Space photographs as remote sensing data for reef environments Julie A. Robinson Office of Earth Sciences, NASA Johnson Space Center Lockheed Martin Space.

Slides:



Advertisements
Similar presentations
( Remote Sensing : RS) 11. (Definition) (Object) (Phenomena)
Advertisements

LANDSAT Program Update Tim Newman Coordinator, USGS Land Remote Sensing Program National Geospatial Advisory Committee December 3, 2014.
Major Operations of Digital Image Processing (DIP) Image Quality Assessment Radiometric Correction Geometric Correction Image Classification Introduction.
PRESENTATION ON “ Processing Of Satellite Image Using Dip ” by B a n d a s r e e n i v a s Assistant Professor Department of Electronics & Communication.
Resolution.
August 5 – 7, 2008NASA Habitats Workshop Optical Properties and Quantitative Remote Sensing of Kelp Forest and Seagrass Habitats Richard C. Zimmerman -
MISSION OPERATIONS DIRECTORATE CARGO INTEGRATION AND OPERATIONS BRANCH Brion J. Au Johnson Space Center/DO55.
Remote Sensing Instructor: Professor Yuji Murayama Teaching Assistant: Niloofar Haji Mirza Aghasi.
Digital Elevation Models GLY 560: GIS and Remote Sensing for Earth Scientists Class Home Page:
CBERS: the Brazilian Experience Gilberto Camara Director for Earth Observation INPE Workshop – 3 Years of CBERS, Beijing, October 2002.
VENUS (Vegetation and Environment New µ-Spacecraft) A demonstration space mission dedicated to land surface environment (Vegetation and Environment New.
January 20, 2006 Geog 258: Maps and GIS
Aerial Imagery David Davis USDA Farm Service Agency Aerial Photography Field Office.
Hyperspectral Satellite Imaging Planning a Mission Victor Gardner University of Maryland 2007 AIAA Region 1 Mid-Atlantic Student Conference National Institute.
Data Acquisition Lecture 8. Data Sources  Data Transfer  Getting data from the internet and importing  Data Collection  One of the most expensive.
Ken Driese Dept. of Botany. 1. How could you assess the effect of drought on plant biomass in California? 2. How could you map sage grouse habitat in.
Aerial Imagery David Davis USDA Farm Service Agency Aerial Photography Field Office USDA-FSA-APFO.
EG1106: GI: a primer Field & Survey data collection 19 th November 2004.
Module 2.1 Monitoring activity data for forests using remote sensing REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF 1 Module.
The Geographer’s Tools
Geography 121 Lab #4 Finding Landsat Data November 8, 2006 Dave Alleman Pat Clancy Sarah Gustafson.
Accuracy Assessment. 2 Because it is not practical to test every pixel in the classification image, a representative sample of reference points in the.
Use of Remote Sensing Data for Delineation of Wildland Fire Effects
1 Image Pre-Processing. 2 Digital Image Processing The process of extracting information from digital images obtained from satellites Information regarding.
Satellite Imagery and Remote Sensing NC Climate Fellows June 2012 DeeDee Whitaker SW Guilford High Earth/Environmental Science & Chemistry.
ARSF Data Processing Consequences of the Airborne Processing Library Mark Warren Plymouth Marine Laboratory, Plymouth, UK RSPSoc 2012 – Greenwich, London.
Acoustic Ground Discrimination Systems (AGDS) Fast mapping of sublittoral habitats without limitations due to turbidity based on the Procedural Guideline.
Orthorectification using
National Mapping Division EROS Data Center U. S. Geological Survey U.S. Geological Survey Earth Resources Operation Systems (EROS) Data Center World Data.
Acquiring Aerial Photos Where and how to get aerial photography.
Remote Sensing with Multispectral Scanners. Multispectral scanners First developed in early 1970’s Why use? Concept: Gather data from very specific wavelengths.
Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Emilio Chuvieco and Alfredo Huete Fundamentals of Satellite Remote.
Getting Ready for the Future Woody Turner Earth Science Division NASA Headquarters May 7, 2014 Biodiversity and Ecological Forecasting Team Meeting Sheraton.
Aseri Baleilevuka OCEANS & ISLANDS PROGRAM SOPAC-SPC Benthic Habitat Mapping Lifuka Island.
10/12/2015 GEM Lecture 10 Content Other Satellites.
Remote sensing and in situ measurements in the Global Earth Observing System of Systems Curtis Woodcock, Boston University.
By: Linda Kpormone Buame Department of Oceanography and Fisheries Date: 18 th January,2011.
Earth observation data for everyone: the CBERS experience Gilberto Câmara Director, National Institute for Space Research.
1 Enviromatics Environmental sampling Environmental sampling Вонр. проф. д-р Александар Маркоски Технички факултет – Битола 2008 год.
Support the spread of “good practice” in generating, managing, analysing and communicating spatial information Introduction to Remote Sensing Images By:
Remote Sensing Realities | June 2008 Remote Sensing Realities.
Terra Remote Sensing. Terra Remote Sensing Inc. is an internationally based Canadian remote sensing company with a background of 40.
Remote Sensing Data Acquisition. 1. Major Remote Sensing Systems.
Chapter 8 Remote Sensing & GIS Integration. Basics EM spectrum: fig p. 268 reflected emitted detection film sensor atmospheric attenuation.
Digital Image Processing Definition: Computer-based manipulation and interpretation of digital images.
U.S. Department of the Interior U.S. Geological Survey Entering A New Landsat Era – The Future is Now Tom Loveland U.S. Geological Survey Earth Resources.
Breakout Session IV: Applying Remote Sensing Observations to Impacts Assessment Background (1) The IPCC WG 2 Report (2008) “Climate Change Impacts, Adaptation.
Globes- 3-D representation of the earth Pros: Accurate shape, landmasses correct size and shape Cons: Inconvienent, only able to see one side at a time.
Remote Sensing SPOT and Other Moderate Resolution Satellite Systems
Fundamentals of Remote Sensing: Digital Image Analysis.
Geography. What is a GIS? GIS stands for Geographic Information System A tool people can use to map and analyze geographic data Organizes data by where.
INTRODUCTION TO GIS  Used to describe computer facilities which are used to handle data referenced to the spatial domain.  Has the ability to inter-
1 October 8, 2015 GIS Day 2015 Geospatial Technologies GPS (global positioning system) –Car GPS systems, yield monitors, smart phones RS (remote sensing)
Chapter 10.  Data collection workflow  Primary geographic data capture  Secondary geographic data capture  Obtaining data from external sources 
What is geography? What is the location of the Atlantic Ocean relative to Africa?
Teacher’s Notes: Digital Image Sources Digital images from space can be found at the following NASA web site: Click.
Data Models, Pixels, and Satellite Bands. Understand the differences between raster and vector data. What are digital numbers (DNs) and what do they.
Sub pixelclassification
SATELLITE ORBITS The monitoring capabilities of the sensor are, to a large extent, governed by the parameters of the satellite orbit. Different types of.
REMOTE SENSING DATA Markus Törmä Institute of Photogrammetry and Remote Sensing Helsinki University of Technology
Earth Observation Data as Public Goods: INPE’s experience Leila Fonseca National Institute for Space Research Brazil.
Satellite Image Pixel Size vs Mapping Scale
Introduction to Remote Sensing of the Environment Bot/Geog 4111/5111
Geog 121 Project 4: Finding LandSat Data
I-CMOR Integrated Chemical Mapping Optical Radar
Geometry of Aerial Photography
Satellite Image Pixel Size vs Mapping Scale
ERT 247 SENSOR & PLATFORM.
Using Earth SySTEM and GLOBE
Geog 121 Project 4: Finding LandSat Data
Presentation transcript:

Space photographs as remote sensing data for reef environments Julie A. Robinson Office of Earth Sciences, NASA Johnson Space Center Lockheed Martin Space Operations

Objectives n Provide information about space photography as a data source –pros and cons –accessibility n Show example of collaboration with ReefBase n Show potential for quantitative remote sensing applications n Look ahead to Space Station

Remote sensing data

Advantages of space photography over other remote sensing data n Low cost n Resolution can equal or exceed SPOT n Can be combined with other data and maps using existing image analysis and GIS software n Image size (Mb) small, transfer via internet n Long time series n Search tools on WWW

Cons: Space photos are more variable than data from robotic satellites n Resolution n Vignetting n Exposure and Illumination n Coverage areas n Cloud obstruction n Look angles n Usually needs to be digitized

Maximum possible digital resolution (minimum pixel size in m) for hand-held photographs scanned at 2400 ppi.

Variable illumination

International Space Station Daylight tracks for 16 consecutive orbits (about one day), 51.6 ° inclination, 173 naut. mi.

All taken from 200 naut. mi. with 100 mm lens

Web Access n Office of Earth Scienceshttp://eol.jsc.nasa.gov –Search tools: clickable map, key words, 350,000 + records –Browse images –Background information and reports –How to order photos n Earth from Space –Information for the general public –Outstanding photographs with captions that can be downloaded in high resolution –Kodak on-line printing service

ReefBase Collaboration Marco Noordeloos ICLARM

ReefBase Collaboration n Sharing photos

ReefBase Collaboration n Sharing photos n GIS Base Maps

STS

STS

STS

ReefBase Collaboration n Sharing photos n GIS Base Maps n “Missing Reefs” –Shuttle/ Station targets n Coarse-scale global survey n More???

Examples of marine remote sensing using space photos Mangrove and coastal land use classification Edward L. Webb, Ma. Arlene Evangelista Asian Institute of Technology Seagrass classification Warren Lee Long and Len McKenzie, Queensland Dept. Primary Industries

Coastal land use and mangroves-- Methods n Chanthaburi province, eastern Thailand n Land cover: rice fields, shrimp farms, orchards, degraded mangrove patches n Digitized RGB Shuttle photo, georeferenced to 1:50,000 topo map n Landsat TM image n A priori supervised classification n Ground truth with 45 sites

Coastal land use and mangroves-- Results n Space photo pixel size = 10.5 m after resampling n Mean consistency (overlap between the a priori and corrected image) was not significantly different between EOP and Landsat n High variability in land use classification consistency between photo and Landsat for a priori classifications –Ground-truth improved the consistency –Differences were at the edges of polygons

Seagrasses--Methods n Shoalwater Bay, Queensland n General survey map from video RS with diving ground truth n Digitized RGB Shuttle photo, georeferenced to survey map n Supervised classification

Seagrasses--Results n Pixel size ~58 m in the cropped image n Remarkable classification performance for the coarse scale of this pilot study n Confusion of mangroves and forest –can be reduced with shoreline filter n Confusion of seagrass and mud/sediments –need to apply species-specific information and exclude sparsely-growing seagrasses n Next step: full GIS

Conclusions n Space photography can be used as digital remote sensing data –studying and monitoring land use change –incorporation into existing GIS systems n This is particularly appropriate in cases where cost is an important factor –low budget –high number of images –regional scale

International Space Station (ISS) Window Observational Research Facility (WORF) n Optical quality, fused quartz window –transmissivity, interference, etc. n Removable scratch pane n Rack system with cooling, power, etc. n Payload and “Earth Obs” mode of data collection –film, ESC –multispectral and hyperspectral sensors

My view of reef opportunities on ISS n Filling in “missing reefs” during long-duration missions (photographic) n New and better instruments for the “techies” –satellite development –as the data collection platform –hyperspectral sensors developed for aircraft n Opportunity for reef-directed payload

Conclusions When all you have is a hammer, every problem looks like a nail. AND Don’t use a baseball bat to swat flies.