IGARSS 2009 SC-4:MODIS Direct Broadcast Data For Enhanced Forecasting And Real-Time Environmental Decision Making
Day 1 Syllabus: Liam Gumley
Lecture Session
Review of Radiative Transfer Principles (Allen Huang)
Introduction to Terra and Aqua
Introduction to the MODIS instrument
What is Direct Broadcast?
- Overview of direct Broadcast Products
Level 1B MODIS products (1KM, HKM, QKM)
- What is Bowtie? How do i remove it?
Atmosphere DB Products
- What is IMAPP?
- Cloud Mask
- Atmospheric Profiles
- Cloud Top Profiles
- Aerosol Products
- Water vapor Products
Land DB Products
- What is DRL
- Active Fires
- Corrected Reflectance
- NDVI
- EVI
- Land Surface Temperatures
- Land Surface Reflectance
Ocean DB Products
- What is SeaDAS?
- Water leaving Radiance
- Sea Surface Temperature
- Chlorophyll Concentration
Image Products
- True Color Images
- Google Earth Images
How do I create DB products?
- What is Direct Broadcast Virtual Machine?
- How do I install and run DBVM?
How do I read the product files
- What is HDF4?
- What software is avaliable?
- What can the software do?
How can I get products from NASA>
- What is LAADS?
- How do I order products from LAADS?
Lab Session
- Introduction to Hydra
- Exploring MODIS Level 1B data in Hydra
- Exploring MODIS Cloud Mask in Hydra
- Exploring MODIS Water Vapor Product in Hydra or Freelook
- Exploring MODIS Active Fire and NDVI Product in Hydra or Freelook
- Exploring MODIS SST and Chlorophyll Product in Hydra or Freelook
- Exploring MODIS true color and other products in Google Earth
Day Two Syllabus:Kathleen Strabala MODIS Applications 8 July 2009
Lecture Sesssion
Introduction to Meteorology - Jordan Gerth
Weather Observation and Forecasting
- Complimentary to Geostationary
- Improved spatial resolution
- Improved spectral resolution
- Unique prducts
- Fog detection
- Snow/ice detection
- Fire detection
- Severe weather
- Cloud height, cloud composition, cloud temperature
- Turbulence
- Ash detection
- Numerical Weather Prediction (NWP) DBCRAS applications
- Direct Broadcast CIMSS Regional Assimilation System (DBCRAS) NWP
- Freely distributed, globally configurable 72 hour
forecasts of meteorological fields centered on user supplied lat/lon
- Improved depiction of cloud and moisture using MODIS products in assimilation
- Unique forecast satellite imagery
Air Quality
- Aerosol detection
- IDEA - Infusing satellite Data into Environmental Applications
Others
- Use of sun glint patterns
- Land Surface Temperatures case study of infestation
Lab Session
- Fog detection case study using HYDRA and Google Earth
- Investigation of Strong Thunderstorms using HYDRA
- Estimating MODIS Aerosol Optical Depth using HYDRA
- Using MODIS to determine cloud phase, atmospheric turbulence and discrimination of snow and ice using HYRDA
- DBCRAS investigation of deep low pressure system using McIDAS-V
Day Three Sylabus:Philip Frost, Karen Steenkamp and Willem Marais
Remote Sensing and Fire 9 July 2009
Lecture Session
Lecture 1: Philip Frost
The role of Remote Sensing in Wildlife Management
- Impact of National Disasters Worldwide
- Wildlife Management and information needs
- Remote Sensing basics
- Remote sensing fire products
- Future fire satellites
- Kruger Park fire disaster
- Botswana Fire Information System
Lecture 2: Philip Frost
Fire Danger Estimation
- Background on Fire Danger modeling
- FDI basics
- Current FDI models
Lecture 3: Karen Steenkamp
Plant phenology and fuel biomass
- Basics of plant phenology
- Long term vegetation datasets
- Role of remote sensing in mapping plant condition
- Relationship between fuel load and fire
- Mapping vegetation fire risk
Lecture 4: Willem Marias
MODIS Burned Area Products
- History of burned area products
- Burned area mapping
- Description of official MODIS BA product
- Description of Lewis Giglio product
Lab Session
- Students will compare the 7 MODIS refelctance bands in relation to each bands
ability to characterize active fire, burned area and smoke plumes
- Students will have the opportunity to manually map a large forest fire
from high resolution Spot data. Their product will then be compared to two automated
MODIS burned area products
- If time remains students will have the opportunity to learn
more about the AFIS viewer and how to use it
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