This chapter describes how to set a scale and measure distances and areas on satellite images. Using ImageJ, a freely available image analysis program that runs on most operating systems, users set the spatial calibration of an image, then select... (View More) and measure distances and areas on it. The measurement results are reported in real-world units. The technique is most useful and accurate for nadir view (straight down) images. In this chapter, users examine satellite images of the Aral Sea, which has shrunk dramatically since 1960 because the rivers that flow into it have been tapped for irrigation. Users access satellite images of the region, then set a scale and measure the width of the sea each year. On another set of images, they highlight areas that represent water and measure them to see how these areas of the sea changed. This chapter is part of the Earth Exploration Toolbook, which provides teachers and/or students with direct practice for using scientific tools to analyze Earth science data. Students should begin on the Case Study page. (View Less)

This chapter walks users through a technique for documenting change in before-and-after sets of satellite images. The technique can be used for any set of time-series images that are spatially registered to show the exact same area at the same... (View More) scale. In the chapter, users examine three Landsat images of the Pearl River delta in southeastern China. In these images, users observe changes in land use, then identify and outline areas of new land that were created by dredging sediments from the river bottom. The final product is an annotated image that highlights new land and indicates when it was created. The chapter is part of the Earth Exploration Toolbook, which provides teachers and/or students with direct practice for using scientific tools to analyze Earth science data. Students should begin on the Case Study page. (View Less)

In this activity, users download and graph modeled climate data to explore variability in climate change. Most people know that climate changes are predicted over the next hundred years, but they may not be aware that these changes are likely to... (View More) vary from region to region. Using data from the University of New Hampshire's EOS-WEBSTER, a digital library of Earth Science data, users will obtain annual predictions for minimum temperature, maximum temperature, precipitation, and solar radiation for each of these 5 states: New York, Georgia, Colorado, Minnesota, and California. Data will span the years 2000 through 2100. Users will import the data into Excel and analyze it to see what, if any, regional variability exists. Finally, they will download data for their own state, compare these results with the results from the other 5 states and use their results to answer questions related to climate change. This chapter is part of the Earth Exploration Toolbook (EET). Each EET chapter provides teachers and/or students with direct practice for using scientific tools to analyze Earth science data. Students should begin on the Case Study page. (View Less)