MODIS: Moderate-resolution Imaging Spectroradiometer National-Scale Remote Sensing Imagery for Natural Resource Applications Mark Finco Remote Sensing.

Slides:



Advertisements
Similar presentations
NOAA National Geophysical Data Center
Advertisements

GOFC/GOLD - Fire Requirements for Fire Observations.
USDA Forest Service, Remote Sensing Applications Center, FSWeb: WWW: LANCE User Working Group.
Scaling Biomass Measurements for Examining MODIS Derived Vegetation Products Matthew C. Reeves and Maosheng Zhao Numerical Terradynamic Simulation Group.
Remote Sensing of Evapotranspiration
AMwww.Remote-Sensing.info Ch.2 Remote Sensing Data Collection
Resolution.
Multispectral Remote Sensing Systems
Precision Agriculture in Environmental Sustainability Rachel Crocker.
FIA National Users Group Meeting – 8 December 2004 FIA Strategic Plan Greg Reams National Program Leader Forest Inventory & Analysis 1601 North.
Remote Sensing – Fire Weather Product Presentation
Detector Configurations Used for Panchromatic, Multispectral and Hyperspectral Remote Sensing Jensen, 2000.
Some Significant Current Projects. Landsat Multispectral Scanner (MSS) and Landsat Thematic Mapper (TM) Sensor System Characteristics.
Introduction, Satellite Imaging. Platforms Used to Acquire Remote Sensing Data Aircraft Low, medium & high altitude Higher level of spatial detail Satellite.
Detect and Simulate Vegetation, Surface Temperature, Rainfall and Aerosol Changes: From Global to Local Examples from EOS MODIS remote sensing Examples.
VENUS (Vegetation and Environment New µ-Spacecraft) A demonstration space mission dedicated to land surface environment (Vegetation and Environment New.
Remote Sensing of Mesoscale Vortices in Hurricane Eyewalls Presented by: Chris Castellano Brian Cerruti Stephen Garbarino.
Satellite Thermal Remote Sensing of Boiling Springs Lake Jeff Pedelty NASA Goddard Space Flight Center Goddard Center for Astrobiology.
Meteorological satellites – National Oceanographic and Atmospheric Administration (NOAA)-Polar Orbiting Environmental Satellite (POES) Orbital characteristics.
Geosynchronous Orbit A satellite in geosynchronous orbit circles the earth once each day. The time it takes for a satellite to orbit the earth is called.
Hyperspectral Satellite Imaging Planning a Mission Victor Gardner University of Maryland 2007 AIAA Region 1 Mid-Atlantic Student Conference National Institute.
Aerial photography and satellite imagery as data input GEOG 4103, Feb 20th Adina Racoviteanu.
Fire Products Training Workshop in Partnership with BAAQMD Santa Clara, CA September 10 – 12, 2013 Applied Remote SEnsing Training (ARSET) – Air Quality.
DROUGHT MONITORING THROUGH THE USE OF MODIS SATELLITE Amy Anderson, Curt Johnson, Dave Prevedel, & Russ Reading.
Satellite Imagery ARSET Applied Remote SEnsing Training A project of NASA Applied Sciences Introduction to Remote Sensing and Air Quality Applications.
Visible Satellite Imagery Spring 2015 ARSET - AQ Applied Remote Sensing Education and Training – Air Quality A project of NASA Applied Sciences Week –
USDA Forest Service Remote Sensing Applications Center Forest Inventory and Analysis New Technology How is FIA integrating new technological developments.
Satellite Imagery and Remote Sensing NC Climate Fellows June 2012 DeeDee Whitaker SW Guilford High Earth/Environmental Science & Chemistry.
Global land cover mapping from MODIS: algorithms and early results M.A. Friedl a,*, D.K. McIver a, J.C.F. Hodges a, X.Y. Zhang a, D. Muchoney b, A.H. Strahler.
Digital Numbers The Remote Sensing world calls cell values are also called a digital number or DN. In most of the imagery we work with the DN represents.
Assessment of Regional Vegetation Productivity: Using NDVI Temporal Profile Metrics Background NOAA satellite AVHRR data archive NDVI temporal profile.
Sentinel: Dynamic Fire Location Mapping. Near- Real Time Emergency Mapping Environmental Remote Sensing Group CSIRO Land and Water Defence Imagery & Geospatial.
MODIS-Based Techniques for Assessing of Fire Location and Timing in the Alaskan Boreal Forest Nancy H.F. French 1, Lucas Spaete 1, Elizabeth Hoy 2, Amber.
Resolution Resolution. Landsat ETM+ image Learning Objectives Be able to name and define the four types of data resolution. Be able to calculate the.
Winter precipitation and snow water equivalent estimation and reconstruction for the Salt-Verde-Tonto River Basin for the Salt-Verde-Tonto River Basin.
Remote Sensing and Image Processing: 8 Dr. Hassan J. Eghbali.
Slide #1 Emerging Remote Sensing Data, Systems, and Tools to Support PEM Applications for Resource Management Olaf Niemann Department of Geography University.
Christine Urbanowicz Prepared for NC Climate Fellows Workshop June 21, 2011.
May 16-18, 2005MultTemp 2005, Biloxi, MS1 Monitoring Change Through Hierarchical Segmentation of Remotely Sensed Image Data James C. Tilton Mail Code 606*
1 Applications of Remote Sensing: SeaWiFS and MODIS Ocean Color Outline  Physical principles behind the remote sensing of ocean color parameters  Satellite.
MODIS Workshop An Introduction to NASA’s Earth Observing System (EOS), Terra, and the MODIS Instrument Michele Thornton
Remote Sensing. Vulnerability is the degree to which a system is susceptible to, or unable to cope with, adverse effects of climate change, including.
Satellite Imagery and Remote Sensing DeeDee Whitaker SW Guilford High EES & Chemistry
Remote Sensing of Evapotranspiration with MODIS
Terra Launched December 18, 1999
EG2234: Earth Observation Interactions - Land Dr Mark Cresswell.
NASA Earth Observing System Visualization Tools ARSET - AQ Applied Remote SEnsing Training – Air Quality A project of NASA Applied Sciences Introduction.
Environmental Remote Sensing GEOG 2021 Lecture 8 Observing platforms & systems and revision.
Multimission platform and Brazilian EO satellites Gilberto Câmara INPE
Uncertainties in Wildfire Emission Estimates Workshop on Regional Emissions & Air Quality Modeling July 30, 2008 Shawn Urbanski, Wei Min Hao, Bryce Nordgren.
Satellites Storm “Since the early 1960s, virtually all areas of the atmospheric sciences have been revolutionized by the development and application of.
Geosynchronous Orbit A satellite in geosynchronous orbit circles the earth once each day. The time it takes for a satellite to orbit the earth is called.
Data acquisition From satellites with the MODIS instrument.
USDA Forest Service, Remote Sensing Applications Center, FSWeb: WWW: National Geospatial Fire.
References: 1)Ganguly, S., Samanta, A., Schull, M. A., Shabanov, N. V., Milesi, C., Nemani, R. R., Knyazikhin, Y., and Myneni, R. B., Generating vegetation.
Landsat Satellite Data. 1 LSOS (1-ha) 9 Intensive Study Areas (1km x 1km) 3 Meso-cell Study Areas (25km x 25km) 1 Small Regional Study Area (1.5 o x 2.5.
Earth Observation Data as Public Goods: INPE’s experience Leila Fonseca National Institute for Space Research Brazil.
Satellite Imagery and Remote Sensing DeeDee Whitaker SW Guilford High EES & Chemistry
Satellite based Sensors for Agricultural Applications
Global Forest Change 2000 – 2012 Classification of Landsat from two different years
Environmental and Disaster Monitoring Small Satellite Constellation
Hyperspectral Sensing – Imaging Spectroscopy
NASA Aqua.
AIRS (Atmospheric Infrared Sounder) Instrument Characteristics
Digital Numbers The Remote Sensing world calls cell values are also called a digital number or DN. In most of the imagery we work with the DN represents.
Potential Landsat Contributions
Satellite Sensors – Historical Perspectives
NASA alert as Russian and US satellites crash in space
MODIS L1B Data Product Uncertainty Index Jack Xiong (Xiaoxiong
Planning a Remote Sensing Project
Presentation transcript:

MODIS: Moderate-resolution Imaging Spectroradiometer National-Scale Remote Sensing Imagery for Natural Resource Applications Mark Finco Remote Sensing Applications Center Salt Lake City, UT (801)

Briefing Overview Objectives & Deliverables Brief Technical Description of MODIS Selected Applications  Fire Information Support  Rangeland Monitoring  Land Cover Change Estimated % Canopy Cover

ObjectivesObjectives Utilize new remote sensing system to provide quick response imagery and geospatial resource information to support : Utilize new remote sensing system to provide quick response imagery and geospatial resource information to support :  National-scale reporting and mapping (e.g., burn areas/severity)  Effectiveness monitoring of watershed restoration and rehabilitation work  National scale strategic planning – restoration prioritization and asset allocation  Regional and forest scale analysis where vegetation and landcover change information is required

Actions and Deliverables Establish MODIS satellite downlink and data processing capability at RSAC – GSTC Provide MODIS imagery and GIS data to field offices via Geospatial Data Clearinghouse Continue development of MODIS image processing algorithms in cooperation with NASA, universities and Forest Service geospatial data users Provide training and technical support

MODIS (MODerate-resolution Imaging Spectroradiometer)

MODIS utilizes latest technology, sensor specifically designed for vegetation, landcover and burn area mapping MODIS images 2,300 km swath in single pass Single MODIS satellite images same location on the ground every two days Two MODIS satellites will be operational early 2001 – second system will provide daily coverage MODIS Characteristics

MODIS Orbital Characteristics Terra Platform – EOS AM1 Aqua Platform – EOS PM1 705 km, Near-polar, Sun Synchronous ~2300 km Swath Width 1 to 2 day revisit

MODIS Sensor Characteristics Red / 250-meters 5 Visible to Mid-IR 500-meters 29 Visible to Thermal 1-km Narrow Spectral Width High Dynamic Range (12-bit) Multiple Thermal Bands Sophisticated Onboard Calibration Spectral Property Summary Comparison of Landsat 7 and MODIS Bands 1-7

Summary: MODIS / Landsat Comparison MODISLandsat 7 Revisit Period1-day16-day Observations per Visit2 day time / 2 night time1 daytime Swath Width~2300 km~185 km Spatial Resolution250 / 500 / 1000 meters30 / 15 meters Number of Spectral Bands36 Total8 Total Dynamic Range12-bit (4096)8-bit (256) Observation to Application Latency ~12 hours2 - 3 weeks MODIS : Unique Niche in Earth Observing Systems & Opens the Door to New Natural Resource Applications

Comparison of MODIS & AVHRR

MODIS Direct Readout Facilitates applications that require near real- time imagery Wider use of data Moderate cost solution

Proposed USDA Forest MODIS Applications Network 3.1-meter X-band Antenna Terra (Aqua) Spacecraft GPS Timing System Level 0 Processing Antenna Control and Programming Tunable X-band Down Converter Demodulation and Frame Synchronization Assembly of Level 0 product Level 1b Processing Level 0 Reformatting Geolocation using Ephemeris and Attitude Calibration to top-of- atmosphere radiance Direct Broadcast Workstation RAID Automated Tape Backup Level 2 & 3 Processing (RSAC) Existing MODLand Products MOD09 - MOD13 MOD14 Algorithm Development Burned Severity / Intensity Watershed Assessment Support Strategic Fire Management Support Level 2 & 3 Processing (FiSL) Algorithm Development Enhanced Active Fire Smoke Dispersion Algorithm Development Burned Severity LANDFIRE Support? Ethernet LAN Broadband Virtual Network Connection (< 60 min. lag) RSAC Image Processing Workstation FiSL Image Processing Workstation

MODIS fire mapping Montana Fires August 23, 2000

MODIS fire mapping Montana & Idaho Fires September 26, 2000

MODIS fire mapping

MODIS Support for Forest Inventory and Analysis (FIA) Nationwide Forest Cover Maps Nationwide Change Detection for Sample Stratification

MODIS Support for Rangeland Management Monitor daily rangeland changes:  Improves forage production estimates  Improves rangeland cover mapping capabilities Identify annual trends in rangeland production:  Develop guidelines for sustainable range management 1 year sequence of “greeness” images

MODIS Vegetative Cover Conversion Alarm for where rapid land cover conversion Multiple change detection algorithms 250-meter Spatial Resolution

Annual Landcover Map MODIS-Derived 1-km Spatial Resolution IGBM Classification Prototype of Annual Land Cover Map

Vegetation Continuous Fields (VCF) – Tree Cover

VCF – North West CONUS Treecover

VCF – Idaho Tree Cover