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 Smithsonian: Cosmic Voyage
Information This activity is recommended for fourth grade and up. If students have not used coordinate systems, review how to name a location with a letter and number. If stu- dents have difficulty following directions and communicating with one another, the teacher can act as the transmitter for th...
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Information This activity is recommended for fourth grade and up. If students have not used coordinate systems, review how to name a location with a letter and number. If stu- dents have difficulty following directions and communicating with one another, the teacher can act as the transmitter for the entire class. A digital image is composed of pixels (picture elements) that are arranged in rows and columns. Each pixel is assigned a numerical value that represents its relative brightness in the image: the larger the
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http://www.nasm.si.edu/education/pubs/cv_guide.pdf#page=7
www.nasm.si.edu/education/pubs/cv_guide.pdf#page=7
Detector Collect and analyze data. Grades six and up Page 32 Get the Picture Use <span class="highlight">pixels</span> to create an <span class="highlight">image</span>. Grades four and up Page 16 Mystery Box Make inferences based on observations. Grades four and up Page 30 Zoom In Investigate size from cells to quarks. Grades seven and up Page 35 Engineer Meet Brynette Smith Page 43 Observing Measuring Understanding Scale Exploring Careers OUR SPACE OUTER SPACE INNER SPACE
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http://www.nasm.si.edu/education/pubs/cv_guide.pdf#page=23
www.nasm.si.edu/education/pubs/cv_guide.pdf#page=23
copy one for each pair <span class="highlight">of</span> students in each class. Make a transparency. Copy the “Effect <span class="highlight">of</span> Changing Pixel Size” on a transparency for class discussion. Procedure Introduce the activity. Ask students to explain how they think scientists get images from spacecraft that do not return to Earth. Let students know that they will simulate how instruments aboard spacecraft collect and transmit images to Earth. Explain the simulation. Instruments aboard spacecraft divide an <span class="highlight">image</span> into tiny squares called <span class="highlight">pixels</span>
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http://www.nasm.si.edu/education/pubs/cv_guide.pdf#page=25
www.nasm.si.edu/education/pubs/cv_guide.pdf#page=25
Information This activity is recommended for fourth grade and up. If students have not used coordinate systems, review how to name a location with a letter and number. If stu- dents have difficulty following directions and communicating with one another, the teacher can act as the transmitter for the entire class. A digital <span class="highlight">image</span> is composed <span class="highlight">of</span> <span class="highlight">pixels</span> (picture elements) that are arranged in rows and columns. Each pixel is assigned a numerical value that represents its relative brightness in the <span class="highlight">image</span>: the larger the
Smithsonian: Reflections on Earth: Exploring Earth from Space Teaching Poster
provides a “signature” for the type of vegetation present. To highlight different features of Earth, scientists combine images made in several broad wavelength bands (see Fig. 3). To create the composite image, colors are assigned to each wavelength band (see Table 1...
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provides a “signature” for the type of vegetation present. To highlight different features of Earth, scientists combine images made in several broad wavelength bands (see Fig. 3). To create the composite image, colors are assigned to each wavelength band (see Table 1 and Fig. 3), and the result is called false-color. The more radiation reflected, the brighter the corresponding color in the image, and these colors are combined by addition, as in a computer monitor or color TV, to produce the image. A satellite
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http://www.nasm.si.edu/education/pubs/reflect.pdf#page=4
www.nasm.si.edu/education/pubs/reflect.pdf#page=4
provides a “signature” for the type <span class="highlight">of</span> vegetation present. To highlight different features <span class="highlight">of</span> Earth, scientists combine images made in several broad wavelength bands (see Fig. 3). To create the composite <span class="highlight">image</span>, colors are assigned to each wavelength band (see Table 1 and Fig. 3), and the result is called false-<span class="highlight">color</span>. The more radiation reflected, the brighter the corresponding <span class="highlight">color</span> in the <span class="highlight">image</span>, and these colors are combined by addition, as in a computer monitor or <span class="highlight">color</span> TV, to produce the <span class="highlight">image</span>. A satellite
Smithsonian: Reflections on Earth: Biodiversity and Remote Sensing Teacher Guide
reflectance properties. The unique spectral properties of a land cover class are derived from a number of factors, including canopy geometry, leaf densities, colors, optical properties and moisture content, shadows, transpiration rates, and the properties of nonvegetated areas....
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reflectance properties. The unique spectral properties of a land cover class are derived from a number of factors, including canopy geometry, leaf densities, colors, optical properties and moisture content, shadows, transpiration rates, and the properties of nonvegetated areas. Defined by the wavelength bands collected for the image analysis, these attributes are known as the class spectral signature. Classification of land cover types using spectral reflectance properties requires the use of a computer to handle the
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http://www.nasm.si.edu/education/pubs/reflecttg.pdf#page=17
www.nasm.si.edu/education/pubs/reflecttg.pdf#page=17
Teacher Guide 15 A c ti v it y 3 L an d C ov er M ap pi ng OVERVIEW Thinking more globally, how do scientists assess biodiversity for large regions? In this activity, students emulate scientists by <span class="highlight">using</span> a satellite <span class="highlight">image</span> to determine different land cover types and create a land cover map <span class="highlight">of</span> Front Royal, Virginia. OBJECTIVES Students will be introduced to remote-sensing techniques and their applications in monitoring forest biodiversity. Students will visually interpret a satellite <span class="highlight">image</span> (as opposed to
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http://www.nasm.si.edu/education/pubs/reflecttg.pdf#page=18
www.nasm.si.edu/education/pubs/reflecttg.pdf#page=18
reflectance properties. The unique spectral properties <span class="highlight">of</span> a land cover class are derived from a number <span class="highlight">of</span> factors, including canopy geometry, leaf densities, colors, optical properties and moisture content, shadows, transpiration rates, and the properties <span class="highlight">of</span> nonvegetated areas. Defined by the wavelength bands collected for the <span class="highlight">image</span> analysis, these attributes are known as the class spectral signature. Classification <span class="highlight">of</span> land cover types <span class="highlight">using</span> spectral reflectance properties requires the use <span class="highlight">of</span> a computer to handle the
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http://www.nasm.si.edu/education/pubs/reflecttg.pdf#page=21
www.nasm.si.edu/education/pubs/reflecttg.pdf#page=21
Landsat TM <span class="highlight">image</span> has a resolution <span class="highlight">of</span> 30 m. A 1-ha plot (100 m x 100 m) would be equivalent to approximately 9 <span class="highlight">pixels</span> (a square <span class="highlight">of</span> 3 <span class="highlight">pixels</span> by 3 <span class="highlight">pixels</span>). School biodiversity plots are only 20 m2.) 5. Ask students what factors might affect the use <span class="highlight">of</span> satellite images. (Cloud cover, for example, can reduce the detail obtained from a Landsat <span class="highlight">image</span>.) EXTENSIONS 1. Repeat the above activity with a satellite <span class="highlight">image</span> <span class="highlight">of</span> your school site, (which should be available from the USGS web site) and a local topographic map
Smithsonian: The Plant Press Newsletter Volume 8.3
rithms into a complete system for image retrieval. While fully automatic systems are out of reach, we hope to build systems in which automatic matching can assist an expert in finding the most relevant infor- mation. I will describe some components we are using to build our syst...
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rithms into a complete system for image retrieval. While fully automatic systems are out of reach, we hope to build systems in which automatic matching can assist an expert in finding the most relevant infor- mation. I will describe some components we are using to build our system. P. Bryan Heidorn University of Illinois at Urbana- Champaign Beyond Paper on the Web: Adapting Paper-based Flora for the Digital Envi- ronment One of the primary challenges for the creation of digital libraries is to enhance the value
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http://botany.si.edu/pubs/plantpress/vol8no3.pdf#page=12
botany.si.edu/pubs/plantpress/vol8no3.pdf#page=12
rithms into a complete system for <span class="highlight">image</span> retrieval. While fully automatic systems are out <span class="highlight">of</span> reach, we hope to build systems in which automatic matching can assist an expert in finding the most relevant infor- mation. I will describe some components we are <span class="highlight">using</span> to build our system. P. Bryan Heidorn University <span class="highlight">of</span> Illinois at Urbana- Champaign Beyond Paper on the Web: Adapting Paper-based Flora for the Digital Envi- ronment One <span class="highlight">of</span> the primary challenges for the creation <span class="highlight">of</span> digital libraries is to enhance the value
Smithsonian: The Plant Press Newsletter Volume 4.4
file is collected in Photoshop 6.0 where white balancing and color balancing are done. The image is saved as a TIF file using the bar code number of the specimen as the filename. Derivatives for web presenta- tions are created in batches. Type Specimen Imaging Project Oct...
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file is collected in Photoshop 6.0 where white balancing and color balancing are done. The image is saved as a TIF file using the bar code number of the specimen as the filename. Derivatives for web presenta- tions are created in batches. Type Specimen Imaging Project October 2001 marks the 40th year of plant mounting by Mary Skinner. She began in 1961 as a US herbarium contract mounter at home, and then from 1969 to 1986 she mounted plants in the National Museum of Natural History for the Herbarium Services
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http://botany.si.edu/pubs/plantpress/vol4no4.pdf#page=9
botany.si.edu/pubs/plantpress/vol4no4.pdf#page=9
file is collected in Photoshop 6.0 where white balancing and <span class="highlight">color</span> balancing are done. The <span class="highlight">image</span> is saved as a TIF file <span class="highlight">using</span> the bar code number <span class="highlight">of</span> the specimen as the filename. Derivatives for web presenta- tions are created in batches. Type Specimen Imaging Project October 2001 marks the 40th year <span class="highlight">of</span> plant mounting by Mary Skinner. She began in 1961 as a US herbarium contract mounter at home, and then from 1969 to 1986 she mounted plants in the National Museum <span class="highlight">of</span> <span class="highlight">Natural</span> History for the Herbarium Services
Smithsonian: Infrared Array Camera (IRAC)
above image; see the optical housing model and the conceptual layout diagram. The pixel size is 1.2 arcsec in all bands. Two adjacent fields of view in the focal plane are viewed by the four channels in pairs (3.6 and 5.8 microns; 4.5 and 8.0 microns). All four detector arrays in the...
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