地理信息系统导论chap04

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Figure 4.3 UTM coordinates for the extent and the center of a 30-meter cell.
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Types of Raster Data
1. 2. 3. 4. 5. 6. 7. 8. Satellite Imagery Digital Elevation Models (DEMs) Digital Orthophotos (DOQ) Land Cover Data Bi-Level Scanned Files Digital Raster Graphics (DRGs) Graphic Files GIS Software-Specific Raster Data
Limited areas in the Conterminous U.S.
10 m
2.44 m
3m
~0.15 m
*Most NED data for Alaska are at 2-arc-second (about 60 m), but part of Alaska is available at the 1- and 1/3-arc second resolution.
Table 4.1 Satellite images from GeoEye and Digital Globe and their spatial resolution
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Digital Elevation Models (DEMs)
A digital elevation model (DEM) consists of an array of uniformly spaced elevation data.
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Raster Data Structure
1. Cell-by-Cell Encoding 2. Run Length Encoding 3. Quad Tree
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Figure 4.8 The cell-by-cell data structure records each cell value by row and column.
A digital raster graphic (DRG) is a scanned image of a USGS topographic map.
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Graphic Files
Many popular graphic files are in raster format, such as TIFF, GeoTIFF, GIF, and JPEG.
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Figure 4.1 A continuous elevation raster with darker shades for higher elevations.
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Figure 4.2 Representation of point, line, and polygon features: raster format on the left and vector format on the right.
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Elements of the Raster Data Model
1. Cell value. Each cell in a raster carries a value, which represents the characteristic of a spatial phenomenon at the location denoted by its row and column. The cell value can be integer or floating-point. 2. Cell size. The cell size determines the resolution of the raster data model. 3. Cell depth. The cell depth indicates the number of bits and the sign of the data type for all cells. 4. Raster bands. A raster may have a single band or multiple bands. 5. Spatial reference. Raster data must have the spatial reference information so that they can align spatially with other data sets in a GIS.
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Global DEMs
1. 2. 3. 4. 5. SRTM DEMs ETOPO5 GTOPO30 GLOBE TanDEM-X
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Figure 4.5 USGS 1-meter black-andwhite DOQ for Sun Valley, Idaho.
A digital orthophoto quad (DOQ) is a digitized image of an aerial photograph or other remotely sensed data in which the displacement caused by camera tilt and terrain relief has been remove. 15
A bi-level scanned file is aues of 1 or 0.
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Figure 4.7 USGS DRG for Sun Valley, Idaho. This DRG is outdated compared to the DOQ in Figure 4.5.
Land Cover Data
Land cover data are typically classified and compiled from satellite imagery and are thus often presented as raster data.
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Figure 4.6 A bi-level scanned file showing soil lines.
Chapter 4 Raster Data Model
4.1 Elements of the Raster Data Model 4.1.1 Cell Value Box 4.1 Rules in Determining a Categorical Cell Value 4.1.2 Cell Size 4.1.3 Cell Depth 4.1.4 Raster Bands 4.1.5 Spatial Reference 4.2 Types of Raster Data 4.2.1 Satellite Imagery 4.2.2 Digital Elevation Models (DEMs) 4.2.3 USGS DEMs 4.2.4 Global DEMs 4.2.5 Digital Orthophotos 4.2.6 Land Cover Data 4.2.7 Bi-Level Scanned Files 4.2.8 Digital Raster Graphics (DRGs) 4.2.9 Graphic Files 4.2.10 GIS Software-Specific Raster Data 4.3 Raster Data Structure 4.3.1 Cell-by-Cell Encoding 4.3.2 Run-Length Encoding 4.3.3 Quad Tree 4.3.4 Header File
Table 4.2 NED DEMs, resolution, vertical accuracy, and coverage*
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Figure 4.4 DEMs at three resolutions: 30 meters, 10 meters, and 3 meters. The 30-m and 10-m DEMs are USGS DEMs. The 3-m DEM is a derived product from LIDAR data.
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Raster Data Model
A raster represents a continuous surface, but for data storage and analysis, a raster is divided into rows, columns, and cells. Raster data represent points by single cells, lines by sequences of neighboring cells, and areas by collections of contiguous cells.
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GeoEye
IKONOS Panchromatic 82 cm Multispectral 4m GeoEye-1 Panchromatic 41 cm Multispectral 1.65 m
Digital Globe QuickBird Panchromatic 65 cm Multispectral 2.62 m WorldView-2 Panchromatic 46 cm Multispectral 1.85 m
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USGS DEMs
DEM Resolution vertical accuracy Coverage
1 Arc Second 1/3 Arc Second
1/9 Arc Second
30 m
2.44 m
Conterminous U.S., HI, PR, VI, and Territorial Islands Conterminous U.S., HI, and portions of AK
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Satellite Images
A passive remote sensing system, such as Landsat, IKONOS, GeoEye-1, QuickBird, and WorldView-2, measures light energy reflected or emitted from the Earth Surface. An active remote sensing system such as RADARSAT-2 transmits its own signal and measure the energy reflected or scattered back from the Earth’s surface. It can work in the presence of clouds, rain, or darkness.
Box 4.2 A Header File Example 4.4 Raster Data Compression 4.5 Raster Data File Formats Box 4.3 A Simple Wavelet Example: The Haar Wavelet 4.6 Data Conversion and Integration 4.6.1 Rasterization 4.6.2 Vectorization 4.6.3 Integration of Raster and Vector Data Box 4.4 Linking Vector Data with Images Box 4.5 Digital Earth Key Concepts and Terms Review Questions Applications: Raster Data Model Task 1: View and Import DEM Data Task 2: View a Satellite Image in ArcMap Task 3: Convert Vector Data to Raster Data Challenge Task References