Title :
Data exploitation of HyspIRI observations for precision vegetation mapping
Author :
Prasad, Saurabh ; Bruce, Lori Mann ; Kalluri, Hemanth
Author_Institution :
Geosystems Res. Inst., Mississippi State Univ., Starkville, MS, USA
Abstract :
An imaging spectrometer´s dense recording of radiance values (and consequently derived reflectance values) over a wide region of the electromagnetic spectrum provides the potential to design classification systems that can perform highly accurate ground cover classification and target recognition. The Hyperspectral Infrared Imager (HyspIRI) - a National Research Council (NRC) decadal survey mission is much anticipated by researchers to aid in answering a wide variety of global ecological and anthropological questions. In order to tackle these research topics and effectively exploit the seasonal global imaging spectroscopy provided by HyspIRI, there will be a great need for reliable hyperspectral-based products for use by domain experts. In this work, we create simulated/proxy HyspIRI data from a database of hyperspectral signatures of various vegetation species. We then study the performance of current state-of-the-art pattern classification paradigms for classifying this proxy data. The outcome of this study will provide valuable insight into the potential efficacy of employing HyspIRI data for vegetation mapping and similar remotely sensed pattern classification tasks.
Keywords :
geophysical image processing; image classification; vegetation mapping; Hyperspectral Infrared Imager; HyspIRI observations; National Research Council; decadal survey mission; global imaging spectroscopy; ground cover classification; hyperspectral based products; imaging spectrometer; pattern classification paradigms; precision vegetation mapping; radiance value recording; remotely sensed pattern classification; target recognition; vegetation hyperspectral signature database; Electromagnetic spectrum; Hyperspectral imaging; Hyperspectral sensors; Infrared imaging; Optical imaging; Pattern classification; Reflectivity; Spectroscopy; Target recognition; Vegetation mapping; Hyperspectral; HyspIRI; Image Processing; Pattern Recognition; Vegetation Mapping;
Conference_Titel :
Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009
Conference_Location :
Cape Town
Print_ISBN :
978-1-4244-3394-0
Electronic_ISBN :
978-1-4244-3395-7
DOI :
10.1109/IGARSS.2009.5417494