Testing Hyperspectral Remote Sensing Monitoring Techniques for Geological CO 2 Storage at Natural Seeps
|
|
- Marvin Conrad Washington
- 5 years ago
- Views:
Transcription
1 Testing Hyperspectral Remote Sensing Monitoring Techniques for Geological CO 2 Storage at Natural Seeps Luke Bateson Clare Fleming Jonathan Pearce British Geological Survey
2 In what ways can EO help with CO 2 monitoring for CCS? Monitoring subsurface plume location InSAR Indirect CO 2 leak detection Vegetation analysis Via effects on geology (CRIUS project in Utah) Hypespectral direct detection of CO 2 Hyperspectral test at BGS campus Hyperspectral work at natural study site in Italy Hyperspectral work over a large industrial source
3 Latera Study Site CO 2 GeoNet is a network of European research institutes to study Geological CO 2 storage Remote sensing work package to study possible CO 2 leak detection from a terrestrial site. Latera, Italy is a natural test site analogous to a leaking CO 2 geological storage site. Extinct caldera structure, known for: High geothermal gradient Cold and warm springs Gas vents Shallow carbonate basement in which there is high heat flow leading to CO 2 release via thermo-metamorphism Rome Tyrrenian Sea km W Adriatic Sea N S E
4 Latera Study Site Gradoli Latera Bolsena Lake Valentano
5 Indirect CO 2 leak detection NDVI (CASI) Thermal (ATM) Aerial photos Lidar intensity Vents mainly identified via changes in vegetation White polygons = possible vents Soil gas testing of 39 of these (colour infill) 40% of our interpretation was correct
6 Direct Detection of CO 2 using Hyperspectral Data CO 2 absorption feature = microns On the edge of water absorption feature Other atmospheric gasses do not absorb at this wavelength HAWK hyperspectral sensor covers this region NERC Airborne Research and Survey Facility have Eagle and Hawk sensors
7 Direct Detection of CO 2 using Hyperspectral Data Band ratio processing results in noisy image: Atmospheric water vapour has an unequal absorption at the CO 2 absorption wavelength (λm) and the reference wavelength (λr). Modify band ratio to account for this unequal water vapour influence.. Use a Continuum Interpolated Band Ratio Interpolated radiance Measured radiance CIBR Radiance m Interpolated _ Radiance m
8 Direct Detection of CO 2 using Hyperspectral Data - Test at BGS
9 True Colour Image of Test Area
10 Test at BGS CIBR result Anomalies detected for white tarpaulin, but also in areas of low signal to noise, such as shadow and across track illumination effects
11 Direct CO 2 detection over natural leaks, Latera NERC ARSF data flown in Italy in September 2007 Ground-truthing data also collected. Field spectrometer readings (ASD) Soil gas flux to atmosphere Soil gas compositions Atmospheric monitoring Weather station Eddy covariance
12 ASD Measurements ASD used for calibration ASD measurements of vegetation surface for a transect across a vent ASD also used try to measure the influence of the additional CO 2. ASD measurement of CO 2. Measurements of the spectralon reference panel in 2 areas: Outside of the vent assumed no extra CO 2 to be present. Directly over the vent, where we assumed additional CO 2 to be present. Measurements were made both at ground level and approximately 1 meter from the ground An average was computed for each measurement, the resulting reflectance was graphed for each category:
13 ASD Measurements of CO 2 Average ASD Reflectance values for areas with and without leaking CO2 Reflectance Absorption Depth (reflectance %) Spectralon reflectance no additional CO 2 Spectralon reflectance additional CO Wavelength (nm) Air CO2 Air No CO2
14 Latera Hawk data 237 spectral bands 920nm to 2500nm (Short Wave Infrared) 2 to 4 meter pixel size About 30% of the imagery covered by shadow. Main area of interest is covered by shadow!
15 CIBR for Latera Density slice of the CIBR White = CIBR using hawk band 166 Yellow = ( nm) Cyanthe = Note noise in the shadow area HAWK true colour image Magenta =
16 Why do we not see the CO 2 in the Hyperspectral imagery? Semi promising results from BGS test ASD results show there is a difference in absorption at wavelengths of interest Possible reasons for not detecting this in Italy: Signal to noise ratio of the sensor Cloud shadow low signal to noise, but still don t see vents which are not in shadow Small amount of leakage gas compared to atmospheric gas It does not have a large enough effect within the area of an image pixel (3-4m square)? Does it disperse to quickly? BGS test suggests this could be a factor Background to the gas is too varied?
17 Direct detection of CO 2 using satellite data Freely available Hyperion data Need a site with high CO 2 flux to detect CO 2 in a relatively low resolution satellite image. Hyperion data exists over Baghdad Oil refinery to south of river
18 Baghdad CIBR Reference bands = 183 ( nm) and 189 ( nm) Measurement band = 185 ( nm)
19 Conclusions Indirect detection works 40% of the time Direct detection with HAWK sensor not giving us the results we want for a natural site SN ratio? Would be interesting to try over a large CO 2 source Direct detection with Hyperion gives promising results over a large industrial site
20 Opportunities for CCS with future ESA Missions Sentinel 1 (C-band Radar) InSAR studies 2 day repeat Sentinel 2 (high res multispectral) Vegetation stress studies Geological mapping Sentinel 5 Atmospheric monitoring will it be sensitive enough to pick up small increases in CO 2 from leaks? Still need - High resolution well calibrated hyperspectral sensors which extend into the thermal region Direct detection via spectral signatures
Hydrocarbon Index an algorithm for hyperspectral detection of hydrocarbons
INT. J. REMOTE SENSING, 20 JUNE, 2004, VOL. 25, NO. 12, 2467 2473 Hydrocarbon Index an algorithm for hyperspectral detection of hydrocarbons F. KÜHN*, K. OPPERMANN and B. HÖRIG Federal Institute for Geosciences
More informationCLASSIFICATION OF NONPHOTOGRAPHIC REMOTE SENSORS
CLASSIFICATION OF NONPHOTOGRAPHIC REMOTE SENSORS PASSIVE ACTIVE DIGITAL CAMERA THERMAL (e.g. TIMS) VIDEO CAMERA MULTI- SPECTRAL SCANNERS VISIBLE & NIR MICROWAVE HYPERSPECTRAL (e.g. AVIRIS) SLAR Real Aperture
More informationREMOTE SENSING OF BENTHIC HABITATS IN SOUTHWESTERN PUERTO RICO
REMOTE SENSING OF BENTHIC HABITATS IN SOUTHWESTERN PUERTO RICO Fernando Gilbes Santaella Dep. of Geology Roy Armstrong Dep. of Marine Sciences University of Puerto Rico at Mayagüez fernando.gilbes@upr.edu
More informationCase Study for Long- Range Beyond Visual Line of Sight Project. March 15, 2018 RMEL Transmission and Planning Conference
Case Study for Long- Range Beyond Visual Line of Sight Project March 15, 2018 RMEL Transmission and Planning Conference 2014 HDR Architecture, 2016 2014 HDR, Inc., all all rights reserved. Helicopters
More informationHyperspectral Remote Sensing
Hyperspectral Remote Sensing Multi-spectral: Several comparatively wide spectral bands Hyperspectral: Many (could be hundreds) very narrow spectral bands GEOG 4110/5100 30 AVIRIS: Airborne Visible/Infrared
More informationAtmospheric correction of hyperspectral ocean color sensors: application to HICO
Atmospheric correction of hyperspectral ocean color sensors: application to HICO Amir Ibrahim NASA GSFC / USRA Bryan Franz, Zia Ahmad, Kirk knobelspiesse (NASA GSFC), and Bo-Cai Gao (NRL) Remote sensing
More informationClassify Multi-Spectral Data Classify Geologic Terrains on Venus Apply Multi-Variate Statistics
Classify Multi-Spectral Data Classify Geologic Terrains on Venus Apply Multi-Variate Statistics Operations What Do I Need? Classify Merge Combine Cross Scan Score Warp Respace Cover Subscene Rotate Translators
More informationTOA RADIANCE SIMULATOR FOR THE NEW HYPERSPECTRAL MISSIONS: STORE (SIMULATOR OF TOA RADIANCE)
TOA RADIANCE SIMULATOR FOR THE NEW HYPERSPECTRAL MISSIONS: STORE (SIMULATOR OF TOA RADIANCE) Malvina Silvestri Istituto Nazionale di Geofisica e Vulcanologia In the frame of the Italian Space Agency (ASI)
More informationABSTRACT 1. INTRODUCTION
Correlation between lidar-derived intensity and passive optical imagery Jeremy P. Metcalf, Angela M. Kim, Fred A. Kruse, and Richard C. Olsen Physics Department and Remote Sensing Center, Naval Postgraduate
More informationAppendix III: Ten (10) Specialty Areas - Remote Sensing/Imagry Science Curriculum Mapping to Knowledge Units-RS/Imagry Science Specialty Area
III. Remote Sensing/Imagery Science Specialty Area 1. Knowledge Unit title: Remote Sensing Collection Platforms A. Knowledge Unit description and objective: Understand and be familiar with remote sensing
More informationShallow-water Remote Sensing: Lecture 1: Overview
Shallow-water Remote Sensing: Lecture 1: Overview Curtis Mobley Vice President for Science and Senior Scientist Sequoia Scientific, Inc. Bellevue, WA 98005 curtis.mobley@sequoiasci.com IOCCG Course Villefranche-sur-Mer,
More informationNATIONAL TECHNICAL UNIVERSITY OF ATHENS PERMANENT COMMITTEE FOR BASIC RESEARCH NTUA BASIC RESEARCH SUPPORT PROGRAMME THALES 2001
NATIONAL TECHNICAL UNIVERSITY OF ATHENS PERMANENT COMMITTEE FOR BASIC RESEARCH NTUA BASIC RESEARCH SUPPORT PROGRAMME THALES 001 «USE OF LIDAR TECHNOLOGY FOR ATMOSPHERIC CORRECTION OF DIGITAL REMOTE SENSING
More informationMotivation. Aerosol Retrieval Over Urban Areas with High Resolution Hyperspectral Sensors
Motivation Aerosol etrieval Over Urban Areas with High esolution Hyperspectral Sensors Barry Gross (CCNY) Oluwatosin Ogunwuyi (Ugrad CCNY) Brian Cairns (NASA-GISS) Istvan Laszlo (NOAA-NESDIS) Aerosols
More informationCrop Types Classification By Hyperion Data And Unmixing Algorithm
Crop Types Classification By Hyperion Data And Unmixing Algorithm H. FAHIMNEJAD 1, S.R. SOOFBAF 2, A. ALIMOHAMMADI 3, M. J. VALADAN ZOEJ 4 Geodesy and Geomatic Faculty, K.N.Toosi University of Technology,
More information2017 Summer Course on Optical Oceanography and Ocean Color Remote Sensing. Introduction to Remote Sensing
2017 Summer Course on Optical Oceanography and Ocean Color Remote Sensing Introduction to Remote Sensing Curtis Mobley Delivered at the Darling Marine Center, University of Maine July 2017 Copyright 2017
More informationDetermining satellite rotation rates for unresolved targets using temporal variations in spectral signatures
Determining satellite rotation rates for unresolved targets using temporal variations in spectral signatures Joseph Coughlin Stinger Ghaffarian Technologies Colorado Springs, CO joe.coughlin@sgt-inc.com
More informationRemote Sensing Introduction to the course
Remote Sensing Introduction to the course Remote Sensing (Prof. L. Biagi) Exploitation of remotely assessed data for information retrieval Data: Digital images of the Earth, obtained by sensors recording
More informationMULTISPECTRAL MAPPING
VOLUME 5 ISSUE 1 JAN/FEB 2015 MULTISPECTRAL MAPPING 8 DRONE TECH REVOLUTION Forthcoming order of magnitude reduction in the price of close-range aerial scanning 16 HANDHELD SCANNING TECH 32 MAX MATERIAL,
More informationRetrieval of crop characteristics from high resolution airborne scanner data
Retrieval of crop characteristics from high resolution airborne scanner data K. Richter 1, F. Vuolo 2, G. D Urso 1, G. Fernandez 3 1 DIIAT, Facoltà di Agraria, Università degli studi di Napoli Federico
More informationOptical/Thermal: Principles & Applications
Optical/Thermal: Principles & Applications Jose F. Moreno University of Valencia, Spain Jose.Moreno@uv.es Lecture D1T2 1 July 2013 23/07/2013 1 OPTICAL PRINCIPLES AND APPLICATIONS Information content of
More informationISPRS Hannover Workshop 2013, May 2013, Hannover, Germany
New light-weight stereosopic spectrometric airborne imaging technology for highresolution environmental remote sensing Case studies in water quality mapping E. Honkavaara, T. Hakala, K. Nurminen, L. Markelin,
More informationUV Remote Sensing of Volcanic Ash
UV Remote Sensing of Volcanic Ash Kai Yang University of Maryland College Park WMO Inter-comparison of Satellite-based Volcanic Ash Retrieval Algorithms Workshop June 26 July 2, 2015, Madison, Wisconsin
More informationOnshore remote sensing applications: an overview
Onshore remote sensing applications: an overview Dr. Richard Teeuw and Dr. Malcolm Whitworth School of Earth and Environmental Sciences, University of Portsmouth, UK. Overview Presentation on the applications
More informationCRISM (Compact Reconnaissance Imaging Spectrometer for Mars) on MRO. Calibration Upgrade, version 2 to 3
CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) on MRO Calibration Upgrade, version 2 to 3 Dave Humm Applied Physics Laboratory, Laurel, MD 20723 18 March 2012 1 Calibration Overview 2 Simplified
More information2010 LiDAR Project. GIS User Group Meeting June 30, 2010
2010 LiDAR Project GIS User Group Meeting June 30, 2010 LiDAR = Light Detection and Ranging Technology that utilizes lasers to determine the distance to an object or surface Measures the time delay between
More informationATMOSPHERIC CORRECTION ITERATIVE METHOD FOR HIGH RESOLUTION AEROSPACE IMAGING SPECTROMETERS
ATMOSPHERIC CORRECTION ITERATIVE METHOD FOR HIGH RESOLUTION AEROSPACE IMAGING SPECTROMETERS Alessandro Barducci, Donatella Guzzi, Paolo Marcoionni, Ivan Pippi * CNR IFAC Via Madonna del Piano 10, 50019
More informationGeomatic & Information Technologies for Ports and Navigable Waterways. Expanding Our Global Opportunities
Geomatic & Information Technologies for Ports and Navigable Waterways Airborne Remote Sensing Susan Jackson Tetra Tech Geomatics BD Director Hydrographic Surveying Robert Feldpausch Tetra Tech Principal
More informationPotential of Sentinel-2 for retrieval of biophysical and biochemical vegetation parameters
Insert the title of your slide Potential of Sentinel-2 for retrieval of biophysical and biochemical vegetation parameters D. Scheffler, T. Kuester, K. Segl, D. Spengler and H. Kaufmann Motivation Insert
More informationMissile Simulation in Support of Research, Development, Test Evaluation and Acquisition
NDIA 2012 Missile Simulation in Support of Research, Development, Test Evaluation and Acquisition 15 May 2012 Briefed by: Stephanie Brown Reitmeier United States Army Aviation and Missile Research, Development,
More informationHyperspectral Image Acquisition and Analysis
Hyperspectral Image Acquisition and Analysis PECORA 15 Workshop 7 Airborne Remote Sensing: A Fast-track Approach to NEPA Streamlining for Transportation Jen Aitken, ITRES Research Limited CASI Hyperspectral
More informationCONTENTS. Quick Start Guide V1.0
Quick Start Guide CONTENTS 1 Introduction... 2 2 What s in the box?... 3 3 Using your buzzard multispectral sensor... 4 3.1 Overview... 4 3.2 Connecting the power / remote trigger cable... 5 3.3 Attaching
More informationENY-C2005 Geoinformation in Environmental Modeling Lecture 4b: Laser scanning
1 ENY-C2005 Geoinformation in Environmental Modeling Lecture 4b: Laser scanning Petri Rönnholm Aalto University 2 Learning objectives To recognize applications of laser scanning To understand principles
More informationInfrared Scene Simulation for Chemical Standoff Detection System Evaluation
Infrared Scene Simulation for Chemical Standoff Detection System Evaluation Peter Mantica, Chris Lietzke, Jer Zimmermann ITT Industries, Advanced Engineering and Sciences Division Fort Wayne, Indiana Fran
More informationGEOMETRY AND RADIATION QUALITY EVALUATION OF GF-1 AND GF-2 SATELLITE IMAGERY. Yong Xie
Prepared by CNSA Agenda Item: WG.3 GEOMETRY AND RADIATION QUALITY EVALUATION OF GF-1 AND GF-2 SATELLITE IMAGERY Yong Xie Institute of Remote Sensing and Digital Earth, Chinese Academy of Science GF-1 and
More informationRetrieval of Surface Reflectance and LAI Mapping with Data from ALI, Hyperion and AVIRIS
Retrieval of Surface Reflectance and LAI Mapping with Data from ALI, Hyperion and AVIRIS P. Gong 1, G. Biging 1, R. Pu 1, and M. R. Larrieu 2 1 Center for Assessment and Monitoring of Forest and Environmental
More informationLecture 7. Spectral Unmixing. Summary. Mixtures in Remote Sensing
Lecture 7 Spectral Unmixing Summary This lecture will introduce you to the concepts of linear spectral mixing. This methods is sometimes also called: Spectral Mixture Analysis (SMA: Wessman et al 1997)
More informationLight Detection and Ranging (LiDAR)
Light Detection and Ranging (LiDAR) http://code.google.com/creative/radiohead/ Types of aerial sensors passive active 1 Active sensors for mapping terrain Radar transmits microwaves in pulses determines
More informationLab on MODIS Cloud spectral properties, Cloud Mask, NDVI and Fire Detection
MODIS and AIRS Workshop 5 April 2006 Pretoria, South Africa 5/2/2006 10:54 AM LAB 2 Lab on MODIS Cloud spectral properties, Cloud Mask, NDVI and Fire Detection This Lab was prepared to provide practical
More informationCORRELATION BETWEEN NDVI AND SURFACE TEMPERATURES USING LANDSAT ETM IMAGERY FOR SAN ANTONIO AREA. Remote Sensing Project By Newfel Mazari Fall 2005
CORRELATION BETWEEN NDVI AND SURFACE TEMPERATURES USING LANDSAT ETM IMAGERY FOR SAN ANTONIO AREA Remote Sensing Project By Newfel Mazari Fall 2005 Procedure Introduction and Objectives Site Date Acquisition
More informationLand Cover Classification Techniques
Land Cover Classification Techniques supervised classification and random forests Developed by remote sensing specialists at the USFS Geospatial Technology and Applications Center (GTAC), located in Salt
More informationINTEGRATION OF TREE DATABASE DERIVED FROM SATELLITE IMAGERY AND LIDAR POINT CLOUD DATA
INTEGRATION OF TREE DATABASE DERIVED FROM SATELLITE IMAGERY AND LIDAR POINT CLOUD DATA S. C. Liew 1, X. Huang 1, E. S. Lin 2, C. Shi 1, A. T. K. Yee 2, A. Tandon 2 1 Centre for Remote Imaging, Sensing
More informationA SENSOR FUSION APPROACH TO COASTAL MAPPING
A SENSOR FUSION APPROACH TO COASTAL MAPPING Maryellen Sault, NOAA, National Ocean Service, National Geodetic Survey Christopher Parrish, NOAA, National Ocean Service, National Geodetic Survey Stephen White,
More informationTHE EFFECT OF TOPOGRAPHIC FACTOR IN ATMOSPHERIC CORRECTION FOR HYPERSPECTRAL DATA
THE EFFECT OF TOPOGRAPHIC FACTOR IN ATMOSPHERIC CORRECTION FOR HYPERSPECTRAL DATA Tzu-Min Hong 1, Kun-Jen Wu 2, Chi-Kuei Wang 3* 1 Graduate student, Department of Geomatics, National Cheng-Kung University
More informationA Survey of Modelling and Rendering of the Earth s Atmosphere
Spring Conference on Computer Graphics 00 A Survey of Modelling and Rendering of the Earth s Atmosphere Jaroslav Sloup Department of Computer Science and Engineering Czech Technical University in Prague
More informationGEOG 4110/5100 Advanced Remote Sensing Lecture 2
GEOG 4110/5100 Advanced Remote Sensing Lecture 2 Data Quality Radiometric Distortion Radiometric Error Correction Relevant reading: Richards, sections 2.1 2.8; 2.10.1 2.10.3 Data Quality/Resolution Spatial
More informationAISASYSTEMS PRODUCE MORE WITH LESS
AISASYSTEMS PRODUCE MORE WITH LESS AISASYSTEMS SPECIM s AISA systems are state-of-the-art airborne hyperspectral imaging solutions covering the VNIR, NIR, SWIR and LWIR spectral ranges. The sensors unbeatable
More informationDefining Remote Sensing
Defining Remote Sensing Remote Sensing is a technology for sampling electromagnetic radiation to acquire and interpret non-immediate geospatial data from which to extract information about features, objects,
More informationAardobservatie en Data-analyse Image processing
Aardobservatie en Data-analyse Image processing 1 Image processing: Processing of digital images aiming at: - image correction (geometry, dropped lines, etc) - image calibration: DN into radiance or into
More informationTHE USE OF AIRBORNE HYPERSPECTRAL REFLECTANCE DATA TO CHARACTERIZE FOREST SPECIES DISTRIBUTION PATTERNS
THE USE OF AIRBORNE HYPERSPECTRAL REFLECTANCE DATA TO CHARACTERIZE FOREST SPECIES DISTRIBUTION PATTERNS Weihs, P., Huber K. Institute of Meteorology, Department of Water, Atmosphere and Environment, BOKU
More informationHYPERSPECTRAL REMOTE SENSING
HYPERSPECTRAL REMOTE SENSING By Samuel Rosario Overview The Electromagnetic Spectrum Radiation Types MSI vs HIS Sensors Applications Image Analysis Software Feature Extraction Information Extraction 1
More informationOutlier and Target Detection in Aerial Hyperspectral Imagery: A Comparison of Traditional and Percentage Occupancy Hit or Miss Transform Techniques
Outlier and Target Detection in Aerial Hyperspectral Imagery: A Comparison of Traditional and Percentage Occupancy Hit or Miss Transform Techniques Andrew Young a, Stephen Marshall a, and Alison Gray b
More informationOakville, Ontario. Hyperspectral Imagery Analysis for EAB Management. Ian Hanou AMEC Earth & Environmental
Oakville, Ontario Hyperspectral Imagery Analysis for EAB Management Ian Hanou Ian.hanou@amec.com (303) 503-4846 Agenda - Project Overview - Technology Overview - Field Data Collection and Imagery - Ash
More informationLocating the Shadow Regions in LiDAR Data: Results on the SHARE 2012 Dataset
Locating the Shadow Regions in LiDAR Data: Results on the SHARE 22 Dataset Mustafa BOYACI, Seniha Esen YUKSEL* Hacettepe University, Department of Electrical and Electronics Engineering Beytepe, Ankara,
More informationENVI. Get the Information You Need from Imagery.
Visual Information Solutions ENVI. Get the Information You Need from Imagery. ENVI is the premier software solution to quickly, easily, and accurately extract information from geospatial imagery. Easy
More informationThe Gain setting for Landsat 7 (High or Low Gain) depends on: Sensor Calibration - Application. the surface cover types of the earth and the sun angle
Sensor Calibration - Application Station Identifier ASN Scene Center atitude 34.840 (34 3'0.64"N) Day Night DAY Scene Center ongitude 33.03270 (33 0'7.72"E) WRS Path WRS Row 76 036 Corner Upper eft atitude
More informationOptical Theory Basics - 2 Atmospheric corrections and parameter retrieval
Optical Theory Basics - 2 Atmospheric corrections and parameter retrieval Jose Moreno 3 September 2007, Lecture D1Lb2 OPTICAL THEORY-FUNDAMENTALS (2) Radiation laws: definitions and nomenclature Sources
More informationAn Introduction to Lidar & Forestry May 2013
An Introduction to Lidar & Forestry May 2013 Introduction to Lidar & Forestry Lidar technology Derivatives from point clouds Applied to forestry Publish & Share Futures Lidar Light Detection And Ranging
More informationENVI Tutorial: Basic Hyperspectral Analysis
ENVI Tutorial: Basic Hyperspectral Analysis Table of Contents OVERVIEW OF THIS TUTORIAL...2 DEFINE ROIS...3 Load AVIRIS Data...3 Create and Restore ROIs...3 Extract Mean Spectra from ROIs...4 DISCRIMINATE
More informationRevision History. Applicable Documents
Revision History Version Date Revision History Remarks 1.0 2011.11-1.1 2013.1 Update of the processing algorithm of CAI Level 3 NDVI, which yields the NDVI product Ver. 01.00. The major updates of this
More informationCHRIS Proba Workshop 2005 II
CHRIS Proba Workshop 25 Analyses of hyperspectral and directional data for agricultural monitoring using the canopy reflectance model SLC Progress in the Upper Rhine Valley and Baasdorf test-sites Dr.
More informationUnsupervised and Self-taught Learning for Remote Sensing Image Analysis
Unsupervised and Self-taught Learning for Remote Sensing Image Analysis Ribana Roscher Institute of Geodesy and Geoinformation, Remote Sensing Group, University of Bonn 1 The Changing Earth https://earthengine.google.com/timelapse/
More informationInteractive comment on Quantification and mitigation of the impact of scene inhomogeneity on Sentinel-4 UVN UV-VIS retrievals by S. Noël et al.
Atmos. Meas. Tech. Discuss., www.atmos-meas-tech-discuss.net/5/c741/2012/ Author(s) 2012. This work is distributed under the Creative Commons Attribute 3.0 License. Atmospheric Measurement Techniques Discussions
More informationInteractive comment on Quantification and mitigation of the impact of scene inhomogeneity on Sentinel-4 UVN UV-VIS retrievals by S. Noël et al.
Atmos. Meas. Tech. Discuss., 5, C741 C750, 2012 www.atmos-meas-tech-discuss.net/5/c741/2012/ Author(s) 2012. This work is distributed under the Creative Commons Attribute 3.0 License. Atmospheric Measurement
More informationIntroduction to Remote Sensing
Introduction to Remote Sensing Spatial, spectral, temporal resolutions Image display alternatives Vegetation Indices Image classifications Image change detections Accuracy assessment Satellites & Air-Photos
More informationMODULE 3. FACTORS AFFECTING 3D LASER SCANNING
MODULE 3. FACTORS AFFECTING 3D LASER SCANNING Learning Outcomes: This module discusses factors affecting 3D laser scanner performance. Students should be able to explain the impact of various factors on
More informationOverview of the EnMAP Imaging Spectroscopy Mission
Overview of the EnMAP Imaging Spectroscopy Mission L. Guanter, H. Kaufmann, K. Segl, S. Foerster, T. Storch, A. Mueller, U. Heiden, M. Bachmann, G. Rossner, C. Chlebek, S. Fischer, B. Sang, the EnMAP Science
More informationTOTAL SUSPENDED MATTER MAPS FROM CHRIS IMAGERY OF A SMALL INLAND WATER BODY IN OOSTENDE (BELGIUM)
TOTAL SUSPENDED MATTER MAPS FROM IMAGERY OF A SMALL INLAND WATER BODY IN OOSTENDE (BELGIUM) Barbara Van Mol (1) and Kevin Ruddick (1) (1) Management Unit of the North Sea Mathematical Models (MUMM), Royal
More informationCalculation steps 1) Locate the exercise data in your PC C:\...\Data
Calculation steps 1) Locate the exercise data in your PC (freely available from the U.S. Geological Survey: http://earthexplorer.usgs.gov/). C:\...\Data The data consists of two folders, one for Athens
More informationContinued Development of the Look-up-table (LUT) Methodology For Interpretation of Remotely Sensed Ocean Color Data
Continued Development of the Look-up-table (LUT) Methodology For Interpretation of Remotely Sensed Ocean Color Data Curtis D. Mobley Sequoia Scientific, Inc. 2700 Richards Road, Suite 107 Bellevue, WA
More informationEXTRACTING SURFACE FEATURES OF THE NUECES RIVER DELTA USING LIDAR POINTS INTRODUCTION
EXTRACTING SURFACE FEATURES OF THE NUECES RIVER DELTA USING LIDAR POINTS Lihong Su, Post-Doctoral Research Associate James Gibeaut, Associate Research Professor Harte Research Institute for Gulf of Mexico
More informationENVI Classic Tutorial: Basic Hyperspectral Analysis
ENVI Classic Tutorial: Basic Hyperspectral Analysis Basic Hyperspectral Analysis 2 Files Used in this Tutorial 2 Define ROIs 3 Load AVIRIS Data 3 Create and Restore ROIs 3 Extract Mean Spectra from ROIs
More informationGODDARD SPACE FLIGHT CENTER. Future of cal/val. K. Thome NASA/GSFC
GODDARD SPACE FLIGHT CENTER Future of cal/val K. Thome NASA/GSFC Key issues for cal/val Importance of cal/val continues to increase as models improve and budget pressures go up Better cal/val approaches
More informationAirborne Hyperspectral Imaging Using the CASI1500
Airborne Hyperspectral Imaging Using the CASI1500 AGRISAR/EAGLE 2006, ITRES Research CASI 1500 overview A class leading VNIR sensor with extremely sharp optics. 380 to 1050nm range 288 spectral bands ~1500
More informationDiffraction gratings. e.g., CDs and DVDs
Diffraction gratings e.g., CDs and DVDs Diffraction gratings Constructive interference where: sinθ = m*λ / d (If d > λ) Single-slit diffraction 1.22 * λ / d Grating, plus order-sorting filters on detector
More informationQuality assessment of RS data. Remote Sensing (GRS-20306)
Quality assessment of RS data Remote Sensing (GRS-20306) Quality assessment General definition for quality assessment (Wikipedia) includes evaluation, grading and measurement process to assess design,
More informationAirborne LiDAR Data Acquisition for Forestry Applications. Mischa Hey WSI (Corvallis, OR)
Airborne LiDAR Data Acquisition for Forestry Applications Mischa Hey WSI (Corvallis, OR) WSI Services Corvallis, OR Airborne Mapping: Light Detection and Ranging (LiDAR) Thermal Infrared Imagery 4-Band
More informationFloX integrated data flow: from tower to database
FloX integrated data flow: from tower to database Andreas Hueni, Simon Trim 5/14/2018 FloX integrated data flow: from tower to database, Hueni et al. Page 1 Overview FloX/RoX Spectral database Integrated
More informationUAV-based Remote Sensing Payload Comprehensive Validation System
36th CEOS Working Group on Calibration and Validation Plenary May 13-17, 2013 at Shanghai, China UAV-based Remote Sensing Payload Comprehensive Validation System Chuan-rong LI Project PI www.aoe.cas.cn
More informationFlood detection using radar data Basic principles
Flood detection using radar data Basic principles André Twele, Sandro Martinis and Jan-Peter Mund German Remote Sensing Data Center (DFD) 1 Overview Introduction Basic principles of flood detection using
More informationTerrestrial GPS setup Fundamentals of Airborne LiDAR Systems, Collection and Calibration. JAMIE YOUNG Senior Manager LiDAR Solutions
Terrestrial GPS setup Fundamentals of Airborne LiDAR Systems, Collection and Calibration JAMIE YOUNG Senior Manager LiDAR Solutions Topics Terrestrial GPS reference Planning and Collection Considerations
More informationLIDAR MAPPING FACT SHEET
1. LIDAR THEORY What is lidar? Lidar is an acronym for light detection and ranging. In the mapping industry, this term is used to describe an airborne laser profiling system that produces location and
More informationENVI Classic Tutorial: Multispectral Analysis of MASTER HDF Data 2
ENVI Classic Tutorial: Multispectral Analysis of MASTER HDF Data Multispectral Analysis of MASTER HDF Data 2 Files Used in This Tutorial 2 Background 2 Shortwave Infrared (SWIR) Analysis 3 Opening the
More informationA Method Suitable for Vicarious Calibration of a UAV Hyperspectral Remote Sensor
A Method Suitable for Vicarious Calibration of a UAV Hyperspectral Remote Sensor Hao Zhang 1, Haiwei Li 1, Benyong Yang 2, Zhengchao Chen 1 1. Institute of Remote Sensing and Digital Earth (RADI), Chinese
More informationA MAXIMUM NOISE FRACTION TRANSFORM BASED ON A SENSOR NOISE MODEL FOR HYPERSPECTRAL DATA. Naoto Yokoya 1 and Akira Iwasaki 2
A MAXIMUM NOISE FRACTION TRANSFORM BASED ON A SENSOR NOISE MODEL FOR HYPERSPECTRAL DATA Naoto Yokoya 1 and Akira Iwasaki 1 Graduate Student, Department of Aeronautics and Astronautics, The University of
More informationProf. Vidya Manian Dept. of Electrical l and Comptuer Engineering. INEL6007(Spring 2010) ECE, UPRM
Inel 6007 Introduction to Remote Sensing Chapter 5 Spectral Transforms Prof. Vidya Manian Dept. of Electrical l and Comptuer Engineering Chapter 5-1 MSI Representation Image Space: Spatial information
More informationRemote Sensing in an
Chapter 2: Adding Data to a Map Document Remote Sensing in an ArcMap Environment Remote Sensing Analysis in an ArcMap Environment Tammy E. Parece Image source: landsat.usgs.gov Tammy Parece James Campbell
More informationRemote Sensing of Snow
Remote Sensing of Snow Remote Sensing Basics A definition: The inference of an area s or object s physical characteristics by distant detection of the range of electromagnetic radiation it reflects and/or
More information9/14/2011. Contents. Lecture 3: Spatial Data Acquisition in GIS. Dr. Bo Wu Learning Outcomes. Data Input Stream in GIS
Contents Lecture 3: Spatial Data Acquisition in GIS Dr. Bo Wu lsbowu@polyu.edu.hk 1. Learning outcomes. Data acquisition: Manual digitization 3. Data acquisition: Field survey 4. Data acquisition: Remote
More informationSPACEFLIGHT HYPERION DATA RADIATION CALIBRATION PRELIMINARY STUDY
SPACEFLIGHT HYPERION DATA RADIATION CALIBRATION PRELIMINARY STUDY Shufang Tian a, Jianping Chen a, Ming Jiang a a CUGB, School of Geosciences and Resources,10083 Haidian District, Beijing, China-(sftian,3s,jming)@cugb.edu.cn
More informationMAPPS 2013 Winter Conference 2013 Cornerstone Mapping, Inc. 1
MAPPS 2013 Winter Conference 2013 Cornerstone Mapping, Inc. 1 What is Thermal Imaging? Infrared radiation is perceived as heat Heat is a qualitative measure of temperature Heat is the transfer of energy
More informationAutomated large area tree species mapping and disease detection using airborne hyperspectral remote sensing
Automated large area tree species mapping and disease detection using airborne hyperspectral remote sensing William Oxford Neil Fuller, James Caudery, Steve Case, Michael Gajdus, Martin Black Outline About
More informationAnalisi di immagini iperspettrali satellitari multitemporali: metodi ed applicazioni
Analisi di immagini iperspettrali satellitari multitemporali: metodi ed applicazioni E-mail: bovolo@fbk.eu Web page: http://rsde.fbk.eu Outline 1 Multitemporal image analysis 2 Multitemporal images pre-processing
More informationSpectral Extinction Coefficient measurements of inland waters
Spectral Extinction Coefficient measurements of inland waters M. Potes, M. J. Costa, R. Salgado and P. Le Moigne Évora Geophysics Centre, PORTUGAL CNRM/GMME/MOSAYC Météo-France, FRANCE Third Workshop on
More informationBetter detection and discrimination of seagrasses using fused bathymetric lidar and hyperspectral data
Better detection and discrimination of seagrasses using fused bathymetric lidar and hyperspectral data Bruce Sabol and Molly Reif US Army Engineer Research and Development Center, Environmental Laboratory
More informationThe 2014 IEEE GRSS Data Fusion Contest
The 2014 IEEE GRSS Data Fusion Contest Description of the datasets Presented to Image Analysis and Data Fusion Technical Committee IEEE Geoscience and Remote Sensing Society (GRSS) February 17 th, 2014
More informationHyperspectral Remote Sensing in Acquisition of Geospatial Information for the Modern Warfare. Dr M R Bhutiyani,
Hyperspectral Remote Sensing in Acquisition of Geospatial Information for the Modern Warfare Dr M R Bhutiyani, Ex-Director, DTRL, New Delhi Chairman, ISRS, Delhi Chapter Air photo-interpretation Multi-spectral
More information5: COMPENSATING FOR VARIABLE WATER DEPTH TO IMPROVE MAPPING OF UNDERWATER HABITATS: WHY IT IS NECESSARY. Aim of Lesson. Objectives
Lesson 5: Compensating for variable water depth 5: COMPENSATING FOR VARIABLE WATER DEPTH TO IMPROVE MAPPING OF UNDERWATER HABITATS: WHY IT IS NECESSARY Aim of Lesson To learn how to carry out "depth-invariant"
More informationOperational use of the Orfeo Tool Box for the Venµs Mission
Operational use of the Orfeo Tool Box for the Venµs Mission Thomas Feuvrier http://uk.c-s.fr/ Free and Open Source Software for Geospatial Conference, FOSS4G 2010, Barcelona Outline Introduction of the
More informationENMAP RADIOMETRIC INFLIGHT CALIBRATION
ENMAP RADIOMETRIC INFLIGHT CALIBRATION Harald Krawczyk 1, Birgit Gerasch 1, Thomas Walzel 1, Tobias Storch 1, Rupert Müller 1, Bernhard Sang 2, Christian Chlebek 3 1 Earth Observation Center (EOC), German
More informationSentinel-1 Toolbox. TOPS Interferometry Tutorial Issued May 2014
Sentinel-1 Toolbox TOPS Interferometry Tutorial Issued May 2014 Copyright 2015 Array Systems Computing Inc. http://www.array.ca/ https://sentinel.esa.int/web/sentinel/toolboxes Interferometry Tutorial
More information