Review for Introduction to Remote Sensing: Science Concepts and Technology

Save this PDF as:
Size: px
Start display at page:

Download "Review for Introduction to Remote Sensing: Science Concepts and Technology"

Transcription

1 Review for Introduction to Remote Sensing: Science Concepts and Technology Ann Johnson Associate Director Funded by National Science Foundation Advanced Technological Education program [DUE # Author s opinions are not necessarily shared by NSF Empowering Colleges: Expanding the Geospatial Workforce What is Remote Sensing and how is it used? Passive and Active Remote Sensing Electromagnetic Spectrum and sensor wavelength and their band numbers Resolutions Temporal, Spatial, Spectral and Radiometric Composite images: Pixels, Brightness and Digital Numbers Pixels and its Remote Sensing Signature graphic Finding and using data Landsat focused Lidar what is it and how can it be used Resources to learn more 1

2 USGS Definition Acquiring information about a natural feature or phenomenon, such as the Earth s surface, without actually being in contact with it. Sensor can be ground based, aerial or satellite. Not just a pretty picture! How it can be used! Land Use Change Climate Disasters Floods, fires, volcanoes, earthquakes Forestry Agriculture Many more! 2

3 Factors to consider when you use remote sensing data to understand or solve a geospatial problem Scale or Resolution Where is the study location? How large is the study are? What is the size of features under study? Is this a one time event or over multiple times over days, months or years? Access to needed resources: Data and its cost? Hardware and software and skills to use them Why is study important? Important for realworld use by industry or government - ROI Use sensors to detect and acquire the information about features The human eye as a senor and brain as processor! 3

4 Two Types of Remote Sensing Sensors Active Energy source is provided Lidar Light Detection and Ranging using pulsed laser beam (of varying wavelengths) SAR Synthetic Aperture Radar pulses of radio wavelengths Passive Sun as the energy source Landsat MODIS Aster Two Types of Remote Sensing Sensors Active Energy source is provided Lidar Light Detection and Ranging using pulsed laser beam (of varying wavelengths) SAR Synthetic Aperture Radar pulses of radio wavelengths Passive Sun as the energy source Landsat MODIS Aster What about our eyes Active or Passive? 4

5 Graphic From: Natural Resources Canada Fundamentals of Remote Sensing Tutorial Need: energy source, sensor(s), target, collection method, processing method and a distribution method Electromagnetic Spectrum NASA Movie Can download a NASA book on the Tour of the Electromagnetic Spectrum 5

6 One Wavelength crest crest Resolution Spectral wavelengths of spectrum collected by sensors Spatial size of area on the ground by one pixel & size of image footprint Temporal how often data (image) is acquired for a location Radiometric the sensitivity of sensor to collect very slight differences in emitted or reflected energy 6

7 Spectral Resolutions Landsat Sensors Collect data in specific Wavelengths or Bands of Electromagnetic Spectrum Landsat 7 Our Eyes Band 1: m (Blue) Band 2: m (Green) Band 3: m (Red) Band 4: m (Near infrared) Band 5: m (Mid-Infrared) Band 6: m (Thermal infrared) Band 7: m (Mid-infrared) Spectral Resolutions SAR; radar Lidar; nm (some visible and some infrared) Multispectral: nm (some visible and some infrared) Lidar Multispectral 7

8 Spatial Resolution Comparison Scale High spatial resolution: Meter to sub meter pixels Small objects can be identified Small area for each image footprint Moderate spatial resolution Generally 30 meter pixels (Landsat) Object identification generally greater than 30 meters Moderate area image footprint Low spatial resolution 1 KM or larger pixels (MODIS) Objects smaller than 1 KM not observable Very large footprint Look at Examples of Different types of Imagery and compare their footprints logon to link below: nh.org/tool.php?content_id=144 8

9 Temporal Resolution How often data is collected of the same location Only once Daily or multiple times a day Frequently every so many days Landsat missions Once every 16 days but.... Must be clear (or have a percent cloud coverage) Must be important (U.S. and outside U.S.) Landsat Image Orbits (Path and Rows) View Orbits video 9

10 Why focus on Landsat Data? Cost Access Archive Tools and other resources Atmosphere blocks some wavelengths: sensors collect wavelength data in specific regions (bands or channels) of the spectrum Lidar 10

11 Gray shading: Wavelength Regions with good transmission Lidar What Does data look like? Landsat 7 Spectral Bands and gray scale values of each band data set Landsat 7 - Band data comes in as rasters with grayscale values 0 to 255 Landsat 8 more than 4,000 scaled to 55,000 gray values 11

12 Radiometric Resolution Ability of a Sensor to discriminate very small differences in reflected or emitted energy Pixel Brightness White to Black in shades of Gray for one band Digital Number: the numeric values of its Brightness Landsat 5 and 7 are 8 bit for 256 gray levels Landsat 8 is 12 Bit for 4,096 gray levels (scaled to 55,000) A B C Creating Visualizations: Composites Brightness values (DN) from three Bands are combined and colored on a computer monitor by designating which of the 3 bands will be coded as Red, Blue or Green 12

13 Landsat 7 Natural or True Color Bands 3, 2, 1 False Color Band 5, 4, 3 Pseudo Color Bands 7, 5, 3 Selecting three different bands as Red, Green or Blue creates different images of the same location Note: Band numbers for Landsat 5 and 7 are different than for Landsat 8 13

14 Resource for Viewing Natural and False Color Composites on USGS Website xamples.php Go to this site and use the swipe to see the difference using different bands for images from four regions of the U.S. Change Matter Website See handout and investigate website for different locations and dates 14

15 Identifying and Classifying Features Visual investigate using composites Using band algebra with data from bands Normalized Difference Vegetation Index (NDVI) uses Near Infra Red and Red bands Classification using spectral data from multiple bands for one pixel creating a spectral signature Spectral Signatures From Different Surfaces in an Image 15

16 NDVI Image Analysis and Greeness Using NIR and Red Bands NDVI Leaf Land Cover Change and Greeness - NDVI 16

17 Classification Using Software Unsupervised Classification User tells Software how many classes to group the image data into and software gathers like values into classes with similar spectral values User then labels the classes into land use types and may combine classes Unsupervised Classification Natural Color Composite of San Fernando Valley, CA Data clustered by software and colored to match Land Use types (i.e. blue, water, green vegetation, etc.) 17

18 Supervised Classification User identifies pixels that are different types of feature (soil, urban, vegetation, etc) and creates a file with spectral information that can be used by software. Software uses spectral value file of the different features and classifies pixels based on the specified land cover types. So many satellites! Resources: Satellite Viewer al&satellite=14484 EarthNow! Landsat Image Viewer Real time view as data is collected showing current path of satellite tml?sessionid=fdbe7bc eda2c68d 1e603ed

19 Finding Data: Go to GloVIS and Try Path 41 and Row 36 Lidar Active Remote Sensing NOAA Lidar Tutorial: 19

20 Thank You! Much of the material for this Presentation was developed by igett-remote Sensing grant from the National Science Foundation (DUE ) More Exercises: igett.delmar.edu Concept Modules on YouTube Channel at igett Remote Sensing Education Ann Johnson 20

A remote sensing instrument collects information about an object or phenomenon within the

A remote sensing instrument collects information about an object or phenomenon within the Satellite Remote Sensing GE 4150- Natural Hazards Some slides taken from Ann Maclean: Introduction to Digital Image Processing Remote Sensing the art, science, and technology of obtaining reliable information

More information

How Landsat Images are Made

How Landsat Images are Made How Landsat Images are Made Presentation by: NASA s Landsat Education and Public Outreach team June 2006 1 More than just a pretty picture Landsat makes pretty weird looking maps, and it isn t always easy

More information

2.3 Spatial Resolution, Pixel Size, and Scale

2.3 Spatial Resolution, Pixel Size, and Scale Section 2.3 Spatial Resolution, Pixel Size, and Scale Page 39 2.3 Spatial Resolution, Pixel Size, and Scale For some remote sensing instruments, the distance between the target being imaged and the platform,

More information

SAMPLE MIDTERM QUESTIONS

SAMPLE MIDTERM QUESTIONS Geography 309 Sample MidTerm Questions Page 1 SAMPLE MIDTERM QUESTIONS Textbook Questions Chapter 1 Questions 4, 5, 6, Chapter 2 Questions 4, 7, 10 Chapter 4 Questions 8, 9 Chapter 10 Questions 1, 4, 7

More information

Hyperspectral Satellite Imaging Planning a Mission

Hyperspectral Satellite Imaging Planning a Mission Hyperspectral Satellite Imaging Planning a Mission Victor Gardner University of Maryland 2007 AIAA Region 1 Mid-Atlantic Student Conference National Institute of Aerospace, Langley, VA Outline Objective

More information

Resolutions of Remote Sensing

Resolutions of Remote Sensing Resolutions of Remote Sensing 1. Spatial (what area and how detailed) 2. Spectral (what colors bands) 3. Temporal (time of day/season/year) 4. Radiometric (color depth) Spatial Resolution describes how

More information

High Resolution Information from Seven Years of ASTER Data

High Resolution Information from Seven Years of ASTER Data High Resolution Information from Seven Years of ASTER Data Anna Colvin Michigan Technological University Department of Geological and Mining Engineering and Sciences Outline Part I ASTER mission Terra

More information

Remote sensing is the collection of data without directly measuring the object it relies on the

Remote sensing is the collection of data without directly measuring the object it relies on the Chapter 8 Remote Sensing Chapter Overview Remote sensing is the collection of data without directly measuring the object it relies on the reflectance of natural or emitted electromagnetic radiation (EMR).

More information

Landsat Monitoring our Earth s Condition for over 40 years

Landsat Monitoring our Earth s Condition for over 40 years Landsat Monitoring our Earth s Condition for over 40 years Thomas Cecere Land Remote Sensing Program USGS ISPRS:Earth Observing Data and Tools for Health Studies Arlington, VA August 28, 2013 U.S. Department

More information

Spectral Response for DigitalGlobe Earth Imaging Instruments

Spectral Response for DigitalGlobe Earth Imaging Instruments Spectral Response for DigitalGlobe Earth Imaging Instruments IKONOS The IKONOS satellite carries a high resolution panchromatic band covering most of the silicon response and four lower resolution spectral

More information

Selecting the appropriate band combination for an RGB image using Landsat imagery

Selecting the appropriate band combination for an RGB image using Landsat imagery Selecting the appropriate band combination for an RGB image using Landsat imagery Ned Horning Version: 1.0 Creation Date: 2004-01-01 Revision Date: 2004-01-01 License: This document is licensed under a

More information

Supervised Classification workflow in ENVI 4.8 using WorldView-2 imagery

Supervised Classification workflow in ENVI 4.8 using WorldView-2 imagery Supervised Classification workflow in ENVI 4.8 using WorldView-2 imagery WorldView-2 is the first commercial high-resolution satellite to provide eight spectral sensors in the visible to near-infrared

More information

Land Use/Land Cover Map of the Central Facility of ARM in the Southern Great Plains Site Using DOE s Multi-Spectral Thermal Imager Satellite Images

Land Use/Land Cover Map of the Central Facility of ARM in the Southern Great Plains Site Using DOE s Multi-Spectral Thermal Imager Satellite Images Land Use/Land Cover Map of the Central Facility of ARM in the Southern Great Plains Site Using DOE s Multi-Spectral Thermal Imager Satellite Images S. E. Báez Cazull Pre-Service Teacher Program University

More information

Finding and Downloading Landsat Data from the U.S. Geological Survey s Global Visualization Viewer Website

Finding and Downloading Landsat Data from the U.S. Geological Survey s Global Visualization Viewer Website January 1, 2013 Finding and Downloading Landsat Data from the U.S. Geological Survey s Global Visualization Viewer Website All Landsat data are available to the public at no cost from U.S. Geological Survey

More information

Digital Remote Sensing Data Processing Digital Remote Sensing Data Processing and Analysis: An Introduction and Analysis: An Introduction

Digital Remote Sensing Data Processing Digital Remote Sensing Data Processing and Analysis: An Introduction and Analysis: An Introduction Digital Remote Sensing Data Processing Digital Remote Sensing Data Processing and Analysis: An Introduction and Analysis: An Introduction Content Remote sensing data Spatial, spectral, radiometric and

More information

GIS Lesson 6 MAPS WITH RASTER IMAGES III: SATELLITE IMAGERY TEACHER INFORMATION

GIS Lesson 6 MAPS WITH RASTER IMAGES III: SATELLITE IMAGERY TEACHER INFORMATION GIS Lesson 6 MAPS WITH RASTER IMAGES III: SATELLITE IMAGERY TEACHER INFORMATION Lesson Summary: During this lesson students use GIS to load and view truecolor and enhanced satellite images of Alaska. Based

More information

Preface. Ko Ko Lwin Division of Spatial Information Science University of Tsukuba 2008

Preface. Ko Ko Lwin Division of Spatial Information Science University of Tsukuba 2008 1 Preface Remote Sensing data is one of the primary data sources in GIS analysis. The objective of this material is to provide fundamentals of Remote Sensing technology and its applications in Geographical

More information

INVESTIGA I+D+i 2013/2014

INVESTIGA I+D+i 2013/2014 INVESTIGA I+D+i 2013/2014 SPECIFIC GUIDELINES ON AEROSPACE OBSERVATION OF EARTH Text by D. Eduardo de Miguel October, 2013 Introducction Earth observation is the use of remote sensing techniques to better

More information

Active and Passive Microwave Remote Sensing

Active and Passive Microwave Remote Sensing Active and Passive Microwave Remote Sensing Passive remote sensing system record EMR that was reflected (e.g., blue, green, red, and near IR) or emitted (e.g., thermal IR) from the surface of the Earth.

More information

LEOworks - a freeware to teach Remote Sensing in Schools

LEOworks - a freeware to teach Remote Sensing in Schools LEOworks - a freeware to teach Remote Sensing in Schools Wolfgang Sulzer Institute for Geography and Regional Science University of Graz Heinrichstrasse 36, A-8010 Graz/Austria wolfgang.sulzer@uni-graz.at

More information

Using Remote Sensing Imagery to Evaluate Post-Wildfire Damage in Southern California

Using Remote Sensing Imagery to Evaluate Post-Wildfire Damage in Southern California Graham Emde GEOG 3230 Advanced Remote Sensing February 22, 2013 Lab #1 Using Remote Sensing Imagery to Evaluate Post-Wildfire Damage in Southern California Introduction Wildfires are a common disturbance

More information

WATER BODY EXTRACTION FROM MULTI SPECTRAL IMAGE BY SPECTRAL PATTERN ANALYSIS

WATER BODY EXTRACTION FROM MULTI SPECTRAL IMAGE BY SPECTRAL PATTERN ANALYSIS WATER BODY EXTRACTION FROM MULTI SPECTRAL IMAGE BY SPECTRAL PATTERN ANALYSIS Nguyen Dinh Duong Department of Environmental Information Study and Analysis, Institute of Geography, 18 Hoang Quoc Viet Rd.,

More information

Mapping Earth from Space Remote sensing and satellite images. Remote sensing developments from war

Mapping Earth from Space Remote sensing and satellite images. Remote sensing developments from war Mapping Earth from Space Remote sensing and satellite images Geomatics includes all the following spatial technologies: a. Cartography "The art, science and technology of making maps" b. Geographic Information

More information

Using Remote Sensing to Monitor Soil Carbon Sequestration

Using Remote Sensing to Monitor Soil Carbon Sequestration Using Remote Sensing to Monitor Soil Carbon Sequestration E. Raymond Hunt, Jr. USDA-ARS Hydrology and Remote Sensing Beltsville Agricultural Research Center Beltsville, Maryland Introduction and Overview

More information

Electromagnetic Radiation (EMR) and Remote Sensing

Electromagnetic Radiation (EMR) and Remote Sensing Electromagnetic Radiation (EMR) and Remote Sensing 1 Atmosphere Anything missing in between? Electromagnetic Radiation (EMR) is radiated by atomic particles at the source (the Sun), propagates through

More information

MODIS IMAGES RESTORATION FOR VNIR BANDS ON FIRE SMOKE AFFECTED AREA

MODIS IMAGES RESTORATION FOR VNIR BANDS ON FIRE SMOKE AFFECTED AREA MODIS IMAGES RESTORATION FOR VNIR BANDS ON FIRE SMOKE AFFECTED AREA Li-Yu Chang and Chi-Farn Chen Center for Space and Remote Sensing Research, National Central University, No. 300, Zhongda Rd., Zhongli

More information

The Role of SPOT Satellite Images in Mapping Air Pollution Caused by Cement Factories

The Role of SPOT Satellite Images in Mapping Air Pollution Caused by Cement Factories The Role of SPOT Satellite Images in Mapping Air Pollution Caused by Cement Factories Dr. Farrag Ali FARRAG Assistant Prof. at Civil Engineering Dept. Faculty of Engineering Assiut University Assiut, Egypt.

More information

Remote Sensing Satellite Information Sheets Geophysical Institute University of Alaska Fairbanks

Remote Sensing Satellite Information Sheets Geophysical Institute University of Alaska Fairbanks Remote Sensing Satellite Information Sheets Geophysical Institute University of Alaska Fairbanks ASTER Advanced Spaceborne Thermal Emission and Reflection Radiometer AVHRR Advanced Very High Resolution

More information

ENVI Classic Tutorial: Atmospherically Correcting Multispectral Data Using FLAASH 2

ENVI Classic Tutorial: Atmospherically Correcting Multispectral Data Using FLAASH 2 ENVI Classic Tutorial: Atmospherically Correcting Multispectral Data Using FLAASH Atmospherically Correcting Multispectral Data Using FLAASH 2 Files Used in this Tutorial 2 Opening the Raw Landsat Image

More information

ENVI THE PREMIER SOFTWARE FOR EXTRACTING INFORMATION FROM GEOSPATIAL IMAGERY.

ENVI THE PREMIER SOFTWARE FOR EXTRACTING INFORMATION FROM GEOSPATIAL IMAGERY. ENVI THE PREMIER SOFTWARE FOR EXTRACTING INFORMATION FROM GEOSPATIAL IMAGERY. ENVI Imagery Becomes Knowledge ENVI software uses proven scientific methods and automated processes to help you turn geospatial

More information

ANALYSIS OF FOREST CHANGE IN FIRE DAMAGE AREA USING SATELLITE IMAGES

ANALYSIS OF FOREST CHANGE IN FIRE DAMAGE AREA USING SATELLITE IMAGES ANALYSIS OF FOREST CHANGE IN FIRE DAMAGE AREA USING SATELLITE IMAGES Joon Mook Kang, Professor Joon Kyu Park, Ph.D Min Gyu Kim, Ph.D._Candidate Dept of Civil Engineering, Chungnam National University 220

More information

TerraColor White Paper

TerraColor White Paper TerraColor White Paper TerraColor is a simulated true color digital earth imagery product developed by Earthstar Geographics LLC. This product was built from imagery captured by the US Landsat 7 (ETM+)

More information

Software requirements * :

Software requirements * : Title: Product Type: Developer: Target audience: Format: Software requirements * : Data: Estimated time to complete: Fire Mapping using ASTER Part I: The ASTER instrument and fire damage assessment Part

More information

See Lab 8, Natural Resource Canada RS Tutorial web pages Tues 3/24 Supervised land cover classification See Lab 9, NR Canada RS Tutorial web pages

See Lab 8, Natural Resource Canada RS Tutorial web pages Tues 3/24 Supervised land cover classification See Lab 9, NR Canada RS Tutorial web pages SFR 406 Remote Sensing, Image Interpretation and Forest Mapping EXAM # 2 (23 April 2015) REVIEW SHEET www.umaine.edu/mial/courses/sfr406/index.htm (Lecture powerpoint & notes) TOPICS COVERED ON 2 nd EXAM:

More information

Big data and Earth observation New challenges in remote sensing images interpretation

Big data and Earth observation New challenges in remote sensing images interpretation Big data and Earth observation New challenges in remote sensing images interpretation Pierre Gançarski ICube CNRS - Université de Strasbourg 2014 Pierre Gançarski Big data and Earth observation 1/58 1

More information

Monitoring a Changing Environment with Synthetic Aperture Radar. Alaska Satellite Facility National Park Service Don Atwood

Monitoring a Changing Environment with Synthetic Aperture Radar. Alaska Satellite Facility National Park Service Don Atwood Monitoring a Changing Environment with Synthetic Aperture Radar Don Atwood Alaska Satellite Facility 1 Entering the SAR Age 2 SAR Satellites RADARSAT-1 Launched 1995 by CSA 5.6 cm (C-Band) HH Polarization

More information

Obtaining and Processing MODIS Data

Obtaining and Processing MODIS Data Obtaining and Processing MODIS Data MODIS is an extensive program using sensors on two satellites that each provide complete daily coverage of the earth. The data have a variety of resolutions; spectral,

More information

Digital image processing

Digital image processing 746A27 Remote Sensing and GIS Lecture 4 Digital image processing Chandan Roy Guest Lecturer Department of Computer and Information Science Linköping University Digital Image Processing Most of the common

More information

Environmental Remote Sensing GEOG 2021

Environmental Remote Sensing GEOG 2021 Environmental Remote Sensing GEOG 2021 Lecture 4 Image classification 2 Purpose categorising data data abstraction / simplification data interpretation mapping for land cover mapping use land cover class

More information

Data Processing Flow Chart

Data Processing Flow Chart Legend Start V1 V2 V3 Completed Version 2 Completion date Data Processing Flow Chart Data: Download a) AVHRR: 1981-1999 b) MODIS:2000-2010 c) SPOT : 1998-2002 No Progressing Started Did not start 03/12/12

More information

Remote Sensing an Introduction

Remote Sensing an Introduction Remote Sensing an Introduction Seminar: Space is the Place Referenten: Anica Huck & Michael Schlund Remote Sensing means the observation of, or gathering information about, a target by a device separated

More information

Remote Sensing and Land Use Classification: Supervised vs. Unsupervised Classification Glen Busch

Remote Sensing and Land Use Classification: Supervised vs. Unsupervised Classification Glen Busch Remote Sensing and Land Use Classification: Supervised vs. Unsupervised Classification Glen Busch Introduction In this time of large-scale planning and land management on public lands, managers are increasingly

More information

Introduction to Imagery and Raster Data in ArcGIS

Introduction to Imagery and Raster Data in ArcGIS Esri International User Conference San Diego, California Technical Workshops July 25, 2012 Introduction to Imagery and Raster Data in ArcGIS Simon Woo slides Cody Benkelman - demos Overview of Presentation

More information

Overview. What is EMR? Electromagnetic Radiation (EMR) LA502 Special Studies Remote Sensing

Overview. What is EMR? Electromagnetic Radiation (EMR) LA502 Special Studies Remote Sensing LA502 Special Studies Remote Sensing Electromagnetic Radiation (EMR) Dr. Ragab Khalil Department of Landscape Architecture Faculty of Environmental Design King AbdulAziz University Room 103 Overview What

More information

Relating Land Cover Changes to Stream Water Quality in North Carolina

Relating Land Cover Changes to Stream Water Quality in North Carolina Relating Land Cover Changes to Stream Water Quality in North Carolina STUDENT HANDOUT! Central Question How has land cover within Long Creek Watershed in Charlotte, NC changed between 1988 and 2008? Overview

More information

Assessing Hurricane Katrina Damage to the Mississippi Gulf Coast Using IKONOS Imagery

Assessing Hurricane Katrina Damage to the Mississippi Gulf Coast Using IKONOS Imagery Assessing Hurricane Katrina Damage to the Mississippi Gulf Coast Using IKONOS Imagery Joseph P. Spruce Science Systems and Applications, Inc. John C., MS 39529 Rodney McKellip NASA Project Integration

More information

U.S. Geological Survey Earth Resources Operation Systems (EROS) Data Center

U.S. Geological Survey Earth Resources Operation Systems (EROS) Data Center U.S. Geological Survey Earth Resources Operation Systems (EROS) Data Center World Data Center for Remotely Sensed Land Data USGS EROS DATA CENTER Land Remote Sensing from Space: Acquisition to Applications

More information

Advanced Image Management using the Mosaic Dataset

Advanced Image Management using the Mosaic Dataset Esri International User Conference San Diego, California Technical Workshops July 25, 2012 Advanced Image Management using the Mosaic Dataset Vinay Viswambharan, Mike Muller Agenda ArcGIS Image Management

More information

INTRODUCTION TO REMOTE SENSING

INTRODUCTION TO REMOTE SENSING INTRODUCTION TO REMOTE SENSING Dr Robert Sanderson New Mexico State University Satellite picture of Las Cruces, NM Table of Contents Introduction...1 Electromagnetic energy...1 Reflection and absorption...2

More information

The premier software for extracting information from geospatial imagery.

The premier software for extracting information from geospatial imagery. Imagery Becomes Knowledge ENVI The premier software for extracting information from geospatial imagery. ENVI Imagery Becomes Knowledge Geospatial imagery is used more and more across industries because

More information

How to calculate reflectance and temperature using ASTER data

How to calculate reflectance and temperature using ASTER data How to calculate reflectance and temperature using ASTER data Prepared by Abduwasit Ghulam Center for Environmental Sciences at Saint Louis University September, 2009 This instructions walk you through

More information

Monitoring Soil Moisture from Space. Dr. Heather McNairn Science and Technology Branch Agriculture and Agri-Food Canada heather.mcnairn@agr.gc.

Monitoring Soil Moisture from Space. Dr. Heather McNairn Science and Technology Branch Agriculture and Agri-Food Canada heather.mcnairn@agr.gc. Monitoring Soil Moisture from Space Dr. Heather McNairn Science and Technology Branch Agriculture and Agri-Food Canada heather.mcnairn@agr.gc.ca What is Remote Sensing? Scientists turn the raw data collected

More information

Remote Sensing. Vandaag. Voordelen Remote Sensing Wat is Remote Sensing? Vier elementen Remote Sensing systeem

Remote Sensing. Vandaag. Voordelen Remote Sensing Wat is Remote Sensing? Vier elementen Remote Sensing systeem Remote Sensing 1 Vandaag Voordelen Remote Sensing Wat is Remote Sensing? Vier elementen Remote Sensing systeem 2 Nederland Vanaf 700 km hoogte Landsat TM mozaïek 3 Europa vanaf 36000 km hoogte 4 5 Mount

More information

APPLICATION OF TERRA/ASTER DATA ON AGRICULTURE LAND MAPPING. Genya SAITO*, Naoki ISHITSUKA*, Yoneharu MATANO**, and Masatane KATO***

APPLICATION OF TERRA/ASTER DATA ON AGRICULTURE LAND MAPPING. Genya SAITO*, Naoki ISHITSUKA*, Yoneharu MATANO**, and Masatane KATO*** APPLICATION OF TERRA/ASTER DATA ON AGRICULTURE LAND MAPPING Genya SAITO*, Naoki ISHITSUKA*, Yoneharu MATANO**, and Masatane KATO*** *National Institute for Agro-Environmental Sciences 3-1-3 Kannondai Tsukuba

More information

Generation of Cloud-free Imagery Using Landsat-8

Generation of Cloud-free Imagery Using Landsat-8 Generation of Cloud-free Imagery Using Landsat-8 Byeonghee Kim 1, Youkyung Han 2, Yonghyun Kim 3, Yongil Kim 4 Department of Civil and Environmental Engineering, Seoul National University (SNU), Seoul,

More information

The USGS Landsat Big Data Challenge

The USGS Landsat Big Data Challenge The USGS Landsat Big Data Challenge Brian Sauer Engineering and Development USGS EROS bsauer@usgs.gov U.S. Department of the Interior U.S. Geological Survey USGS EROS and Landsat 2 Data Utility and Exploitation

More information

ENVI Classic Tutorial: Atmospherically Correcting Hyperspectral Data using FLAASH 2

ENVI Classic Tutorial: Atmospherically Correcting Hyperspectral Data using FLAASH 2 ENVI Classic Tutorial: Atmospherically Correcting Hyperspectral Data Using FLAASH Atmospherically Correcting Hyperspectral Data using FLAASH 2 Files Used in This Tutorial 2 Opening the Uncorrected AVIRIS

More information

and satellite image download with the USGS GloVis portal

and satellite image download with the USGS GloVis portal Tutorial: NDVI calculation with SPRING GIS and satellite image download with the USGS GloVis portal Content overview: Downloading data from GloVis: p 2 Using SPRING GIS: p 11 This document is meant to

More information

River Flood Damage Assessment using IKONOS images, Segmentation Algorithms & Flood Simulation Models

River Flood Damage Assessment using IKONOS images, Segmentation Algorithms & Flood Simulation Models River Flood Damage Assessment using IKONOS images, Segmentation Algorithms & Flood Simulation Models Steven M. de Jong & Raymond Sluiter Utrecht University Corné van der Sande Netherlands Earth Observation

More information

A tiered reconnaissance approach toward flood monitoring utilising multi-source radar and optical data

A tiered reconnaissance approach toward flood monitoring utilising multi-source radar and optical data 5 th International Workshop on Remote Sensing for Disaster Response A tiered reconnaissance approach toward flood monitoring utilising multi-source radar and optical data Anneley McMillan Dr. Beverley

More information

JACIE Science Applications of High Resolution Imagery at the USGS EROS Data Center

JACIE Science Applications of High Resolution Imagery at the USGS EROS Data Center JACIE Science Applications of High Resolution Imagery at the USGS EROS Data Center November 8-10, 2004 U.S. Department of the Interior U.S. Geological Survey Michael Coan, SAIC USGS EROS Data Center coan@usgs.gov

More information

The Idiots Guide to GIS and Remote Sensing

The Idiots Guide to GIS and Remote Sensing The Idiots Guide to GIS and Remote Sensing 1. Picking the right imagery 1 2. Accessing imagery 1 3. Processing steps 1 a. Geocorrection 2 b. Processing Landsat images layerstacking 4 4. Landcover classification

More information

APPLICATION OF GOOGLE EARTH FOR THE DEVELOPMENT OF BASE MAP IN THE CASE OF GISH ABBAY SEKELA, AMHARA STATE, ETHIOPIA

APPLICATION OF GOOGLE EARTH FOR THE DEVELOPMENT OF BASE MAP IN THE CASE OF GISH ABBAY SEKELA, AMHARA STATE, ETHIOPIA APPLICATION OF GOOGLE EARTH FOR THE DEVELOPMENT OF BASE MAP IN THE CASE OF GISH ABBAY SEKELA, AMHARA STATE, ETHIOPIA Abineh Tilahun Department of Geography and environmental studies, Adigrat University,

More information

Chapter Contents Page No

Chapter Contents Page No Chapter Contents Page No Preface Acknowledgement 1 Basics of Remote Sensing 1 1.1. Introduction 1 1.2. Definition of Remote Sensing 1 1.3. Principles of Remote Sensing 1 1.4. Various Stages in Remote Sensing

More information

SEMI-AUTOMATED CLOUD/SHADOW REMOVAL AND LAND COVER CHANGE DETECTION USING SATELLITE IMAGERY

SEMI-AUTOMATED CLOUD/SHADOW REMOVAL AND LAND COVER CHANGE DETECTION USING SATELLITE IMAGERY SEMI-AUTOMATED CLOUD/SHADOW REMOVAL AND LAND COVER CHANGE DETECTION USING SATELLITE IMAGERY A. K. Sah a, *, B. P. Sah a, K. Honji a, N. Kubo a, S. Senthil a a PASCO Corporation, 1-1-2 Higashiyama, Meguro-ku,

More information

LANDSAT 8 Level 1 Product Performance

LANDSAT 8 Level 1 Product Performance Réf: IDEAS-TN-10-QualityReport LANDSAT 8 Level 1 Product Performance Quality Report Month/Year: January 2016 Date: 26/01/2016 Issue/Rev:1/9 1. Scope of this document On May 30, 2013, data from the Landsat

More information

Introduction to Remote Sensing and Image Processing

Introduction to Remote Sensing and Image Processing Introduction to Remote Sensing and Image Processing Of all the various data sources used in GIS, one of the most important is undoubtedly that provided by remote sensing. Through the use of satellites,

More information

Remote sensing and GIS applications in coastal zone monitoring

Remote sensing and GIS applications in coastal zone monitoring Remote sensing and GIS applications in coastal zone monitoring T. Alexandridis, C. Topaloglou, S. Monachou, G.Tsakoumis, A. Dimitrakos, D. Stavridou Lab of Remote Sensing and GIS School of Agriculture

More information

Operational Space- Based Crop Mapping Protocols at AAFC A. Davidson, H. McNairn and T. Fisette.

Operational Space- Based Crop Mapping Protocols at AAFC A. Davidson, H. McNairn and T. Fisette. Operational Space- Based Crop Mapping Protocols at AAFC A. Davidson, H. McNairn and T. Fisette. Science & Technology Branch. Agriculture and Agri-Food Canada. 1. Introduction Space-Based Crop Mapping at

More information

APPLICATION OF MULTITEMPORAL LANDSAT DATA TO MAP AND MONITOR LAND COVER AND LAND USE CHANGE IN THE CHESAPEAKE BAY WATERSHED

APPLICATION OF MULTITEMPORAL LANDSAT DATA TO MAP AND MONITOR LAND COVER AND LAND USE CHANGE IN THE CHESAPEAKE BAY WATERSHED APPLICATION OF MULTITEMPORAL LANDSAT DATA TO MAP AND MONITOR LAND COVER AND LAND USE CHANGE IN THE CHESAPEAKE BAY WATERSHED S. J. GOETZ Woods Hole Research Center Woods Hole, Massachusetts 054-096 USA

More information

Image Analysis CHAPTER 16 16.1 ANALYSIS PROCEDURES

Image Analysis CHAPTER 16 16.1 ANALYSIS PROCEDURES CHAPTER 16 Image Analysis 16.1 ANALYSIS PROCEDURES Studies for various disciplines require different technical approaches, but there is a generalized pattern for geology, soils, range, wetlands, archeology,

More information

Information Contents of High Resolution Satellite Images

Information Contents of High Resolution Satellite Images Information Contents of High Resolution Satellite Images H. Topan, G. Büyüksalih Zonguldak Karelmas University K. Jacobsen University of Hannover, Germany Keywords: satellite images, mapping, resolution,

More information

STAAR Science Tutorial 30 TEK 8.8C: Electromagnetic Waves

STAAR Science Tutorial 30 TEK 8.8C: Electromagnetic Waves Name: Teacher: Pd. Date: STAAR Science Tutorial 30 TEK 8.8C: Electromagnetic Waves TEK 8.8C: Explore how different wavelengths of the electromagnetic spectrum such as light and radio waves are used to

More information

Evaluation of the Effect of Upper-Level Cirrus Clouds on Satellite Retrievals of Low-Level Cloud Droplet Effective Radius

Evaluation of the Effect of Upper-Level Cirrus Clouds on Satellite Retrievals of Low-Level Cloud Droplet Effective Radius Evaluation of the Effect of Upper-Level Cirrus Clouds on Satellite Retrievals of Low-Level Cloud Droplet Effective Radius F.-L. Chang and Z. Li Earth System Science Interdisciplinary Center University

More information

MOD09 (Surface Reflectance) User s Guide

MOD09 (Surface Reflectance) User s Guide MOD09 (Surface ) User s Guide MODIS Land Surface Science Computing Facility Principal Investigator: Dr. Eric F. Vermote Web site: http://modis-sr.ltdri.org Correspondence e-mail address: mod09@ltdri.org

More information

VCS REDD Methodology Module. Methods for monitoring forest cover changes in REDD project activities

VCS REDD Methodology Module. Methods for monitoring forest cover changes in REDD project activities 1 VCS REDD Methodology Module Methods for monitoring forest cover changes in REDD project activities Version 1.0 May 2009 I. SCOPE, APPLICABILITY, DATA REQUIREMENT AND OUTPUT PARAMETERS Scope This module

More information

Multinomial Logistics Regression for Digital Image Classification

Multinomial Logistics Regression for Digital Image Classification Multinomial Logistics Regression for Digital Image Classification Dr. Moe Myint, Chief Scientist, Mapping and Natural Resources Information Integration (MNRII), Switzerland maungmoe.myint@mnrii.com KEY

More information

Land Use/ Land Cover Mapping Initiative for Kansas and the Kansas River Watershed

Land Use/ Land Cover Mapping Initiative for Kansas and the Kansas River Watershed Land Use/ Land Cover Mapping Initiative for Kansas and the Kansas River Watershed Kansas Biological Survey Kansas Applied Remote Sensing Program April 2008 Previous Kansas LULC Projects Kansas LULC Map

More information

'Developments and benefits of hydrographic surveying using multispectral imagery in the coastal zone

'Developments and benefits of hydrographic surveying using multispectral imagery in the coastal zone Abstract With the recent launch of enhanced high-resolution commercial satellites, available imagery has improved from four-bands to eight-band multispectral. Simultaneously developments in remote sensing

More information

RESOLUTION MERGE OF 1:35.000 SCALE AERIAL PHOTOGRAPHS WITH LANDSAT 7 ETM IMAGERY

RESOLUTION MERGE OF 1:35.000 SCALE AERIAL PHOTOGRAPHS WITH LANDSAT 7 ETM IMAGERY RESOLUTION MERGE OF 1:35.000 SCALE AERIAL PHOTOGRAPHS WITH LANDSAT 7 ETM IMAGERY M. Erdogan, H.H. Maras, A. Yilmaz, Ö.T. Özerbil General Command of Mapping 06100 Dikimevi, Ankara, TURKEY - (mustafa.erdogan;

More information

From lowest energy to highest energy, which of the following correctly orders the different categories of electromagnetic radiation?

From lowest energy to highest energy, which of the following correctly orders the different categories of electromagnetic radiation? From lowest energy to highest energy, which of the following correctly orders the different categories of electromagnetic radiation? From lowest energy to highest energy, which of the following correctly

More information

Evaluations of the CALIPSO Cloud Optical Depth Algorithm Through Comparisons with a GOES Derived Cloud Analysis

Evaluations of the CALIPSO Cloud Optical Depth Algorithm Through Comparisons with a GOES Derived Cloud Analysis Generated using V3.0 of the official AMS LATEX template Evaluations of the CALIPSO Cloud Optical Depth Algorithm Through Comparisons with a GOES Derived Cloud Analysis Katie Carbonari, Heather Kiley, and

More information

High Resolution RF Analysis: The Benefits of Lidar Terrain & Clutter Datasets

High Resolution RF Analysis: The Benefits of Lidar Terrain & Clutter Datasets 0 High Resolution RF Analysis: The Benefits of Lidar Terrain & Clutter Datasets January 15, 2014 Martin Rais 1 High Resolution Terrain & Clutter Datasets: Why Lidar? There are myriad methods, techniques

More information

Istanbul Technical University-Center for Satellite Communications and Remote Sensing (ITU-CSCRS)

Istanbul Technical University-Center for Satellite Communications and Remote Sensing (ITU-CSCRS) Istanbul Technical University-Center for Satellite Communications and Remote Sensing (ITU-CSCRS) Istanbul Technical University, Center for Satellite Communications and Remote Sensing (ITU-CSCRS) was originally

More information

REMOTE SENSING AND ENVIRONMENTAL MONITORING. P. M. Mather School of Geography, The University of Nottingham, U.K.

REMOTE SENSING AND ENVIRONMENTAL MONITORING. P. M. Mather School of Geography, The University of Nottingham, U.K. REMOTE SENSING AND ENVIRONMENTAL MONITORING P. M. Mather School of Geography, The University of Nottingham, U.K. Keywords: Earth observation, image processing, lidar, pattern recognition, radar Contents

More information

GIS and Remote Sensing in Diachronic Study of Agriculture in Greece

GIS and Remote Sensing in Diachronic Study of Agriculture in Greece GIS and Remote Sensing in Diachronic Study of Agriculture in Greece Maria Androulidaki a, Michail Salampasis b, Vagis Samathrakis c, Christos Batzios d a Alexander Technology Educational Institute of Thessaloniki,

More information

Monitoring of Arctic Conditions from a Virtual Constellation of Synthetic Aperture Radar Satellites

Monitoring of Arctic Conditions from a Virtual Constellation of Synthetic Aperture Radar Satellites DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Monitoring of Arctic Conditions from a Virtual Constellation of Synthetic Aperture Radar Satellites Hans C. Graber RSMAS

More information

3D VISUALIZATION OF GEOTHERMAL WELLS DIRECTIONAL SURVEYS AND INTEGRATION WITH DIGITAL ELEVATION MODEL (DEM)

3D VISUALIZATION OF GEOTHERMAL WELLS DIRECTIONAL SURVEYS AND INTEGRATION WITH DIGITAL ELEVATION MODEL (DEM) Presented at Short Course VII on Exploration for Geothermal Resources, organized by UNU-GTP, GDC and KenGen, at Lake Bogoria and Lake Naivasha, Kenya, Oct. 27 Nov. 18, 2012. GEOTHERMAL TRAINING PROGRAMME

More information

Color image processing: pseudocolor processing

Color image processing: pseudocolor processing Color image processing: pseudocolor processing by Gleb V. Tcheslavski: gleb@ee.lamar.edu http://ee.lamar.edu/gleb/dip/index.htm Spring 2008 ELEN 4304/5365 DIP 1 Preliminaries Pseudocolor (false color)

More information

SPOT Satellite Earth Observation System Presentation to the JACIE Civil Commercial Imagery Evaluation Workshop March 2007

SPOT Satellite Earth Observation System Presentation to the JACIE Civil Commercial Imagery Evaluation Workshop March 2007 SPOT Satellite Earth Observation System Presentation to the JACIE Civil Commercial Imagery Evaluation Workshop March 2007 Topics Presented Quick summary of system characteristics Formosat-2 Satellite Archive

More information

Design of a High Resolution Multispectral Scanner for Developing Vegetation Indexes

Design of a High Resolution Multispectral Scanner for Developing Vegetation Indexes Design of a High Resolution Multispectral Scanner for Developing Vegetation Indexes Rishitosh kumar sinha*, Roushan kumar mishra, Sam jeba kumar, Gunasekar. S Dept. of Instrumentation & Control Engg. S.R.M

More information

Let s SAR: Mapping and monitoring of land cover change with ALOS/ALOS-2 L-band data

Let s SAR: Mapping and monitoring of land cover change with ALOS/ALOS-2 L-band data Let s SAR: Mapping and monitoring of land cover change with ALOS/ALOS-2 L-band data Rajesh Bahadur THAPA, Masanobu SHIMADA, Takeshi MOTOHKA, Manabu WATANABE and Shinichi rajesh.thapa@jaxa.jp; thaparb@gmail.com

More information

Remote Sensing for Geographical Analysis

Remote Sensing for Geographical Analysis Remote Sensing for Geographical Analysis Geography 651, Fall 2008 Department of Geography Texas A&M University (3 credit hours) Instructor: Dr. Hongxing Liu Office hours: Tue & Thur 10:00AM-12:00AM, O&M

More information

Welcome to NASA Applied Remote Sensing Training (ARSET) Webinar Series

Welcome to NASA Applied Remote Sensing Training (ARSET) Webinar Series Welcome to NASA Applied Remote Sensing Training (ARSET) Webinar Series Introduction to Remote Sensing Data for Water Resources Management Course Dates: October 17, 24, 31 November 7, 14 Time: 8-9 a.m.

More information

Understanding Raster Data

Understanding Raster Data Introduction The following document is intended to provide a basic understanding of raster data. Raster data layers (commonly referred to as grids) are the essential data layers used in all tools developed

More information

MULTIPURPOSE USE OF ORTHOPHOTO MAPS FORMING BASIS TO DIGITAL CADASTRE DATA AND THE VISION OF THE GENERAL DIRECTORATE OF LAND REGISTRY AND CADASTRE

MULTIPURPOSE USE OF ORTHOPHOTO MAPS FORMING BASIS TO DIGITAL CADASTRE DATA AND THE VISION OF THE GENERAL DIRECTORATE OF LAND REGISTRY AND CADASTRE MULTIPURPOSE USE OF ORTHOPHOTO MAPS FORMING BASIS TO DIGITAL CADASTRE DATA AND THE VISION OF THE GENERAL DIRECTORATE OF LAND REGISTRY AND CADASTRE E.ÖZER, H.TUNA, F.Ç.ACAR, B.ERKEK, S.BAKICI General Directorate

More information

HANDBOOK for detecting land cover changes with Landsat data archive

HANDBOOK for detecting land cover changes with Landsat data archive HANDBOOK for detecting land cover changes with Landsat data archive Jan 2011 Northwest Pacific Region Environmental Cooperation Center Table of Contents 1. Introduction 1 2. Obtaining Landsat data 2 2.1

More information

16 th IOCCG Committee annual meeting. Plymouth, UK 15 17 February 2011. mission: Present status and near future

16 th IOCCG Committee annual meeting. Plymouth, UK 15 17 February 2011. mission: Present status and near future 16 th IOCCG Committee annual meeting Plymouth, UK 15 17 February 2011 The Meteor 3M Mt satellite mission: Present status and near future plans MISSION AIMS Satellites of the series METEOR M M are purposed

More information

EVALUATION OF AIRBORNE LIDAR DIGITAL TERRAIN MAPPING FOR HIGHWAY CORRIDOR PLANNING AND DESIGN

EVALUATION OF AIRBORNE LIDAR DIGITAL TERRAIN MAPPING FOR HIGHWAY CORRIDOR PLANNING AND DESIGN Waheed Uddin Director, Center for Advanced Infrastructure Technology, Carrier Hall 203 The University of Mississippi, University, MS 38677-1848, USA cvuddin@olemiss.edu KEY WORDS: Terrain, mapping, airborne,

More information

Joint Polar Satellite System (JPSS)

Joint Polar Satellite System (JPSS) Joint Polar Satellite System (JPSS) John Furgerson, User Liaison Joint Polar Satellite System National Environmental Satellite, Data, and Information Service National Oceanic and Atmospheric Administration

More information