Center for Remote Sensing and Computational Ecology January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA HyCODE Workshop 2002 Florida Environmental.

Slides:

Advertisements

Similar presentations

Richard Young Optronic Laboratories Kathleen Muray INPHORA

Advertisements

Atmospheric Correction Algorithm for the GOCI Jae Hyun Ahn* Joo-Hyung Ryu* Young Jae Park* Yu-Hwan Ahn* Im Sang Oh** Korea Ocean Research & Development.

Time & Frequency Products R. Peřestý, J. Kraus, SWRM 4 th Data Quality Workshop 2-5 December 2014 GFZ Potsdam Recent results on ACC Data Processing 1 SWARM.

Pisgah High School Chemistry Mike Jones The Hydrogen Spectrum Rev Canton, NC.

Predicting and mapping biomass using remote sensing and GIS techniques; a case of sugarcane in Mumias Kenya Odhiambo J.O, Wayumba G, Inima A, Omuto C.T,

Wavelength Trades for Viewing Titan’s Surface: Can JET’s Science Objectives be Met with a 2-Micron Camera? Jason W. Barnes Associate Professor of Physics.

What do you see? Old woman? Or young girl?  Is turning a light on and off a chemical or physical change? ◦ Physical change  What creates light?

Ocean Currents of the Eastern Gulf of Mexico Robert H. Weisberg Professor, Physical Oceanography College of Marine Science University of South Florida.

Spectrometer Sam Valerio. Shows spectral distribution of a light source in the form of a graph. This specific one in the Imaging Science Center is called.

Hyperspectral Imaging Camera From HORIBA Scientific.

Image classification in natural scenes: Are a few selective spectral channels sufficient?

Motivation Spectroscopy is most important analysis tool in all natural sciences Astrophysics, chemical/material sciences, biomedicine, geophysics,… Industry.

REMOTE SENSING Presented by: Anniken Lydon. What is Remote Sensing? Remote sensing refers to different methods used for the collection of information.

August 5 – 7, 2008NASA Habitats Workshop Optical Properties and Quantitative Remote Sensing of Kelp Forest and Seagrass Habitats Richard C. Zimmerman -

NRL09/21/2004_Davis.1 GOES-R HES-CW Atmospheric Correction Curtiss O. Davis Code 7203 Naval Research Laboratory Washington, DC 20375

Soil Moisture Estimation Using Hyperspectral SWIR Imagery Poster Number IN43B-1184 D. Lewis, Institute for Technology Development, Building 1103, Suite.

2 Remote sensing applications in Oceanography: How much we can see using ocean color? Adapted from lectures by: Martin A Montes Rutgers University Institute.

Multiple-Slit Interference Uniform slits, distance d apart. Light of wavelength. Screen L away “Thin” slits  compared to d) L y  L >> d then path length.

Bio-Optical Assessment of Giant Kelp Dynamics Richard.C. Zimmerman 1, W. Paul Bissett 2, Daniel C. Reed 3 1 Dept. Ocean Earth & Atmospheric Sciences, Old.

May 12-15, 2011 (red) May 6-11, 2011 (light red) Permanent Water (blue)

Physics for Scientists and Engineers II, Summer Semester Lecture 27: July 31 st 2009 Physics for Scientists and Engineers II.

Physical Oceanographic Observations and Models in Support of the WFS HyCODE College of Marine Science University of South Florida St. Petersburg, FL HyCode.

Center for Remote Sensing and Computational Ecology January16-18, 2003ONR HyCODE Workshop Miami, FL IOP and Rrs Predictive Modeling.

June 2007SBC LTER Annual Meeting Bio-Optical Assessment of Giant kelp Dynamics Richard C. Zimmerman Old Dominion University Norfolk VA W. Paul Bissett.

12/28/2001 #1 LEO 2001 IN SITU DATA Profiling Optics and Water Return (POWR) Package Joe Rhea and Gia Lamela.

NOAA Research and Operations Marine Optical Buoy Design Review July 18-19, 2006 Plan for calibration and maintenance of AHAB Uncertainty Budget: Laboratory.

Center for Remote Sensing and Computational Ecology PREDICTION OF HYPERSPECTRAL IOPs ON THE WEST FLORIDA SHELF W. Paul Bissett Florida Environmental Research.

1. What is light and how do we describe it? 2. What are the physical units that we use to describe light? 1. Be able to convert between them and use.

Atmospheric Correction Algorithms for Remote Sensing of Open and Coastal Waters Zia Ahmad Ocean Biology Processing Group (OBPG) NASA- Goddard Space Flight.

The use of MOD09 product and in situ data in a reservoir Valério, A.M.; Kampel, M.; Stech, J.L. alineval, milton, stech COSPAR Training.

SeaDAS Training ~ NASA Ocean Biology Processing Group 1 Level-2 ocean color data processing basics NASA Ocean Biology Processing Group Goddard Space Flight.

Radiometric and Geometric Correction

Blue: Histogram of normalised deviation from “true” value; Red: Gaussian fit to histogram Presented at ESA Hyperspectral Workshop 2010, March 16-19, Frascati,

U.S. Department of the Interior U.S. Geological Survey Multispectral Remote Sensing of Benthic Environments Christopher Moses, Ph.D. Jacobs Technology.

Introduction To describe the dynamics of the global carbon cycle requires an accurate determination of the spatial and temporal distribution of photosynthetic.

Estimating Water Optical Properties, Water Depth and Bottom Albedo Using High Resolution Satellite Imagery for Coastal Habitat Mapping S. C. Liew #, P.

VSF as a proxy for Particle Size Distribution Pauline Stephen.

Diffraction gratings let us measure wavelengths by separating the diffraction maxima associated with different wavelengths. In order to distinguish two.

Examples of Closure Between Measurements and HydroLight Predictions Curtis D. Mobley Sequoia Scientific, Inc. Bellevue, Washington Maine 2007.

Optical properties Satellite observation ? T,H 2 O… From dust microphysical properties to dust hyperspectral infrared remote sensing Clémence Pierangelo.

The Second TEMPO Science Team Meeting Physical Basis of the Near-UV Aerosol Algorithm Omar Torres NASA Goddard Space Flight Center Atmospheric Chemistry.

Validation of MODIS Snow Mapping Algorithm Jiancheng Shi Institute for Computational Earth System Science University of California, Santa Barbara.

State of Engineering in Precision Agriculture, Boundaries and Limits for Agronomy.

NASA’s Coastal and Ocean Airborne Science Testbed (COAST) L. Guild 1 *, J. Dungan 1, M. Edwards 1, P. Russell 1, S. Hooker 2, J. Myers 3, J. Morrow 4,

A model for predicting spectral signature of suspended sediments Vijay Garg & Indrajeet Chaubey † ECOLOGICAL ENGINEERING GROUP † Respectively, Graduate.

Interference and Diffraction. Conditions for Interference Coherent Sources - The phase between waves from the multiple sources must be constant. Monochromatic.

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Image: MODIS Land Group,

Industrial Affiliates March 2 nd, Ranging-Imaging Spectrometer Brian A. Kinder Advisor: Dr. Eustace Dereniak Optical Detection Lab Optical Sciences.

MODIS Near-IR Water Vapor and Cirrus Reflectance Algorithms & Recent Updates for Collection 5 Bo-Cai Gao Remote Sensing Division, Code 7232, Naval Research.

AATS-14 measurements during COAST J. Livingston R. Johnson M. Kacenelenbogen C. Chang P. Russell.

Hydrolight Lab: Part 1 July 18th, 2013.

SOC Camera Performance Systematic Assessment Jin Wu 11/20/2013.

OC3522Summer 2001 OC Remote Sensing of the Atmosphere and Ocean - Summer 2001 Ocean Color.

UNIT 2 – MODULE 5: Multispectral, Thermal & Hyperspectral Sensing

Electromagnetic Radiation

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 STAR Enterprise Synthesis.

Project Participants and Consultants

A Atmospheric Correction Update and ACIX Status

Using a Radio Telescope

Hyperspectral Sensing – Imaging Spectroscopy

Electromagnetic Spectrum

Diffraction Grating Resolving Power

RapidEye 1-5 (Germany) Resolution: 5 m Bands: Altitude: 630 km

What Is Spectral Imaging? An Introduction

Planning a Remote Sensing Project

Developing Spectral Corrections / SRF Retrievals Tim Hewison

BASIC HYPER SPECTRAL IMAGING

How we do Spectroscopy An Overview

Build a Remote Sensing Satellite

MERIS Level 1b processing Ludovic Bourg

Presentation transcript:

Center for Remote Sensing and Computational Ecology January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA HyCODE Workshop 2002 Florida Environmental Research Institute

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Modeling West Florida Shelf

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Modeling West Florida Shelf

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Modeling West Florida Shelf

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Modeling LEO-15

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Modeling LEO-15

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA West Florida Shelf April 16 th, 17 th, 18 th, 19 th, 21 th, 23 th, 24 th, and 26 th 23 th, 24 th, and 26 th LEO-15 July 21 th, 23 th, 27 th, and 31 th, August 1 th and 2 nd Hyperspectral Remote Sensing West Florida Shelf and LEO-15

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Zero Order Light –Direct reflection off diffraction grating, >> greater than other orders combined. Out-of-band response. –On order of of signal wavelength distributed across all others in a non-gaussian distribution. Calibration light source –Red rich lamps do not approximate blue rich scene. Out-of-band response causes errors in gain calculations. Extrapolation of calibration light series to data series. –Only a small fraction of wavelengths had calibration series that actually included water data collections. Calibration Issues

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Zero Order Light Pre-Mask

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Out-of-Band Response Post-Mask

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Calibration Light Source

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Beach and Water Spectra LEO-15

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Initial Calibration Series WFS

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Initial Calibration Series LEO-15

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Future Calibration Series

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Out-of-Band Response/Lamp Source Optimization Scheme

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Post-Optimization Calibration

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Geo-Correction Camera Timing Errors

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Geo-Correction CMIGIT Timing Errors

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Geo-Correction Effects of CMIGIT Errors

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Geo-Corrected LEO-15

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Spatial Shift LEO-15

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA PHILLS-1 and PHILLS-2 Inter-Comparison

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA PHILLS-1 and PHILLS-2 Inter-Comparison

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Point 2 Point 1 Point 3 Released Data

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Active Archive

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Active Archive

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Active Archive

January 7-9, 2002HyCODE Workshop 2002 Santa Barbara, CA Outstanding Issues Modeling –Phase function matters to Rrs! Prediction of Rrs will require particle specific phase functions. Hyperspectral –Some indication that the spectral calibration has shifted 0 – 3 nm, spectrally dependent. –Atmospheric correction requires much more attention to parameter choices. –Inter-comparison of 5 satellites and 5 aircraft!