PPT-Understanding Multispectral Reflectance

Remote sensing measures reflected light EMR Different materials reflect EMR differently Basis for distinguishing materials Reflectance Learning Objectives Be able to define reflectance qualitatively and quantitatively. source sensor surface element normal brPage 3br BRDF Bidirectional Reflectance Distribution Function T I source viewing direction surface element normal incident direction I T I T surface I T surface I T Irradiance at Surface in direction I T Radian The reflectance map depends both on the nature o the surface layers of th object being imaged and the distribution o light sources Recently a unified approach t the specification of surface reflectance in terms of both incident and reflected beam ge Steve Miller . (. Steven.Miller@colostate.edu. ). Updated: 27 July 2012. Lunar Spectral Irradiance Model. Miller and Turner, 2009. IEEE Trans. . Geosci. . Rem. Sens., 47(7), 2316-2329. . A . lunar irradiance prediction model . Intercomparisons. Lessons Learned. K. Thome. 1. , N. Fox. 2. 1. NASA/GSFC , . 2. National Physical Laboratory. Summarize lessons learned during joint field campaigns to . Tuz. . Golu. , Turkey. 10 countries and 13 organizations. Spatial. Spatial. Hyperspectral Sensing . – Imaging Spectroscopy. What is Hyperspectral Sensing?. Z = Spectral Bands. X. Y. Data Cube. – a way to visualize the data. Multispectral. Hyperspectral. Remote sensing measures reflected “light” (EMR). Different materials reflect EMR differently. Basis for distinguishing materials. Reflectance. Learning Objectives. Be able to define reflectance qualitatively and quantitatively.. 2. . NOAA/STAR; 3. UMBC JCET; 4. UMD ESSIC; 5. SRG. Introduction. Surface reflectance ratios are crucial to the VIIRS (Visible Infrared Imaging Radiometer Suite) aerosol optical thickness (AOT) retrieval over land for dark pixels.  Having better estimates of these ratios can improve AOT retrievals.  . Chengquan. Huang. 1,2. . Min Feng. 1,2. , . Joseph O. . Sexton. 1,2. , . Raghuram. . Narasimhan. 1,2. , . Saurabh. . Channan. 1,2. , Jeff . Masek. 3. , Eric . Vermote. 2. , . Feng. Gao. 4. , John Townshend. 2. . NOAA/STAR; 3. UMBC JCET; 4. UMD ESSIC; 5. SRG. Introduction. Surface reflectance ratios are crucial to the VIIRS (Visible Infrared Imaging Radiometer Suite) aerosol optical thickness (AOT) retrieval over land for dark pixels.  Having better estimates of these ratios can improve AOT retrievals.  . 15-463, 15-663, 15-862. Computational Photography. Fall 2018, Lecture 16. http://graphics.cs.cmu.edu/courses/15-463. Homework 4 is still ongoing. - Any questions?. I will try to go over project ideas tonight.. GOES-R Algorithm Working Group Aerosol, Atmospheric Chemistry and Air Quality (AAA) Application Team. 1. Presentations. Suspended Matter/Aerosol Optical Depth Algorithm – . Istvan. Laszlo, STAR. Aerosol Detection Algorithm – . Alison Wright and Yaning Wang. EN.520.483.01.SP20 Bio-Photonics Laboratory. Skin is the largest organ in the human body and consists of two principal layers: the epidermis and the dermis. The epidermis is a stratified squamous epithelium, which consists of 4 types of cells:[3]. Fusion FlexEye. TM. High performance multispectral cameras tailored to your. application requirements. 2. Application. examples. Crop health, intelligent farming, environmental…. Inspection of fruits, vegetables, nuts, grains, tea leaves…. Carol J. Bruegge. Science driver: . The radiometric response of sensors change with time, and must be updated during the mission life. For example, Orbiting Carbon Observatory (OCO) requires 5% radiometric uncertainty in order to meet its XCO2 retrieval uncertainty of 1 ppm. Vicarious calibration provides this, but for sensors that view off-nadir, such as OCO, a necessary input is a model of the test site bi-directional reflectance factor (BRF)..