Brown, Richard B. | Search NASA

NASA NTRS2012

Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing

Geospatial resource assessments frequently require timely geospatial data processing that involves large multivariate remote sensing data sets. In particular, for disasters, response requires rapid access to large data volumes, substantial storage space and high performance processing capability. The processing and distribution of this data into usable information products requires a processing pipeline that can efficiently manage the required storage, computing utilities, and data handling requirements. In recent years, with the availability of cloud computing technology, cloud processing platforms have made available a powerful new computing infrastructure resource that can meet this need. To assess the utility of this resource, this project investigates cloud computing platforms for bulk, automated geoprocessing capabilities with respect to data handling and application development requirements. This presentation is of work being conducted by Applied Sciences Program Office at NASA-Stennis Space Center. A prototypical set of image manipulation and transformation processes that incorporate sample Unmanned Airborne System data were developed to create value-added products and tested for implementation on the "cloud". This project outlines the steps involved in creating and testing of open source software developed process code on a local prototype platform, and then transitioning this code with associated environment requirements into an analogous, but memory and processor enhanced cloud platform. A data processing cloud was used to store both standard digital camera panchromatic and multi-band image data, which were subsequently subjected to standard image processing functions such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), band stacking, reprojection, and other similar type data processes. Cloud infrastructure service providers were evaluated by taking these locally tested processing functions, and then applying them to a given cloud-enabled infrastructure to assesses and compare environment setup options and enabled technologies. This project reviews findings that were observed when cloud platforms were evaluated for bulk geoprocessing capabilities based on data handling and application development requirements.

Brown, Richard B.↗

NASA NTRS2010

Creation of High Resolution Terrain Models of Barringer Meteorite Crater (Meteor Crater) Using Photogrammetry and Terrestrial Laser Scanning Methods

Barringer Meteorite Crater or Meteor Crater, AZ, has been a site of high interest for lunar and Mars analog crater and terrain studies since the early days of the Apollo-Saturn program. It continues to be a site of exceptional interest to lunar, Mars, and other planetary crater and impact analog studies because of its relatively young age (est. 50 thousand years) and well-preserved structure. High resolution (2 meter to 1 decimeter) digital terrain models of Meteor Crater in whole or in part were created at NASA Stennis Space Center to support several lunar surface analog modeling activities using photogrammetric and ground based laser scanning techniques. The dataset created by this activity provides new and highly accurate 3D models of the inside slope of the crater as well as the downslope rock distribution of the western ejecta field. The data are presented to the science community for possible use in furthering studies of Meteor Crater and impact craters in general as well as its current near term lunar exploration use in providing a beneficial test model for lunar surface analog modeling and surface operation studies.

Brown, Richard B.↗

NASA NTRS2009

Coastal Online Analysis and Synthesis Tool 2.0 (COAST)

The Coastal Online Assessment and Synthesis Tool (COAST) 3D geobrowser has been developed to integrate disparate coastal datasets from NASA and other sources into a desktop tool that provides new data visualization and analysis capabilities for coastal researchers, managers, and residents. It is built upon the widely used NASA-developed open source World Wind geobrowser from NASA Ames (Patrick Hogan et al.) .Net and C# version is used for development. It is leveraged off of World Wind community shared code samples and COAST 2.0 enhancement direction is based on Coastal science community feedback and needs assessment (GOMA). The main objective is to empower the user to bring more user-meaningful data into multi-layered, multi-temporal spatial context.

Brown, Richard B.↗