Remote Sensing Exam 2 Study Guide
|
|
- Dulcie Quinn
- 6 years ago
- Views:
Transcription
1 Remote Sensing Exam 2 Study Guide Resolution Analog to digital Instantaneous field of view (IFOV) f ( cone angle of optical system ) Everything in that area contributes to spectral response mixels Sampling rate Determines horizontal resolution # of sampling levels determines bits Instantaneous field of view (IFOV) f ( cone angle of optical system ) Everything in that area contributes to spectral response mixels Dwell time the time a sensor spends looking at any area Analog-Digital conversion process Photons strike detector, electrons flow proportional to the # photons # photons related to reflectance characteristics, λ (recall that shorter wavelengths carry more energy) Area viewed (more photons come from a larger area (at any λ)) Spectral region width (wider region = more photons) Sampling rate Determines horizontal resolution # of sampling levels determines bit Spatial resolution Spectral resolution Radiometric resolution There are tradeoffs If you increase the spatial resolution (i.e. smaller area of coverage), detector is receiving energy from a smaller area (less total energy received at detector at some λ) So, the spectral range needs to be increased to receive enough energy (or design a better detector) If you increase the spectral resolution (i.e. more bands each representing a smaller range of the EMS) detectors are receiving energy in a narrower range of the spectrum (less total energy received at the detector at some λ) So, the DWELL time needs to be increased to compensate, resulting in lower spatial resolution (or design a better detector) Coverage area (altitude and field of view) Off-nadir capabilities (point sensor to side or front/aft)
2 Pushbroom System Advantages Fewer moving parts Less energy drain Less weight Longer dwell time Better geometric fidelity Disadvantages More sensors to calibrate Limited spectral range Orbital characteristics of satellites Altitude Period Inclination Equatorial crossing Sun synchronous Combination of orbital period and inclination that cause the satellite to cross the equator at the same time (keeps pace with the sun s westward progress Geostationary Equatorial orbit of an altitude that results in an orbital period of 24 hours. 36,000km Earth resources space imaging ERTS-1 Earth Resources Technology Satellite A feasibility test First launched 7/23/1972 But design began 1967 Planned to launch six satellites Pre-launch designated as ERTS A,B,C,D,E,F Post-launch redesignated as ERTS 1,2,3,4,5,6 Open-sky principle All countries may evaluate Just before ERTS-B launch, NASA renamed the program to LANDSAT To differentiate it from a future program launch Seasat ERTS1 renamed Landsat1 retroactively
3 Landsat 1,2, 3 Similar characteristics 185km swath width Sun synchronous orbit 9 o inclination to equator Successive orbits 2760km apart 104 minutes orbital period Crosses equator at 9:42AM local time Takes advantage of normally better atm. cond early in day Also provides same illumination conditions for comparing images Large gaps between orbits on a given day (14/day) 18 day temporal resolution Overlap at equator 14%, at poles 84% Return-beam Vidicon (RBV) system RBV sensed in 3 bands equivalent to CIR film G,R,IR Bands 1,2,3 Television camera-like Used a photosensitive surface with shutter, then scanned Instant image (like camera) better geometric fidelity Spatial resolution 80m Landsat 3 changed to improve spatial resolution (30m) also single band ( um) 2 cameras (side-side) MSS G, R, NIR, NIR.5.-6,.6-.7,.7-.8,.8-1.1um Bands 4,5,6,7 Landsat 3 and B Failed 6 contiguous lines scanned IFOV = 79m A-D on-board 0-63 (6-bit) B4-6 rescaled to (7-bit) On ground Sampling rate = /s Results in 56m horizontal spacing
4 Landsat 4, day orbital return period (i.e. the temporal resolution) Altitude 705km 185km swath width Sun synchronous orbit 98.2 o inclination to equator Crosses at 9:45Am Successive orbits 2760km apart 104 minutes orbital period Also provides same illumination conditions for comparing images Orbits (14.5/day) Overlap at equator 14%, at poles 84% 8 bit resolution Except band 6 is 7 bit 30m IFOV Except band 6 is 120m on TM4,5 60m on TM7 15m Pan on TM7 16 detectors for all bands (4 for B6) totaling 100 detectors Note: Landsat 7 Added a pan Band 8 15m res0.4 to 0.9um
5 SPOT satellite French satellite (Toulouse, France) SPOT 1,2,3 26 day repeat period 20 m res. MSS 3 bands (G,R, NIR) 10 m res. Pan SPOT 4 launched March 1998 HRVIR Includes Mid-IR band (20m) Pan band replaced by red band Vegetation instrument 2250 km swath, 1 km IFOV, same bands as HRVIR but blue used instead of green For oceanographic appllications SPOT 5 - launched May m res. (pan HRGeometric) May be resampled to 2.5 m 10 m res G,R,NIR 20 m res MIR (due to CCD limitations) HRStereoscopic instrument Fore-aft instruments for DEM generation Global 10 m AVHRR Advanced Very High Resolution Radiometer
6 EOS ESE Science Objectives Provide the first state distribution of the main Earthatmosphere coupled parameters Improve our ability to detect human impacts on climate, identify fingerprints of human activity on climate, and predict climate change Provide observations that will improve forecasts of the timing and geographical extent of transient climatic anomalies Improve seasonal and inter-annual predictions Develop technologies for disaster prediction, characterization, and risk reduction from wildfires, volcanoes, floods, and droughts. Start long-term monitoring of the change in global climate and environmental change. EOS (ESE) AM-1 Mission Overview Terra and Aqua Launch date: December 1999 Terra May 2002 Aqua Orbit: 705 km altitude, polar Orbit period: 98.8 minutes Equator crossing: 10:30 AM descending Terra 1:30 PM Ascending Aqua Ground track repeat cycle: 16 days Terra Instruments: Moderate Resolution Imaging Spectroradiometer (MODIS) Advanced Spaceborne Thermal Emission Radiometer (ASTER) Multi-angle Imaging Spectroradiometer (MISR) Measurement of Pollution in the Troposphere (MOPITT) Clouds and the Earth Radiant Energy System (CERES)
7 MODIS 12-bit radiometric Resolution for all Bands 2-day global coverage Excellent band-band Registration and Radiomertric accuracy Aster 3 unique instruments (has off-nadir capabilities) Visible and Near Infrared (VNIR) 3 bands on nadir (bands 1-3) G, R, NIR 1 band 27.5º rear-looking (NIR & same as B3 on nadir) Capable of DEM generation 15m res Short Wave Infrared (SWIR) 6 bands (bands 4-9) 30m res Thermal Infrared (TIR) 5 bands (bands 10-14) 90m res DIGITAL IMAGE PROCESSING Image rectification & restoration Correct distortions and degradations to imagery Geometric distortions Radiometric distortions Sensor dependent Together, called preprocessing techniques Image Enhancement More effectively portray image data for visual interpretation Many techniques No set best way Trial and error Sometimes several enhancements to a single image are the best way
8 Image classification Quantitative techniques for automating the identification of features in a scene Multispectral data Statistical based decision rules Spectral pattern recognition LULC mapping Data merging / GIS Change detection Merging with GIS (LULC) w/zoning, topo, etc Multisensor merging Multitemporal data merging Hyperspectral image analysis Dozens to hundreds of bands Biophysical modeling Crop yield, water depth, insect infestation, pollution, etc Image compression Statistics Mean Standard Deviation Histograms Graphical distribution of values in single band Used for interpretation And for enhancements Scatterplot & Ellipses Used for interpretation of band-pairs Enhancements Process of making an image more interpretable Technique used f(dataset, desired result) Must know characteristics of dataset Have an objective Ex. Sharpening a dataset to better delineate boundaries Ex. Reducing the number of bands May be permanent or on-screen only Spectral enhancements Deals with pixels in different bands Spatial enhancements Deals with surrounding pixels in a single band Derive a new value based on values in surrounding pixels Moving window concept
9 Image enhancements Contrast enhancements Gray-level thresholding Level slicing Contrast stretching Spatial feature manipulation Filtering Edge enhancement Fourier analysis Multi-image manipulation Band ratioing Principle components IHS color space transforms Vegetation components Contrast enhancements A form of spectral enhancements Increases the contrast in certain spectral ranges of the image Likely at the expense of others Goal to make image more interpretable or features more identifiable Application in one band may not be appropriate for others (each band handled separately) Contrast Stretching Linear contrast stretch Simple Sinusoidal stretch Divides histogram into several user-defined parts Doesn t eliminate detail in some parts of image Histogram Equaliztion LUT values assigned based on frequency of occurrence Large regions of LUT reserved for common DN Small regions of LUT reserved for infrequent DN Concept based upon information yield Greatest information in most frequent pixels Special stretches Enhance whatever you re interested in Water, veg, etc Contrast enhancements Grey-level thresholding Segment image into 2 classes One above/below some user-defined value Often used to prepare a binary mask Level slicing Divide histogram into segments Each segment receives the same DN Each coded (colors) Elevations, Thermal imagery
10 Destriping Sixth line striping or Variations in calibration (sensitivity) of same sensor on different lines Produces contrast variation parallel to scan Fix Averaging Histogram Normalization MUST be done prior to geometric correction
Lecture 6: Multispectral Earth Resource Satellites. The University at Albany Fall 2018 Geography and Planning
Lecture 6: Multispectral Earth Resource Satellites The University at Albany Fall 2018 Geography and Planning Outline SPOT program and other moderate resolution systems High resolution satellite systems
More informationNON-PHOTOGRAPHIC SYSTEMS: Multispectral Scanners Medium and coarse resolution sensor comparisons: Landsat, SPOT, AVHRR and MODIS
NON-PHOTOGRAPHIC SYSTEMS: Multispectral Scanners Medium and coarse resolution sensor comparisons: Landsat, SPOT, AVHRR and MODIS CLASSIFICATION OF NONPHOTOGRAPHIC REMOTE SENSORS PASSIVE ACTIVE DIGITAL
More informationThe studies began when the Tiros satellites (1960) provided man s first synoptic view of the Earth s weather systems.
Remote sensing of the Earth from orbital altitudes was recognized in the mid-1960 s as a potential technique for obtaining information important for the effective use and conservation of natural resources.
More informationRemote Sensing Platforms
Types of Platforms Lighter-than-air Remote Sensing Platforms Free floating balloons Restricted by atmospheric conditions Used to acquire meteorological/atmospheric data Blimps/dirigibles Major role - news
More informationIntroduction of Satellite Remote Sensing
Introduction of Satellite Remote Sensing Spatial Resolution (Pixel size) Spectral Resolution (Bands) Resolutions of Remote Sensing 1. Spatial (what area and how detailed) 2. Spectral (what colors bands)
More informationRemote Sensing Platforms
Remote Sensing Platforms Remote Sensing Platforms - Introduction Allow observer and/or sensor to be above the target/phenomena of interest Two primary categories Aircraft Spacecraft Each type offers different
More informationSome Basic Concepts of Remote Sensing. Lecture 2 August 31, 2005
Some Basic Concepts of Remote Sensing Lecture 2 August 31, 2005 What is remote sensing Remote Sensing: remote sensing is science of acquiring, processing, and interpreting images and related data that
More informationThe studies began when the Tiros satellites (1960) provided man s first synoptic view of the Earth s weather systems.
Remote sensing of the Earth from orbital altitudes was recognized in the mid-1960 s as a potential technique for obtaining information important for the effective use and conservation of natural resources.
More informationSources of Geographic Information
Sources of Geographic Information Data properties: Spatial data, i.e. data that are associated with geographic locations Data format: digital (analog data for traditional paper maps) Data Inputs: sampled
More informationAn Introduction to Remote Sensing & GIS. Introduction
An Introduction to Remote Sensing & GIS Introduction Remote sensing is the measurement of object properties on Earth s surface using data acquired from aircraft and satellites. It attempts to measure something
More informationREMOTE SENSING. Topic 10 Fundamentals of Digital Multispectral Remote Sensing MULTISPECTRAL SCANNERS MULTISPECTRAL SCANNERS
REMOTE SENSING Topic 10 Fundamentals of Digital Multispectral Remote Sensing Chapter 5: Lillesand and Keifer Chapter 6: Avery and Berlin MULTISPECTRAL SCANNERS Record EMR in a number of discrete portions
More informationCHARACTERISTICS OF REMOTELY SENSED IMAGERY. Radiometric Resolution
CHARACTERISTICS OF REMOTELY SENSED IMAGERY Radiometric Resolution There are a number of ways in which images can differ. One set of important differences relate to the various resolutions that images express.
More informationAn Introduction to Geomatics. Prepared by: Dr. Maher A. El-Hallaq خاص بطلبة مساق مقدمة في علم. Associate Professor of Surveying IUG
An Introduction to Geomatics خاص بطلبة مساق مقدمة في علم الجيوماتكس Prepared by: Dr. Maher A. El-Hallaq Associate Professor of Surveying IUG 1 Airborne Imagery Dr. Maher A. El-Hallaq Associate Professor
More informationCHAPTER 7: Multispectral Remote Sensing
CHAPTER 7: Multispectral Remote Sensing REFERENCE: Remote Sensing of the Environment John R. Jensen (2007) Second Edition Pearson Prentice Hall Overview of How Digital Remotely Sensed Data are Transformed
More information9/12/2011. Training Course Remote Sensing Basic Theory & Image Processing Methods September 2011
Training Course Remote Sensing Basic Theory & Image Processing Methods 19 23 September 2011 Remote Sensing Platforms Michiel Damen (September 2011) damen@itc.nl 1 Overview Platforms & missions aerial surveys
More informationRemote Sensing of the Environment An Earth Resource Perspective John R. Jensen Second Edition
Remote Sensing of the Environment An Earth Resource Perspective John R. Jensen Second Edition Pearson Education Limited Edinburgh Gate Harlow Essex CM20 2JE England and Associated Companies throughout
More informationNORMALIZING ASTER DATA USING MODIS PRODUCTS FOR LAND COVER CLASSIFICATION
NORMALIZING ASTER DATA USING MODIS PRODUCTS FOR LAND COVER CLASSIFICATION F. Gao a, b, *, J. G. Masek a a Biospheric Sciences Branch, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA b Earth
More information9/12/2011. Training Course Remote Sensing Basic Theory & Image Processing Methods September 2011
Training Course Remote Sensing Basic Theory & Image Processing Methods 19 23 September 2011 Popular Remote Sensing Sensors & their Selection Michiel Damen (September 2011) damen@itc.nl 1 Overview Low resolution
More informationSensor resolutions from space: the tension between temporal, spectral, spatial and swath. David Bruce UniSA and ISU
Sensor resolutions from space: the tension between temporal, spectral, spatial and swath David Bruce UniSA and ISU 1 Presentation aims 1. Briefly summarize the different types of satellite image resolutions
More informationInt n r t o r d o u d c u ti t on o n to t o Remote Sensing
Introduction to Remote Sensing Definition of Remote Sensing Remote sensing refers to the activities of recording/observing/perceiving(sensing)objects or events at far away (remote) places. In remote sensing,
More informationIntroduction to Remote Sensing Part 1
Introduction to Remote Sensing Part 1 A Primer on Electromagnetic Radiation Digital, Multi-Spectral Imagery The 4 Resolutions Displaying Images Corrections and Enhancements Passive vs. Active Sensors Radar
More informationGE 113 REMOTE SENSING
GE 113 REMOTE SENSING Topic 5. Introduction to Digital Image Interpretation and Analysis Lecturer: Engr. Jojene R. Santillan jrsantillan@carsu.edu.ph Division of Geodetic Engineering College of Engineering
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 informationremote sensing? What are the remote sensing principles behind these Definition
Introduction to remote sensing: Content (1/2) Definition: photogrammetry and remote sensing (PRS) Radiation sources: solar radiation (passive optical RS) earth emission (passive microwave or thermal infrared
More informationPart I. The Importance of Image Registration for Remote Sensing
Part I The Importance of Image Registration for Remote Sensing 1 Introduction jacqueline le moigne, nathan s. netanyahu, and roger d. eastman Despite the importance of image registration to data integration
More informationRemote sensing in archaeology from optical to lidar. Krištof Oštir ModeLTER Scientific Research Centre of the Slovenian Academy of Sciences and Arts
Remote sensing in archaeology from optical to lidar Krištof Oštir ModeLTER Scientific Research Centre of the Slovenian Academy of Sciences and Arts Introduction Optical remote sensing Systems Search for
More informationSatellite Remote Sensing: Earth System Observations
Satellite Remote Sensing: Earth System Observations Land surface Water Atmosphere Climate Ecosystems 1 EOS (Earth Observing System) Develop an understanding of the total Earth system, and the effects of
More informationPreparing Remote Sensing Data for Natural Resources Mapping (image enhancement, rectifications )
Preparing Remote Sensing Data for Natural Resources Mapping (image enhancement, rectifications ) Why is this important What are the major approaches Examples of digital image enhancement Follow up exercises
More informationSatellite data processing and analysis: Examples and practical considerations
Satellite data processing and analysis: Examples and practical considerations Dániel Kristóf Ottó Petrik, Róbert Pataki, András Kolesár International LCLUC Regional Science Meeting in Central Europe Sopron,
More informationFundamentals of Remote Sensing
Climate Variability, Hydrology, and Flooding Fundamentals of Remote Sensing May 19-22, 2015 GEO-Latin American & Caribbean Water Cycle Capacity Building Workshop Cartagena, Colombia 1 Objective To provide
More informationRemote Sensing and GIS
Remote Sensing and GIS Atmosphere Reflected radiation, e.g. Visible Emitted radiation, e.g. Infrared Backscattered radiation, e.g. Radar (λ) Visible TIR Radar & Microwave 11/9/2017 Geo327G/386G, U Texas,
More informationLecture 13: Remotely Sensed Geospatial Data
Lecture 13: Remotely Sensed Geospatial Data A. The Electromagnetic Spectrum: The electromagnetic spectrum (Figure 1) indicates the different forms of radiation (or simply stated light) emitted by nature.
More informationJohn P. Stevens HS: Remote Sensing Test
Name(s): Date: Team name: John P. Stevens HS: Remote Sensing Test 1 Scoring: Part I - /18 Part II - /40 Part III - /16 Part IV - /14 Part V - /93 Total: /181 2 I. History (3 pts. each) 1. What is the name
More informationSpectral Signatures. Vegetation. 40 Soil. Water WAVELENGTH (microns)
Spectral Signatures % REFLECTANCE VISIBLE NEAR INFRARED Vegetation Soil Water.5. WAVELENGTH (microns). Spectral Reflectance of Urban Materials 5 Parking Lot 5 (5=5%) Reflectance 5 5 5 5 5 Wavelength (nm)
More informationUsing Freely Available. Remote Sensing to Create a More Powerful GIS
Using Freely Available Government Data and Remote Sensing to Create a More Powerful GIS All rights reserved. ENVI, E3De, IAS, and IDL are trademarks of Exelis, Inc. All other marks are the property of
More informationOutline. Introduction. Introduction: Film Emulsions. Sensor Systems. Types of Remote Sensing. A/Prof Linlin Ge. Photographic systems (cf(
GMAT x600 Remote Sensing / Earth Observation Types of Sensor Systems (1) Outline Image Sensor Systems (i) Line Scanning Sensor Systems (passive) (ii) Array Sensor Systems (passive) (iii) Antenna Radar
More informationOn the use of water color missions for lakes in 2021
Lakes and Climate: The Role of Remote Sensing June 01-02, 2017 On the use of water color missions for lakes in 2021 Cédric G. Fichot Department of Earth and Environment 1 Overview 1. Past and still-ongoing
More informationGovt. Engineering College Jhalawar Model Question Paper Subject- Remote Sensing & GIS
Govt. Engineering College Jhalawar Model Question Paper Subject- Remote Sensing & GIS Time: Max. Marks: Q1. What is remote Sensing? Explain the basic components of a Remote Sensing system. Q2. What is
More informationLecture Notes Prepared by Prof. J. Francis Spring Remote Sensing Instruments
Lecture Notes Prepared by Prof. J. Francis Spring 2005 Remote Sensing Instruments Material from Remote Sensing Instrumentation in Weather Satellites: Systems, Data, and Environmental Applications by Rao,
More informationOVERVIEW OF KOMPSAT-3A CALIBRATION AND VALIDATION
OVERVIEW OF KOMPSAT-3A CALIBRATION AND VALIDATION DooChun Seo 1, GiByeong Hong 1, ChungGil Jin 1, DaeSoon Park 1, SukWon Ji 1 and DongHan Lee 1 1 KARI(Korea Aerospace Space Institute), 45, Eoeun-dong,
More informationREMOTE SENSING FOR FLOOD HAZARD STUDIES.
REMOTE SENSING FOR FLOOD HAZARD STUDIES. OPTICAL SENSORS. 1 DRS. NANETTE C. KINGMA 1 Optical Remote Sensing for flood hazard studies. 2 2 Floods & use of remote sensing. Floods often leaves its imprint
More informationAtmospheric interactions; Aerial Photography; Imaging systems; Intro to Spectroscopy Week #3: September 12, 2018
GEOL 1460/2461 Ramsey Introduction/Advanced Remote Sensing Fall, 2018 Atmospheric interactions; Aerial Photography; Imaging systems; Intro to Spectroscopy Week #3: September 12, 2018 I. Quick Review from
More informationRemote Sensing. Division C. Written Exam
Remote Sensing Division C Written Exam Team Name: Team #: Team Members: _ Score: /132 A. Matching (10 points) 1. Nadir 2. Albedo 3. Diffraction 4. Refraction 5. Spatial Resolution 6. Temporal Resolution
More informationRemote Sensing 1 Principles of visible and radar remote sensing & sensors
Remote Sensing 1 Principles of visible and radar remote sensing & sensors Nick Barrand School of Geography, Earth & Environmental Sciences University of Birmingham, UK Field glaciologist collecting data
More informationAPCAS/10/21 April 2010 ASIA AND PACIFIC COMMISSION ON AGRICULTURAL STATISTICS TWENTY-THIRD SESSION. Siem Reap, Cambodia, April 2010
APCAS/10/21 April 2010 Agenda Item 8 ASIA AND PACIFIC COMMISSION ON AGRICULTURAL STATISTICS TWENTY-THIRD SESSION Siem Reap, Cambodia, 26-30 April 2010 The Use of Remote Sensing for Area Estimation by Robert
More informationRemote sensing image correction
Remote sensing image correction Introductory readings remote sensing http://www.microimages.com/documentation/tutorials/introrse.pdf 1 Preprocessing Digital Image Processing of satellite images can be
More informationChapter 5. Preprocessing in remote sensing
Chapter 5. Preprocessing in remote sensing 5.1 Introduction Remote sensing images from spaceborne sensors with resolutions from 1 km to < 1 m become more and more available at reasonable costs. For some
More informationGIS Data Collection. Remote Sensing
GIS Data Collection Remote Sensing Data Collection Remote sensing Introduction Concepts Spectral signatures Resolutions: spectral, spatial, temporal Digital image processing (classification) Other systems
More informationREMOTE SENSING INTERPRETATION
REMOTE SENSING INTERPRETATION Jan Clevers Centre for Geo-Information - WU Remote Sensing --> RS Sensor at a distance EARTH OBSERVATION EM energy Earth RS is a tool; one of the sources of information! 1
More information3/31/03. ESM 266: Introduction 1. Observations from space. Remote Sensing: The Major Source for Large-Scale Environmental Information
Remote Sensing: The Major Source for Large-Scale Environmental Information Jeff Dozier Observations from space Sun-synchronous polar orbits Global coverage, fixed crossing, repeat sampling Typical altitude
More informationHigh Resolution Sensor Test Comparison with SPOT, KFA1000, KVR1000, IRS-1C and DPA in Lower Saxony
High Resolution Sensor Test Comparison with SPOT, KFA1000, KVR1000, IRS-1C and DPA in Lower Saxony K. Jacobsen, G. Konecny, H. Wegmann Abstract The Institute for Photogrammetry and Engineering Surveys
More informationRemote Sensing for Rangeland Applications
Remote Sensing for Rangeland Applications Jay Angerer Ecological Training June 16, 2012 Remote Sensing The term "remote sensing," first used in the United States in the 1950s by Ms. Evelyn Pruitt of the
More informationIntroduction to Remote Sensing Fundamentals of Satellite Remote Sensing. Mads Olander Rasmussen
Introduction to Remote Sensing Fundamentals of Satellite Remote Sensing Mads Olander Rasmussen (mora@dhi-gras.com) 01. Introduction to Remote Sensing DHI What is remote sensing? the art, science, and technology
More informationCamera Case Study: HiSCI à now CaSSIS (Colour and Stereo Surface Imaging System)
Camera Case Study: HiSCI à now CaSSIS (Colour and Stereo Surface Imaging System) A camera for ESA s 2016 ExoMars Trace Gas Orbiter: h
More informationCourse overview; Remote sensing introduction; Basics of image processing & Color theory
GEOL 1460 /2461 Ramsey Introduction to Remote Sensing Fall, 2018 Course overview; Remote sensing introduction; Basics of image processing & Color theory Week #1: 29 August 2018 I. Syllabus Review we will
More informationAral Sea profile Selection of area 24 February April May 1998
250 km Aral Sea profile 1960 1960 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 2010? Selection of area Area of interest Kzyl-Orda Dried seabed 185 km Syrdarya river Aral Sea Salt
More information366 Glossary. Popular method for scale drawings in a computer similar to GIS but without the necessity for spatial referencing CEP
366 Glossary GISci Glossary ASCII ASTER American Standard Code for Information Interchange Advanced Spaceborne Thermal Emission and Reflection Radiometer Computer Aided Design Circular Error Probability
More informationFinal Examination Introduction to Remote Sensing. Time: 1.5 hrs Max. Marks: 50. Section-I (50 x 1 = 50 Marks)
Final Examination Introduction to Remote Sensing Time: 1.5 hrs Max. Marks: 50 Note: Attempt all questions. Section-I (50 x 1 = 50 Marks) 1... is the technology of acquiring information about the Earth's
More informationIKONOS High Resolution Multispectral Scanner Sensor Characteristics
High Spatial Resolution and Hyperspectral Scanners IKONOS High Resolution Multispectral Scanner Sensor Characteristics Launch Date View Angle Orbit 24 September 1999 Vandenberg Air Force Base, California,
More informationIntroduction to Satellite Remote Sensing
Introduction to Satellite Remote Sensing Remote sensing of the Earth from orbital altitudes was recognized in the mid-1960 s as a potential technique for obtaining information important for the effective
More informationIntroduction to Remote Sensing. Electromagnetic Energy. Data From Wave Phenomena. Electromagnetic Radiation (EMR) Electromagnetic Energy
A Basic Introduction to Remote Sensing (RS) ~~~~~~~~~~ Rev. Ronald J. Wasowski, C.S.C. Associate Professor of Environmental Science University of Portland Portland, Oregon 1 September 2015 Introduction
More information746A27 Remote Sensing and GIS. Multi spectral, thermal and hyper spectral sensing and usage
746A27 Remote Sensing and GIS Lecture 3 Multi spectral, thermal and hyper spectral sensing and usage Chandan Roy Guest Lecturer Department of Computer and Information Science Linköping University Multi
More informationAbstract Quickbird Vs Aerial photos in identifying man-made objects
Abstract Quickbird Vs Aerial s in identifying man-made objects Abdullah Mah abdullah.mah@aramco.com Remote Sensing Group, emap Division Integrated Solutions Services Department (ISSD) Saudi Aramco, Dhahran
More informationFrom Proba-V to Proba-MVA
From Proba-V to Proba-MVA Fabrizio Niro ESA Sensor Performances Products and Algorithm (SPPA) ESA UNCLASSIFIED - For Official Use Proba-V extension in the Copernicus era Proba-V was designed with the main
More information(Refer Slide Time: 1:28)
Introduction to Remote Sensing Dr. Arun K Saraf Department of Earth Sciences Indian Institute of Technology Roorkee Lecture 10 Image characteristics and different resolutions in Remote Sensing Hello everyone,
More informationRemote Sensing. The following figure is grey scale display of SPOT Panchromatic without stretching.
Remote Sensing Objectives This unit will briefly explain display of remote sensing image, geometric correction, spatial enhancement, spectral enhancement and classification of remote sensing image. At
More informationA map says to you, 'Read me carefully, follow me closely, doubt me not.' It says, 'I am the Earth in the palm of your hand. Without me, you are alone
A map says to you, 'Read me carefully, follow me closely, doubt me not.' It says, 'I am the Earth in the palm of your hand. Without me, you are alone and lost. Beryl Markham (West With the Night, 1946
More informationGE 113 REMOTE SENSING. Topic 7. Image Enhancement
GE 113 REMOTE SENSING Topic 7. Image Enhancement Lecturer: Engr. Jojene R. Santillan jrsantillan@carsu.edu.ph Division of Geodetic Engineering College of Engineering and Information Technology Caraga State
More informationImage interpretation and analysis
Image interpretation and analysis Grundlagen Fernerkundung, Geo 123.1, FS 2014 Lecture 7a Rogier de Jong Michael Schaepman Why are snow, foam, and clouds white? Why are snow, foam, and clouds white? Today
More informationEXAMPLES OF TOPOGRAPHIC MAPS PRODUCED FROM SPACE AND ACHIEVED ACCURACY CARAVAN Workshop on Mapping from Space, Phnom Penh, June 2000
EXAMPLES OF TOPOGRAPHIC MAPS PRODUCED FROM SPACE AND ACHIEVED ACCURACY CARAVAN Workshop on Mapping from Space, Phnom Penh, June 2000 Jacobsen, Karsten University of Hannover Email: karsten@ipi.uni-hannover.de
More informationJP Stevens High School: Remote Sensing
1 Name(s): ANSWER KEY Date: Team name: JP Stevens High School: Remote Sensing Scoring: Part I - /18 Part II - /40 Part III - /16 Part IV - /14 Part V - /93 Total: /181 2 I. History (3 pts each) 1. What
More informationApplication of GIS to Fast Track Planning and Monitoring of Development Agenda
Application of GIS to Fast Track Planning and Monitoring of Development Agenda Radiometric, Atmospheric & Geometric Preprocessing of Optical Remote Sensing 13 17 June 2018 Outline 1. Why pre-process remotely
More informationASTER and USGS EROS Emergency Imaging for Hurricane Disasters
ASTER and USGS EROS Emergency Imaging for Hurricane Disasters By Kenneth A. Duda and Michael Abrams Satellite images have been extremely useful in a variety of emergency response activities, including
More informationNEC s EO Sensors and Data Applications
NEC s EO Sensors and Data Applications Second Singapore Space Symposium 30 September, 2015 Nanyang Technological University, Singapore Shimpei Kondo Space Technologies Department, Space System Division,
More informationTextbook, Chapter 15 Textbook, Chapter 10 (only 10.6)
AGOG 484/584/ APLN 551 Fall 2018 Concept definition Applications Instruments and platforms Techniques to process hyperspectral data A problem of mixed pixels and spectral unmixing Reading Textbook, Chapter
More informationDESIS Applications & Processing Extracted from Teledyne & DLR Presentations to JACIE April 14, Ray Perkins, Teledyne Brown Engineering
DESIS Applications & Processing Extracted from Teledyne & DLR Presentations to JACIE April 14, 2016 Ray Perkins, Teledyne Brown Engineering 1 Presentation Agenda Imaging Spectroscopy Applications of DESIS
More informationMonitoring Natural Disasters with Small Satellites Smart Satellite Based Geospatial System for Environmental Protection
Monitoring Natural Disasters with Small Satellites Smart Satellite Based Geospatial System for Environmental Protection Krištof Oštir, Space-SI, Slovenia Contents Natural and technological disasters Current
More informationIntroduction to image processing for remote sensing: Practical examples
Università degli studi di Roma Tor Vergata Corso di Telerilevamento e Diagnostica Elettromagnetica Anno accademico 2010/2011 Introduction to image processing for remote sensing: Practical examples Dr.
More informationRemote Sensing. Measuring an object from a distance. For GIS, that means using photographic or satellite images to gather spatial data
Remote Sensing Measuring an object from a distance For GIS, that means using photographic or satellite images to gather spatial data Remote Sensing measures electromagnetic energy reflected or emitted
More informationUniversity of Texas at San Antonio EES 5053 Term Project CORRELATION BETWEEN NDVI AND SURFACE TEMPERATURES USING LANDSAT ETM + IMAGERY NEWFEL MAZARI
University of Texas at San Antonio EES 5053 Term Project CORRELATION BETWEEN NDVI AND SURFACE TEMPERATURES USING LANDSAT ETM + IMAGERY NEWFEL MAZARI Introduction and Objectives The present study is a correlation
More informationBlacksburg, VA July 24 th 30 th, 2010 Remote Sensing Page 1. A condensed overview. For our purposes
A condensed overview George McLeod Prepared by: With support from: NSF DUE-0903270 in partnership with: Geospatial Technician Education Through Virginia s Community Colleges (GTEVCC) The art and science
More informationCoral Reef Remote Sensing
Coral Reef Remote Sensing Spectral, Spatial, Temporal Scaling Phillip Dustan Sensor Spatial Resolutio n Number of Bands Useful Bands coverage cycle Operation Landsat 80m 2 2 18 1972-97 Thematic 30m 7
More informationEnvironmental Remote Sensing GEOG 2021
Environmental Remote Sensing GEOG 2021 Lecture 2 Image display and enhancement 2 Image Display and Enhancement Purpose visual enhancement to aid interpretation enhancement for improvement of information
More informationData acquisition and integration 6.
University of West Hungary, Faculty of Geoinformatics Malgorzata Verőné Wojtaszek Data acquisition and integration 6. module DAI6 Remote Sensing SZÉKESFEHÉRVÁR 2010 The right to this intellectual property
More informationINF-GEO Introduction to remote sensing
INF-GEO 4310 Introduction to remote sensing Anne Solberg (anne@ifi.uio.no) Satellites, orbits and repeat cycles Optical remote sensings Based on a tutorial adapted from Canadian Center for Remote Sensing,
More informationSatellite Imagery and Remote Sensing. DeeDee Whitaker SW Guilford High EES & Chemistry
Satellite Imagery and Remote Sensing DeeDee Whitaker SW Guilford High EES & Chemistry whitakd@gcsnc.com Outline What is remote sensing? How does remote sensing work? What role does the electromagnetic
More informationRadiometric performance of Second Generation Global Imager (SGLI) using integrating sphere
Radiometric performance of Second Generation Global Imager (SGLI) using integrating sphere Taichiro Hashiguchi, Yoshihiko Okamura, Kazuhiro Tanaka, Yukinori Nakajima Japan Aerospace Exploration Agency
More information(Presented by Jeppesen) Summary
International Civil Aviation Organization SAM/IG/6-IP/06 South American Regional Office 24/09/10 Sixth Workshop/Meeting of the SAM Implementation Group (SAM/IG/6) - Regional Project RLA/06/901 Lima, Peru,
More informationUS Commercial Imaging Satellites
US Commercial Imaging Satellites In the early 1990s, Russia began selling 2-meter resolution product from its archives of collected spy satellite imagery. Some of this product was down-sampled to provide
More informationASTER ADVANCED SPACEBORNE THERMAL EMISSION AND REFLECTION RADIOMETER
ASTER ADVANCED SPACEBORNE THERMAL EMISSION AND REFLECTION RADIOMETER Front Cover image: Simulated ASTER images of Death Valley, California. The visible image (left) shows vegetation in red, salt deposits
More informationUpdate on Landsat Program and Landsat Data Continuity Mission
Update on Landsat Program and Landsat Data Continuity Mission Dr. Jeffrey Masek LDCM Deputy Project Scientist NASA GSFC, Code 923 November 21, 2002 Draft LDCM Implementation Phase RFP Overview Page 1 Celebrate!
More informationRADIOMETRIC CALIBRATION
1 RADIOMETRIC CALIBRATION Lecture 10 Digital Image Data 2 Digital data are matrices of digital numbers (DNs) There is one layer (or matrix) for each satellite band Each DN corresponds to one pixel 3 Digital
More informationIntroduction to Remote Sensing
Introduction to Remote Sensing Daniel McInerney Urban Institute Ireland, University College Dublin, Richview Campus, Clonskeagh Drive, Dublin 14. 16th June 2009 Presentation Outline 1 2 Spaceborne Sensors
More informationRemote Sensing (Test) Topic: Climate Change Processes*
Scioly Summer Study Session 2017 Remote Sensing (Test) Topic: Climate Change Processes* By user whythelongface (merge) Name(s): Test format: This test is worth 150 points. There are four sections: 1. Remote
More informationMulti-Resolution Analysis of MODIS and ASTER Satellite Data for Water Classification
Corina Alecu, Simona Oancea National Meteorological Administration 97 Soseaua Bucuresti-Ploiesti, 013686, Sector 1, Bucharest Romania corina.alecu@meteo.inmh.ro Emily Bryant Dartmouth Flood Observatory,
More informationtypical spectral signatures of photosynthetically active and non-photosynthetically active vegetation (Beeri et al., 2007)
typical spectral signatures of photosynthetically active and non-photosynthetically active vegetation (Beeri et al., 2007) Xie, Y. et al. J Plant Ecol 2008 1:9-23; doi:10.1093/jpe/rtm005 Copyright restrictions
More informationImage transformations
Image transformations Digital Numbers may be composed of three elements: Atmospheric interference (e.g. haze) ATCOR Illumination (angle of reflection) - transforms Albedo (surface cover) Image transformations
More informationCOMPARISON OF INFORMATION CONTENTS OF HIGH RESOLUTION SPACE IMAGES
COMPARISON OF INFORMATION CONTENTS OF HIGH RESOLUTION SPACE IMAGES H. Topan*, G. Büyüksalih*, K. Jacobsen ** * Karaelmas University Zonguldak, Turkey ** University of Hannover, Germany htopan@karaelmas.edu.tr,
More informationFOR 353: Air Photo Interpretation and Photogrammetry. Lecture 2. Electromagnetic Energy/Camera and Film characteristics
FOR 353: Air Photo Interpretation and Photogrammetry Lecture 2 Electromagnetic Energy/Camera and Film characteristics Lecture Outline Electromagnetic Radiation Theory Digital vs. Analog (i.e. film ) Systems
More informationMod. 2 p. 1. Prof. Dr. Christoph Kleinn Institut für Waldinventur und Waldwachstum Arbeitsbereich Fernerkundung und Waldinventur
Histograms of gray values for TM bands 1-7 for the example image - Band 4 and 5 show more differentiation than the others (contrast=the ratio of brightest to darkest areas of a landscape). - Judging from
More information