Abstract
With the popularity of (hyperspectral) remote sensing systems coupled with a myriad of applications, comes the need for investigations into hyperspectral system designs and parameter trade-off studies. Analytical models based on statistical descriptions and signal propagation are efficient methods to examine these parameter trade-off studies, as well as sensitivity studies, with low computational cost. In this paper, a newly developed long wave infrared (LWIR) statistical iterative spectrally smooth temperature/emissivity separation (S-ISSTES) algorithm has been integrated into a widely used full spectrum hyperspectral remote sensing system model known as the forecasting and analysis of spectroradiometric system performance (FASSP) model. This new tool now allows users to perform <i>LWIR</i> full system (<i>i.e</i>., from surface reflectance, to sensor, to retrieve emissivity, to detection analysis) trade studies. In this paper, we validate the LWIR model and detection performance of the new FASSP model followed by illustrating the usage of the full system model by demonstrating trade examples including useful parameter trade studies and subpixel detection sensitivity studies.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Geoscience and Remote Sensing
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
