Introduction to Remote Sensing of the Environment Bot/Geog 4111/5111 Ken Driese Dept. of Botany

Group Activity: Solving Remote Sensing Problems Your group must speculate about how to accomplish one of the following using remote sensing! You must use only your brains! You cannot use the internet or other resources. How could you assess the effect of drought on plant biomass in California? How could you map sage grouse habitat in Wyoming? How could you measure ground deformation in Yellowstone that might signal an eruption of the feared supervolcano? How could you use remote sensing to gather intelligence about whether the recent election in Venezuela was legitimate? How could you find your own private hot spring deep in the wilderness?

Course Scope Electromagnetic radiation Emphasis on satellite remote sensing Emphasis on land management applications – particularly vegetation mapping and monitoring Introduction to specialized types of remote sensing Hands-on skills: image processing and analysis

Types of Remote Sensing -- Sensors Aerial Photography Film, Digital, Aerial, Orbiting Multispectral Imaging Hyperspectral Imaging Active Remote Sensing Thermal Imaging

Types of Remote Sensing – Applications Terrestrial Marine Atmospheric Planetary Astronomy

The History of Remote Sensing Historical context is important for understanding the present and predicting the future.

The Electromagnetic Spectrum

Reflectance

Identifying Materials: Spectral Differences

Digital Data vs. “Pictures” Satellite data are numbers that represent the strength of reflected light hitting the sensor, just like your digital camera Satellite “pictures” are visualizations of these data

Satellite Basics What so satellites measure? What is satellite resolution? How do orbital characteristics affect data collection? How do satellites gather data?

Survey of Commonly Used Satellites Landsat Hyperion Ikonos/Quickbird AVHRR MODIS IRS SPOT etc. From www.nasa.gov

High spatial resolution (E.G., Worldview, Quickbird Aerial Photograph Grand Prismatic Pool, Yellowstone Google Earth

Lower spatial resolution (e.g., MODIS)

Atmospheric Corrections

Geometric Corrections

Image Enhancement – Spectral Indices What do these images show you?

Aerial Photography

Image Classification (Making Maps) What does MMU mean? What is “land cover”?

Accuracy Assessment Corn User’s Accuracy = 25/32

Change Detection 2003 1989 Also see THIS SITE

Using GIS to Improve Maps

Hyperspectral Imaging – “hyper” amounts of spectral data black - blue - green - yellow - red (brightest) Area on right side, where red occurs in NIR is probably areas of dense vegetation. bright areas in MIR are different minerals

Thermal Remote Sensing Death Valley thermal image with north to right

Radar and Lidar

Global Change