NPS is conducting research in the use of imaging spectrometry (hyperspectral imagery or “HSI”) remote-sensing techniques for characterization of Earth surface materials for military and civilian applications. This work focuses on the development and application of new approaches to the analysis of visible and near infrared (VNIR), shortwave infrared (SWIR), and long wave infrared (LWIR) imaging spectrometer data.
We are interested in a broad range of topics, including (1) full-range spectral analysis for improving materials identification and mapping; (2) approaches for improved analysis of reflectance and emission spectra, spectral variability, and spectral libraries; (3) new approaches to the use of airborne, satellite, and/or ground-based hyperspectral systems for in-situ identification, characterization, and mapping of surface materials; (4) categorization of spectral characteristics in the littoral zone to include submerged and near-shore materials; (5) characterization and mapping of natural hazards (landslides, debris flows, avalanches, post earthquake response, volcanoes) using hyperspectral remote-sensing approaches; (6) detection, identification, and characterization of night lights based on their spectral signatures, changes in lighting over time, and possible military/intelligence applications; (7) integration of HSI, LiDAR, SAR and other datasets (multimodal analysis and data fusion) and improved approaches and tools for combined analysis and visualization of these disparate datasets; and (8) development of case histories for use in graduate-level course preparation and teaching.
The Associate should have a strong math, physics, and Earth science background, and remote-sensing analysis skills. Previous experience with imaging spectrometer/hyperspectral data analysis required. Software development capabilities and familiarity with the commercial software packages IDL, ENVI, and ArcGIS are highly desirable. Field experience in data collection efforts is important, including work with field spectrometers.
Kruse FA, Perry SL: Applied Remote Sensing 3, 033504: doi:10.l 117/1.3081548, 2009
Taranik JV, Aslett ZL: Reviews in Economic Geology 16: 83, 2009
Remote sensing; Imaging spectrometry; Sensor fusion; Hyperspectral analysis; HSI;