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UPDATED: 08/28/07 by RL 08/24/07 by RL/MJA (added MJ’s part 1 and glossary) 08/07/07 by RL 07/20/07 by RL 07/09/07 by MJA 06/28/07 by MJA 06/15/07 by RL

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EET Chapter Description A general description of what the user will DO to produce the result advertised in the chapter title. Use active voice to describe the general sequence of procedures within the context of the chapter. Each description should include the following points.  start with a broad description that shows the major goal of the chapter, mentioning type of tool and general data description.  describe the general procedures  describe the intellectual activity (analysis, synthesis, evaluation) that user will engage in at end of technological manipulations.  you may want to include a representative graphic from the chapter to add visual interest to the description.

08/20/07 11:00 am

Introduction to NEO


The Earth's atmosphere is a complex, dynamic system - it is constantly changing. Indeed, it always has changed, and it always will.

The question today is - how is it changing, and what factors and events are driving these many changes? [image 10312 right border caption] [small][hidden 'credits'] The Next Generation Blue Marble True Color image of the Earth acquired using NASA's MODIS sensor onboard the Terra satellite. [end small] [end hidden][end caption]

In this chapter, students will learn to use NEO to examine several highly dynamic components of the Earth's atmosphere. NEO is NASA's Earth Observation web-based tool designed to help students picture, explore, and analyze patterns of environmental change using satellite images. NEO combines a user-friendly but powerful set of exploratory and analytical tools with a wide range of remotely sensed Earth system science data, allowing students and teachers to investigate Earth system components of atmosphere, oceans, land, life, and energy.

Students will learn how to select, evaluate, and explore a wide range of satellite images, all in the context of a case study of the origins of atmospheric carbon monoxide, a harmful gaseous pollutant, and aerosols, tiny solid airborne particles such as smoke from forest fires, and dust from desert wind storms. They will learn how to display, graph, analyze, and evaluate variation, and more powerfully, covariation, in carbon monoxide and aerosols covering various areas of interest, anywhere on Earth. In this way, students can see how carbon monoxide and particulates, two important and highly dynamic atmospheric constituents, change in density and distribution from month to month. In addition, they will learn how to investigate potential sources of these two important atmospheric pollutants, ultimately attributing a possible cause to the patterns they discover.

By exploring and analyzing these two related data sets in the NEO ICE tool, students will not only learn how to investigate patterns of atmospheric pollution, but will also learn how to use NEO to investigate and analyze other dynamic patterns of change in the complex system that we call Planet Earth. Indeed, this chapter is designed not only to introduce students to the Earth's beautiful and exciting atmosphere, but also as an introductory tutorial to NEO, NASA's incredibly powerful and unique Earth system science exploration tool.

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Teaching Notes Page

EET Grade Level

Upper elementary (5-6) Middle school (7-8) High school (9-10, with further investigations appropriate for 11 and 12 general science)

EET Learning Goals

A list of goals related to data manipulation, analysis techniques, content of the case study, and/or concepts in Earth system science. Describe each goal in a bulleted statement that begins with an action verb. Text entered in this field will be prefaced by the phrase "After completing this chapter, users will be able to:"

After completing this chapter, users will be able to:

 Use NEO to display Earth system satellite data.  Use NEO to explore geographic and time-series patterns in a single image  Use NEO to explore, graph, and analyze changes (spatial and temporal covariation) in two satellite images (more accurately described as ‘within a single data set, and between data sets’ – how to say this at the 6-10th grade level?)  Describe the relationships between atmospheric carbon dioxide and aerosol concentrations  Investigate the possible sources of CO and aerosols EET Rationale A description of why an educator would want their students to learn this technique. For instance, what else could students do with it? Include examples of how the technique or data might be used within Earth systems curricula.

This chapter provides a computer-based activity to supplement and reinforce classroom and laboratory study of the Earth's atmosphere. With a basic background in the physical and chemical composition and structure of the atmosphere, students will begin to explore an example of atmosphere change, as well as what drives the change, and the possible results of the change. They will learn to identify and analyze patterns in space and time, using these as clues to identify sourcers of atmospheric pollutants. In addition, they will begin to understand that even trace gases like carbon monoxide can have an effect on how the Earth system functions.

By exploring and analyzing these patterns in NEO, students will gain the ability and confidence to initiate their own inquiry into the exciting rhealm of NASA remotely sensed Earth system data. Ultimately both students and teachers will be able to use NEO in a wide range of Earth system, ecological, and even social-geographic studies of our ever changing planet.

EET Background information: Any detailed information that educators might need to feel comfortable presenting the content or techniques of the chapter to students. Explain the general principles of the science involved with collecting or generating the data, or include external links to "fact sheets" or other pages that provide this information. Clarify the scope of the chapter here, specifically indicating any concepts related to the topic that are not covered.

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Earth Science, general science, geography (advanced), mathematics (graphing, plotting, analyzing data sets), environmental science

EET Science Standards

RL- UP TO HERE 5/30 5:30 P.M. (WHAT A COINCIDENCE)

A list of the Science Education Standards supported by the chapter. Click the link for the appropriate grade level range below, and identify all standards addressed by your chapter. Check standards in the Abilities of Science Inquiry (ASI) section at the top as well as within the specific science content areas that appear below them. Copy and paste the text (including the code number that precedes each one) of each standard addressed by your chapter into this field. Your list will be prefaced by the phrase "The following National Science Education Standards are supported by this chapter:"

K-4 http://pals.sri.com/standards/nsesK-4text.html 5-8 http://pals.sri.com/pals/standards/nses5-8text.html 9-12 http://pals.sri.com/pals/standards/nses9-12text.html

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Case Study Page

Case Study Text The goal of the Case Study page is to present a compelling story line that gives users a reason for learning the chapter techniques; it should make the goal of the chapter obvious. The Case Study might "hook" end users with a question, an interesting image or map, or an external link. The case study should draw the user into "caring" about the content or motivate them to learn the chapter technique on the promise of future usefulness.

Case Study: Identifying the Source of Atmospheric Pollution 07/20 RL

Satellite images allow us to survey and monitor the Earth from space, providing new and powerful insights into many of the physical and biological phenomena that, when considered together, shape conditions for life on our planet. Satellite images show land surface features such as deserts, forests, and development, ocean properties such as temperature and chlorophyll concentrations, and meteorological patterns such as hurricanes and typhoons, frontal systems, dust storms, and areas of calm, stable weather. In addition to weather patterns, some satellite sensors have been designed to image specific components of the atmosphere, such as aerosol particles and the concentration of certain gases such as carbon monoxide and ozone.

[image 10119 right border caption] [small][hidden 'credits'] NASA NEO, Global Carbon Monoxide concentrations acquired using the MODIS sensor, March 2007. [end small][end hidden][end caption]

As we have already seen, the atmosphere is a dynamic and complex component of the Earth system, and is continuously changing in composition and structure. But what drives these changes, and why should we care? After all, humans have evolved, and indeed thrived, in this unpredictable and highly dynamic environment. We should care because human activity is changing various components of the atmosphere at rates that, as far as the current scientific evidence suggests, are out of the historic range of variability. From what we have learned recently, in part from our observations of the Earth from space, the atmosphere appears to be changing more rapidly at present than in any other time in human history.

[image 10120 left border caption] [small][hidden 'credits'] NASA NEO, Global Aerosol Optical Thickness concentrations acquired using the MODIS sensor, March 2007. [end small][end hidden][end caption]

In this study, we will explore the spatial and temporal patterns of aerosols and carbon monoxide, and study the interactions between these two important atmospheric components. By exploring the covariation between carbon monoxide and aerosols in Earth's atmosphere, it will be possible to deduce their sources and better understand how these two significant gases influence our changing planet.

Page Name A brief title that will appear at the top of the page which describes the setting or context within which the chapter technique is presented. The title you enter should be prefaced by the words "Case Study:"

Step 1 Step-by-Step Instructions Page

Introductory Text Use this field only if you have important information that the user must have before they begin the activity.

Part 1 Name Part 1— Learn to use NASA Earth Observations (NEO)

Part 1 Description (note: not sure where this information gets displayed)

  • Introduce the NEO interface using Blue Marble Data.
  • Learn to use the primary visualization tools to explore Aerosol Optical Thickness.
  • Compare/contrast spatial and temporal resolution.
  • Identify sources of aerosols in the atmosphere: Fires, dust, pollution.
Repeat Part Name and Part Description for up to 6 Parts Part 1 Page

Step 1 Name Opening NEO web site

Step 1 Description

In a web browser, open the NASA Earth Observations (NEO) home page: [link http://neo.sci.gsfc.nasa.gov 'http://neo.sci.gsfc.nasa.gov' new].

Step 2 Name Exploring the Blue Marble Data

Step 2 Description

Begin by using the Blue Marble image, the default map already displayed at the top of this page, to learn about the basic navigation tools (widgets) available in NEO. This NASA Blue Marble image shows Earth in true color, according to the human eye.

To help view this image, there are tools to zoom in and out, pan (move) around the image, and return the image to the original view.

[hidden 'me how']

Click on the ? to view a Map Widget Help box. (Click the X in the upper right-hand corner to close the Widget Help box.)

[image 9896 center border]

Use the + to zoom in as much as possible.

[image 9897 center border]

Use the hand to pan (move) around.
When you are done, you can use the or the = to zoom back out to the full image.

[end hidden]

Use the zoom and pan tools to find where you live.

  • What is the resolution of the imagery?
  • Can you see your school, a near-by lake, or other features you know?

This limitation is known as [link glossary.html#SpatialResolution 'Spatial Resolution' new] and each dot or pixel is approximately 11 km (at the equator).

Step 3 Name Accessing Aerosol Optical Thickness Data

Step 3 Description

To access the Aerosol Optical Thickness images, first, click on the Atmosphere tab. Then, click on the Aerosol Optical Thickness (MODIS) data set. Click on View to ensure the data set is open. This is the Aerosol Optical Thickness (1 month - Terra/MODIS) dataset.

[hidden 'me how']

Click on the Atmosphere tab.

[image 9917 center border]

Click on the Aerosol Optical Thickness (MODIS) data set.

[image 9918 center border]

Click on View to ensure the data set is open.

[image 9919 center border] [end hidden]

[pullquote]Notice that below the Aerosol Optical Thickness image, there is a legend that explains the false-colors applied to the map. The colors range from blue to deep red/brown, with dark grey/black representing areas where no measurements were taken. [end pullquote]

  • Where do you see maximum values?
  • Where do you see minimum values?
  • What do you know about those areas?
  • Why do you think these areas have high or low values?

Step 4 Name Learning about Aerosol Optical Thickness Data

Step 4 Description

To learn more about the Aerosol Optical Thickness dataset, click on About this dataset.

[pullquote]Note that there are three levels of information about the dataset that can be shown, with the Basic Description as default. Toggle between the less and more detailed descriptions using the Less Detail | More Detail links.[end pullquote] [hidden 'me how']

Click on the About this dataset link.

[image 9920 center border]

Read the description of the Aerosol Optical Thickness dataset. Use the Less Detail | More Detail links to toggle between less complex and more complex explanations.

[image 9921 center border] [end hidden]

  • What are aerosols? What are they composed of?
  • What are the major sources of aerosols?
  • Are aerosols evenly distributed throughout the atmosphere? If not, why not?
  • Why is it important for scientists and policy makers to understand the role of particulates in the atmosphere?
  • What NASA instrument (sensor) gathers information on aerosols? What does the sensor measure in the atmosphere to determine the amount of aerosols?

Close the window when done.

Step 5 Name Observing Aerosol Optical Thickness over Time

Step 5 Description

Learn more about the coverage of the Aerosol Optical Thickness dataset by scrolling to the bottom of the page and browsing through the available search results, using the Next link. The different results show the Aerosol Optical Thickness dataset at different times.

[hidden 'me how']

Scroll to the bottom of the NEO page, and determine how many images are available.

[image 9924 center border]

Click Next to see the other available data.

[end hidden]

  • What is the range of dates available on the NEO web site?

Each map represents a "composite" satellite image used to create a "monthly average" dataset. What does this mean? When a satellite passes over the Earth, it can't take a picture of the whole thing at one time. It can only take measurements of what is beneath it at any given time. For example, the satellite might measure New York today and Paris tomorrow. Scientists collect all the individual measurements of all the different parts of the world into one "composite" image, so that we can study the whole Earth at once. In this case, the measurements are taken from one month's worth of data to make the map. If aerosols above New York were measured three times during that month, the three values are averaged for the monthly composite image.

How frequently/often measurements are taken from a certain area, how many measurements are taken in total, and over what time period a dataset exists help define the [link glossary.html#TemporalResolution 'Temporal Resolution' new] of the dataset.

  • What do you think the maps would look like if they weren't composite images?
  • How might a map of a weekly or daily average look different than a map a monthly average?

Click on a few datasets from different times of the year. Click on View to refresh the map at the top of the page.

  • When do you see maximum values?
  • When do you see minimum values?
  • Does your answer depend on where you looking? Why might one area have its maximum aerosol values in the spring, while another has its maximum aerosol values in the fall?

Step 6 Name Interpreting an Aerosol Optical Thickness Dataset

Step 6 Description

Using the Next or Prev link at the bottom of the results list, find the Aerosol Optical Thickness dataset for September 1, 2005 00:00 to October 1, 2005 00:00

If the September 1, 2005 00:00 to October 1, 2005 00:00 listing is "closed," click the + sign alongside it. Then click View to open this dataset in the image window above.

  • Where do you see maximum values?
  • In central South America, what do you think the source of atmospheric particulates is? (smoke, pollution, dust, etc.)
  • What other datasets would help support your hypothesis about the source of particulates?

[pullquote]

Note that these articles may help you answer the questions above:

[link http://earthobservatory.nasa.gov/NaturalHazards/natural_hazards_v2.php3? img_id=13150 'From Earth Observatory, on fires in South America' new]
[link http://earthobservatory.nasa.gov/NaturalHazards/Archive/natural_hazards_archive. php3?page=13&topic=dust 'From Earth Observatory, on dust and smoke events for August, September and October 2005' new] [end pullquote]

Step 7 Name Saving an Image for Future Reference

Step 7 Description

Download this image for later analysis or use in a report using the Download Options box, on the right side of the NEO screen. Use the following recommended settings:
Full resolution, Color image, JPEG format

Click the Get Image button.

[hidden 'me how']

To the right of the image, find the Download Options box.

[image 9925 center border]

Choose Full, Color, and JPEG from the drop-down menus. Then, click the Get Image button.

[end hidden]

The image will load in a separate window, where you can save the image.

  • On a Windows machine, right-click the image to save it. Select Save image as... or Save Picture As... to save the image. Change the image's name, if preferred.
  • On a Macintosh machine, right-click (or control+click) the image to save it. Select Save Image to Desktop to save the image.

Images Used in Part 1: 9896 -- Blue Marble image on NEO site with Map Widget Help box open 9897 -- Blue Marble image on NEO site zoomed in to North America 9917 -- Image of Atmosphere tab on the NEO site 9918 -- Image of Aerosol Optical Thickness link on the NEO site 9919 -- Image of Aerosol Optical Thickness map and View link on NEO site 9920 -- Image of About this dataset link for Aerosol Optical Thickness 9921 -- Image of About this dataset page for Aerosol Optical Thickness 9924 -- Image of total number of Aerosol Optical Thickness datasets available 9925 -- Image of Download Options box on NEO site

Within each step, describe which menu items, buttons, and/or dialog boxes the user should interact with and how, including brief comments about what the main actions accomplish, as appropriate. Integrate the chapter’s Earth system science content with these instructions, to inform users what their technology interactions have to do with phenomena in the real world. Use context tags to focus the user on content-related mental interaction with the graphical information.

Repeat Step Name and Step Description for up to 9 Steps

Step 3 Step-by-Step Instructions Page

Within each step, describe which menu items, buttons, and/or dialog boxes the user should interact with and how, including brief comments about what the main actions accomplish, as appropriate. Integrate the chapter’s Earth system science content with these instructions, to inform users what their technology interactions have to do with phenomena in the real world. Use context tags to focus the user on content-related mental interaction with the graphical information. Introductory Text Use this field only if you have important information that the user must have before they begin the activity.

Part 1 Name

Part 1 Description

Glossary

Step 1 Description

[anchor 'SpatialResolution']Spatial resolution -

Resolution is the ability of a sensor to distinguish two closely spaced objects or lines as two rather than one object or line. Alternately, it is the smallest object or narrowest line a sensor can detect. ([link http://ccrs.nrcan.gc.ca/glossary/index_e.php?id=3000 'Canada Centre for Remote Sensing' new])

Additional resources:
[link http://maic.jmu.edu/sic/rs/resolution.htm 'Spatial Information Clearinghouse' new]
[link http://www.crisp.nus.edu.sg/~research/tutorial/image.htm 'Centre for Remote Imaging, Sensing & Processing' new]
[link http://mynasadata.larc.nasa.gov/glossary.php?&letter=S 'My NASA Data' new]

[anchor 'TemporalResolution']Temporal Resolution -

Indicates the time increment of a data set, or the frequency at which data was measured. ([link http://mynasadata.larc.nasa.gov/glossary.php?&letter=T 'My NASA Data' new])

Additional resources:
[link http://maic.jmu.edu/sic/glossary.htm#TemporalResolution 'Spatial Information Clearinghouse' new]
[link http://ccrs.nrcan.gc.ca/glossary/index_e.php?id=612 'Canada Centre for Remote Sensing' new]

Part 1 Page

Step 1 Name

Image Animation

Step 1 Description

[bigfirstline]Before we begin, let's consider for a moment what an animation of the atmosphere actually is. Any ideas?[end bigfirstline]

You've probably seen one before. If you've ever watched the weather forecast on TV, you know that weather patterns change from day to day. For instance, in the temperate zone of the northern hemisphere, most frontal storm systems move generally from west to east, and a storm in the midwestern US will typically travel to the east coast in two or three days. Another example of the atmosphere in motion is the counter-clockwise spin of a large low pressure system, such as a hurricane. When seen on TV or the internet, these are examples of weather animations. Click [link http://www.ssec.wisc.edu/data/us_comp/us_comp.html 'here'] for an example of an animation of today's weather over the US.

How many images were there in the animation? How do you know?

An atmospheric animation is a series of images showing change in one or more components of the atmosphere over time.

Think about that for a moment, and try to picture an animation of carbon monoxide concentration. What do you envision? You probably picture a plume of carbon monoxide expanding or contracting, or perhaps moving slightly in one direction or another, but not randomly changing from one image to the next, right?

Keeping in mind that the aerosol optical thickness and carbon mononxide images are monthly averages, decide what temporal scale is most appropriate for our lesson. Should you create an animation using a temporal scale of one month between successive images, or two months between images, or some other scale, such as a year between images?

Step 2 Name

Image Selection

Step 2 Description

Let's begin with a simple question -- Which would most likely show a greater amount of change, a 1-month temporal resolution (for example Sept. 02, Oct. 02, Nov. 02), or a 3-month temporal resolution (Sept. 02, Dec. 02, March 03)?

It would depend, right? Right! It would depend on the underlying source of the CO. If the CO source is a constant emitter, then the concentration should not change dramatically in location, size, or concentration from month to month. For instance, a large industrialized area with many factories will emit a fairly consistent amount of CO from month to month. Conversely, a natural source of CO, such as a region that experiences sporadic brush or forest fires, will emit CO on an intermittentbasis, until the fires are extinguished or naturally burn themselves out.

Before we create the animation, right down your hypothesis, your prediction of the change that your animation will show. Your hypothesis should describe 1) the predicted size of the plume – for example, it will increase in size over time, or decrease in size over time; 2) and it's position – for example, it will move from west to east, in some other direction, or not at all, and 3) the level of concentration - for example, the plume will become less concentrated over time. Don't worry about being 'right' or 'wrong', but simply base your hypothesis, or best guess, on your growing knowledge of carbon monoxide concentration images from the two previous lessons.

Here's an example of an hypothesis:

"I predict that the CO plume over central Africa will increase from September to November 2002, and will move slightly from east to west."

This statement is a testable, right? The animation will allow you to determine if your hypothesis was correct, or not.

If you understand the concepts of variation and source of emissions, and you've written down your hypothesis, you're ready to begin creating your animation.

Step 3 Name

Step 3 Description

Step 4 Name

Step 4 Description

Step 5 Name

Step 5 Description

Step 6 Name

Step 6 Description

Step 7 Name

Step 7 Description

Repeat Step Name and Step Description for up to 9 Steps About the Tool and Data Page

EET Tool Name Specific or general name of the tool used in the chapter. If the tool used in your chapter is the only tool that can be used to accomplish it, give the specific name of the tool. If the chapter could be completed using a generic tool such as a spreadsheet or a GIS, use the generic name, then give the name of the specific tool you will use to illustrate the chapter. Example of a generic tool entry: Spreadsheet. This chapter uses Excel

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EET Tool Help Links to useful, stable help site(s) for using the tool.

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EET Data Name 1 General name describing data set #1 EET Data Description 1 Begin with a clear, general description of data set #1. Describe the data accurately, using as little discipline-specific vocabulary as possible. Build the complexity of the description incrementally, focusing on one idea at a time.

EET Data Geospatial Coverage 1 Describe areas of Earth for which data are available. Wherever possible, give the latitude and longitude coordinates of the bounding box of the area for which data are available.

EET Data Temporal Coverage 1 Describe the time period for which data are available including any periodicity of the data. Enter the beginning and ending dates.

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EET Variations General instructions that extend users abilities to use the tool or data in a new way. This may include suggestions (other ideas) for further analysis of the data, technique applied to different content, different techniques applied to same data. Use an active voice directed to the user.

Hi All,

While looking for information to complete the Aerosol Optical Thickness data sheet, I found this VERY cool series of fire maps. http://rapidfire.sci.gsfc.nasa.gov/firemaps/?2005241-2005250

As you can see, during the time period that we've decided to study, central South America and southern Africa are "ablaze."

If you go forward and backward in time, you can see how the pattern moves around. I'm not sure if/how we can use this resource, but I thought it was interesting enough to pass along.

Mary Jo

NOTE TO SELF / RICK – SEE BOOKMARKS FOR KML FILES OF RAPID FIRE MODIS PTS BY WORLD REGION http://maps.geog.umd.edu/firms/kml/

EET Other Data Link(s) to other data sets, each followed by a brief general description of how the same tool and technique might be used to explore it.

EET Other Techniques Alternate approaches to working with the tool or data.

EET Other Tools Link(s) to related tools, each followed by a brief general description of how it accomplishes the same technique.

EET Related Case Studies Descriptions of other EET case studies that use the same tool, technique, data set, or that cover similar content matter. Provide link(s) to the case study page of related chapters. ------email_1 http://earthobservatory.nasa.gov/Study/FireAlerts/ http://earthobservatory.nasa.gov/Study/FireAlerts/fire_alerts2.html http://earthobservatory.nasa.gov/Study/Fire/ NASA Demonstrates New Technology for Monitoring Fires from Space —by David Herring http://earthobservatory.nasa.gov/Observatory/Datasets/mopitt_co.atmos.html (great description of carbon monoxide data –scroll down) http://earthobservatory.nasa.gov/Newsroom/NewImages/images.php3?img_id=16762 Aerosols and Carbon Monoxide over Africa and Asia http://earthobservatory.nasa.gov/Newsroom/NewImages/images.php3?img_id=17431 Carbon Monoxide, Fires, and Air Pollution ------email_2 http://earthobservatory.nasa.gov/Observatory/Datasets/aer_od.modis.html great short explanation of aerosols http://earthobservatory.nasa.gov/Newsroom/NewImages/images.php3?img_id=17575 explanation of aerosols http://earthobservatory.nasa.gov/NaturalHazards/natural_hazards_v2.php3?img_id=2621 smoke and optical depth ------email_3 http://earthobservatory.nasa.gov/Study/CoralDeath/coral_death.html

Interesting (depressing) example of the catastrophic intersection of human impacts and natural environmental variation

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