivity and reduced latency, are depreciated by the detrimental effect of prevalent interference. Interference mitigation is thus a prime objective in WMN deployments. It is often accomplished through prudent channel allocation (CA) schemes which minimize the adverse impact of interference and enhance the network performance. However, a multitude of CA schemes have been proposed in research literature and absence of a CA performance prediction metric, which could aid in the selection of an efficient CA scheme for a given WMN, is often felt. In this work, we offer a fresh characterization of the interference endemic in wireless networks. We then propose a reliable CA performance prediction metric, which employs a statistical interference estimation approach. We carry out a rigorous quantitative assessment of the proposed metric by validating its CA performance predictions with experimental results, recorded from extensive simulations run on an ns-3 802.11g environment

Temporal variability corrections for Advanced Microwave Scanning Radiometer E (AMSR-E) surface soil moisture: case study in Little River Region, Georgia, U. S.

Statistical correction methods, the Cumulative Distribution Function (CDF) matching technique and Regional Statistics Method (RSM) are applied to adjust the limited temporal variability of Advanced Microwave Scanning Radiometer E (AMSR-E) data using the Common Land Model (CLM). The temporal variability adjustment between CLM and AMSR-E data was conducted for annual and seasonal periods for 2003 in the Little River region, GA. The results showed that the statistical correction techniques improved AMSR-E\u27s limited temporal variability as compared to ground-based measurements. The regression slope and intercept improved from 0.210 and 0.112 up to 0.971 and -0.005 for the non-growing season. The R-2 values also modestly improved. The Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) products were able to identify periods having an attenuated microwave brightness signal that are not likely to benefit from these statistical correction techniques

Temporal Variability Corrections for Advanced Microwave Scanning Radiometer E (AMSR-E) Surface Soil Moisture: Case Study in Little River Region, Georgia, U.S.

Statistical correction methods, the Cumulative Distribution Function (CDF) matching technique and Regional Statistics Method (RSM) are applied to adjust the limited temporal variability of Advanced Microwave Scanning Radiometer E (AMSR-E) data using the Common Land Model (CLM). The temporal variability adjustment between CLM and AMSR-E data was conducted for annual and seasonal periods for 2003 in the Little River region, GA. The results showed that the statistical correction techniques improved AMSR-E’s limited temporal variability as compared to ground-based measurements. The regression slope and intercept improved from 0.210 and 0.112 up to 0.971 and -0.005 for the non-growing season. The R2 values also modestly improved. The Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) products were able to identify periods having an attenuated microwave brightness signal that are not likely to benefit from these statistical correction techniques

Shellfish Population and Bed Dimension Assessment in the Great Bay Estuary

This final report details a study funded by the NHEP over the course of 2001-02. The NHF&G Department was funded to delineate oyster bed size and density, monitor oyster disease, and examine the density of clam concentrations in the Great Bay Estuary

Developing an acceptance test for non-hydrographic airborne bathymetric lidar data application to NOAA charts in shallow waters

Hydrographic data of the National Oceanic and Atmospheric Administration are typically acquired using sonar systems, with a small percent acquired via airborne lidar bathymetry for nearshore areas. This study investigates an integrated approach to meeting NOAA’s hydrographic survey requirements for nearshore areas of NOAA charts using existing U.S. Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP) topographic-bathymetric lidar (TBL) data. Because these existing NCMP bathymetric lidar datasets were not collected to NOAA hydrographic surveying standards, it is unclear if, and under what circumstances, they might aid in meeting certain hydrographic surveying requirements. The NCMP bathymetric lidar data were evaluated through a comparison against NOAA’s hydrographic Services Division (HSD) data derived from acoustic surveys. Key goals included assessing whether NCMP bathymetry can be used to fill in the data gap shoreward of the navigable area limit line (0 to 4 m depth) and if there is potential for applying NCMP TBL data to nearshore areas deeper than 10 m. The study results were used to make recommendations for future use of the data in NOAA. Additionally, this work may allow the development of future operating procedures and workflows using other topographicbathymetric lidar datasets to help update nearshore areas of the NOAA charts

The NASA-IGES geometry data visualizer

NIGESview, an interactive software tool for reading, viewing, and translating geometry data available in the Initial Graphics Exchange Specification (IGES) format, is described. NIGESview is designed to read a variety of IGES entities, translate some of the entities, graphically view the data, and output a file in a specific IGES format. The software provides a modern graphical user interface and is designed in a modular fashion so developers can utilize all or part of the code in their grid generation software for computational fluid dynamics

Merit - An evaluation tool for 100% renewable energy provision

Islands represent an interesting challenge in terms of energy supply. A great deal of work has been carried out to look at specific aspects of this issue on different islands. Unfortunately, results from one study cannot be easily applied to other islands due to island-specific resources and energy-use profiles. A quantitative evaluation tool (MERIT) is presented here, which is able to match half-hourly energy demands (heat, electricity, hot water and transport) with local supplies. The program examines the energy balance on any scale, from an individual building through to an entire country, thereby providing a powerful and generic aid to decision making. This paper demonstrates the generality and usefulness of MERIT by using it to analyse the options for creating an energy-autonomous community on a typical, small island off the west coast of Scotland. Results are presented showing the feasibility of accomplishing 100% renewable provision on this island using available local resources

EcoGIS – GIS tools for ecosystem approaches to fisheries management

Executive Summary: The EcoGIS project was launched in September 2004 to investigate how Geographic Information Systems (GIS), marine data, and custom analysis tools can better enable fisheries scientists and managers to adopt Ecosystem Approaches to Fisheries Management (EAFM). EcoGIS is a collaborative effort between NOAA’s National Ocean Service (NOS) and National Marine Fisheries Service (NMFS), and four regional Fishery Management Councils. The project has focused on four priority areas: Fishing Catch and Effort Analysis, Area Characterization, Bycatch Analysis, and Habitat Interactions. Of these four functional areas, the project team first focused on developing a working prototype for catch and effort analysis: the Fishery Mapper Tool. This ArcGIS extension creates time-and-area summarized maps of fishing catch and effort from logbook, observer, or fishery-independent survey data sets. Source data may come from Oracle, Microsoft Access, or other file formats. Feedback from beta-testers of the Fishery Mapper was used to debug the prototype, enhance performance, and add features. This report describes the four priority functional areas, the development of the Fishery Mapper tool, and several themes that emerged through the parallel evolution of the EcoGIS project, the concept and implementation of the broader field of Ecosystem Approaches to Management (EAM), data management practices, and other EAM toolsets. In addition, a set of six succinct recommendations are proposed on page 29. One major conclusion from this work is that there is no single “super-tool” to enable Ecosystem Approaches to Management; as such, tools should be developed for specific purposes with attention given to interoperability and automation. Future work should be coordinated with other GIS development projects in order to provide “value added” and minimize duplication of efforts. In addition to custom tools, the development of cross-cutting Regional Ecosystem Spatial Databases will enable access to quality data to support the analyses required by EAM. GIS tools will be useful in developing Integrated Ecosystem Assessments (IEAs) and providing pre- and post-processing capabilities for spatially-explicit ecosystem models. Continued funding will enable the EcoGIS project to develop GIS tools that are immediately applicable to today’s needs. These tools will enable simplified and efficient data query, the ability to visualize data over time, and ways to synthesize multidimensional data from diverse sources. These capabilities will provide new information for analyzing issues from an ecosystem perspective, which will ultimately result in better understanding of fisheries and better support for decision-making. (PDF file contains 45 pages.