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Many targets that remote sensing scientists encounter when conducting their research experiments do not lend themselves to laboratory measurement of their surface optical properties. Removal of these targets from the field can change their biotic condition, disturb the surface composition, and change the moisture content of the sample. These parameters, as(More)
The purpose of this research is to show how common computer vision techniques can be implemented in such a way that it is possible to automate the process of analytical photogram-metry. This work develops a workflow that generates a sparse three-dimensional point cloud from a bundle of images using SIFT, RANSAC, and a sparse bundle adjustment along with(More)
Immediately following the 12 January 2010 earthquake in Haiti, a disaster response team from Rochester Institute of Technology, ImageCat Inc., and Kucera International, funded by the Global Facility for Disaster Reduction and Recovery group of the World Bank, collected 0.15 m airborne imagery and two points/m 2 lidar data for 650 km 2 over a period of seven(More)
The ability to detect and identify effluent gases is, and will continue to be, of great importance. This would not only aid in the regulation of pollutants but also in treaty enforcement and monitoring the production of weapons. Considering these applications, finding a way to remotely investigate a gaseous emission is highly desirable. This research(More)
A new algorithm, optimized land surface temperature and emissivity retrieval (OL-STER), is presented to compensate for atmospheric effects and retrieve land surface temperature (LST) and emissivity from airborne thermal infrared hyperspectral data. The OLSTER algorithm is designed to retrieve properties of both natural and man-made materials.(More)
Phototourism is a burgeoning field that uses collections of ground-based photographs to construct a three-dimensional model of a tourist site, using computer vision techniques. These techniques capitalize on the extensive overlap generated by the various visitor-acquired images from which a three-dimensional point cloud can be generated. From there, a(More)
Comparison of the components and the overall fidelity of infrared synthetic image generation models with truth data and imagery is a crucial part of determining model validity and identifying areas in which improvements can be made. The Rochester Institute of Technology's Digital Imaging and Remote Sensing Image Generation Model, DIRSIG, was validated in(More)