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EOS-WEBSTER has partnered with several other organizations to develop Earth science data products for use in middle and high school to college level courses. We are also creating data products (such as MPEG movies) from our existing data collections that can be used in a classroom environment.

Highlighting some of our educational products and services:

Would you like to give your students a visual illustration of how climate has changed in the United States in the last century and how it may change in the future?

We now offer time series animations of climatological variables for the years 1895 through 2100. These MPEG movies were created from the model output results of two of the most frequently cited climate simulation models developed by the Canadian Center for Climate Modelling and the Hadley Center for Climate Prediction and Research.

Each movie is approximately 9.0 megabytes in size and may take a long time to load, please be patient.

Net Primary Production:

What about viewing global landuse change over the past 300 years? These movies are decadal snapshots from the period 1700 to 2000 developed from the Global Landuse Model (GLM), which has input from several model sources, as detailed in the GLM dataguide. Some areas have moved from forested to agriculture to urban, and others have moved from forested to harvested trees and then regrown a forest (secondary landuse) in the past 300 years. All movies are global at one degree resolution (*). They can be downloaded using the right-hand mouse click on the movie link, or run directy in your browser by left-hand click. Try a smaller movie first if your system is older.

(*) a 1 degree by 1 degree pixel in latitude-longitude measure is of variable area. One of the datasets you can get from this GLM collection is pixel area. By multiplying this area by the fraction value from the actual data, you would be able to estimate the land area.

These are static jpeg images (thumbnail and full size images) of the model output results noted above.

Climate Variables:

Net Primary Production:

EOS-WEBSTER is a founding partner in the Earth Exploration Toolbook. The Earth Exploration Toolbook (EET) is a collection of case studies or chapters in which the user obtains data and uses specific analytical tools to learn more about issues or concepts in Earth science. Screen shots are provided to assist those who may be less familiar with the software or other analytical tool that is used in the chapter. Each chapter also includes a detailed list of what is needed (typically software) to complete the chapter and any associated costs. The chapter also identifies which National Science Education Inquiry and Content Standards are addressed in the case study and concludes with suggestions for other applications of the data and areas for further exploration.

Each chapter in the EET is external reviewed by a panel of educators and is also field tested before it's released publicly. Five chapters are currently on-line:

Exploring Regional Differences in Climate Change
Access data from EOS-WEBSTER and produce graphs in a spreadsheet application comparing climate change among states in the U.S through the year 2100. Analyze the graph to interpret regional trends in climate change.

Analyzing the Antarctic Ozone Hole
Download images from the Total Ozone Mapping Spectrometer (TOMS) instrument and use image processing software to measure the area of the ozone hole over time. Import measurements into a spreadsheet application to produce a graph.

Analyzing Populations with Maps
Use the United States-Mexico Demographic Data Viewer to generate a series of maps. Analyze the maps to compare how people live in different urban and rural settings.

Annotating Change in Satellite Images
Use image processing software, ImageJ, and Landsat images to produce a map documenting change over time. Document how human activities have changed a river delta.

Analyzing Wetlands
Access data on wetlands around the world and perform a series of searches to identify wetland areas that might benefit from protection.

Investigating the Streamflow-Precipitation Relationship
Request specific datasets from the USGS and the National Climatic Data Center (NCDC), and use a spreadsheet application to produce a graph comparing them. Analyze the graph to interpret conditions that affect streamflow.

Investigating Earthquakes: GIS Mapping and Analysis
Download lists of recent and historical earthquakes from USGS, then use a spreadsheet application to prepare the data. Import the data into ArcVoyager, a freely available Geographic Information System (GIS). Use the GIS to analyze the data and predict where the next big earthquake will occur.

Looking into Earth with GIS
Examine seismic wave model data in ArcVoyager, a freely available Geographic Information System (GIS). Use the GIS to examine variations in seismic wave velocities and infer the depth of the crust-mantle boundary beneath ocean basins and North America.

Measuring Distance and Area in Satellite Images
Download and examine MODIS (Moderate Resolution Imaging Spectroradiometer) images of the Aral Sea from 1973 through 2003. Use image analysis software to quantify change in the width and area of the sea over time.

Using GLOBE Data to Investigate the Earth System
Access and graph environmental data that has been collected by students who participate in the GLOBE (GLobal Observations to Better the Environment) Program. Use GLOBE's graphing tool to compare several variables, and interpret the graph to examine evidence of Earth system processes.

When is Dinner Served? Predicting the Spring Phytoplankton Bloom in the Gulf of Maine

Photos: D. Townsend

Phytoplankton are the microscopic plants that form the basis of the marine food chain that sustains almost all life in the ocean. Phytoplankton also produce half of all the oxygen we breathe. In this chapter, students will gain a better understanding of the critical role phytoplankton play in the marine food web by predicting the timing of the spring phytoplankton bloom in the Gulf of Maine. Students will obtain data on the variables that influence the spring phytoplankton bloom from buoy monitoring stations in the region. Students will graph these data and from these graphs make a prediction as to when the phytoplankton bloom should occur. They will then obtain MODIS satellite images of the Gulf of Maine to see when the bloom actually occurred and compare their estimate to observation for that year.

EOS-WEBSTER has also partnered with the Forest Watch Program here at UNH to provide teachers and students with an easily accessible collection of Landsat data. These Landsat 7 ETM+ and Landsat 5 data have been subsetted by city or town and several hundred multispectral, panchromatic, and thermal images are now available. You can view thumbnail images of the cities in this collection by selecting "Educational Image Subsets" from our Collections list. (Click the "Apply Filter" button to make this selection and then use the "Next" button to view the list of Landsat holdings).

Image Analysis and Visualization Software:

There are a number of free software programs for image processing and visualization of image data. Three commonly used applications are MultiSpec, ImageJ, and Freelook.

In addition, there are numerous tools for manipulating or displaying NetCDF data as well as HDF-EOS data (see the
"Visualization Applications" section of the HDF-EOS page). For definitions of these two image output formats please see our Output Formats page.

Additional Data Resources for Teachers:

	The National Science Digital Library
	The Digital Library for Earth Science Education

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