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Performance. Performance is fundamentally limited by: Size of data Where the data is stored Type of processing Processing software Hardware available. Real Performance Limitations. Rasters: Size of the data and number of files Points: Number of rows, number of size of attributes
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Performance • Performance is fundamentally limited by: • Size of data • Where the data is stored • Type of processing • Processing software • Hardware available
Real Performance Limitations • Rasters: Size of the data and number of files • Points: Number of rows, number of size of attributes • Network access, especially services • ArcGIS tools • Mistakes in processing • Hardware
4 Resolutions of Remote Sensing • Spatial: • X and Y resolution • Spectral: • Number of bands • Temporal: • Number of samples per time unit • Radiometric: • Number of bits or bytes per sample
Raster Structure X Dimension Band 0 16 15 10 12 Band 1 23 27 14 19 Band 2 Y Dimension 29 30 18 22 34 32 21 25 Sample Pixel: All the samples are coincident
Raster Resolutions • Spatial Resolution: • Width and height of each sample/pixel • Spectral Resolution: • Number of widths of the bands • Radiometric Resolution: • Number of bits per band • Temporal Resolution: • Number of rasters per time interval
Raster Resolutions • Spatial: • 10 cm to 1 km • Spectral (Number of Bands): • 3 for photos, 7 for Landsat, for 256 MODIS • Temporal: • Daily for MODIS, 15 days for Landsat, every few years for SRTM • Radiometric (Sample Depth): • 8 bits=0 to 255 (256 shades)
Raster Size Size in Bytes = Width of the area * Resolution * Height of the area * Resolution * Bytes per band * Number of bands * Number of Temporal Slices
Landsat TM Scene • Sensor type: opto-mechanical • Spatial Resolution: 30 m (120 m - thermal) • Spectral Range: 0.45 - 12.5 µm • Number of Bands: 7 • Temporal Resolution: 16 days • Image Size: 185 km X 172 km • Swath: 185 km • Programmable: yes http://landsat.gsfc.nasa.gov/about/tm.html
Improving Performance • It used to be storing the data was a major problem • Today, the problem is getting the computer processor “close” to the data
Improving Performance • Resample rasters to the size desired • Clip rasters to the area of interest • Only use the bands required • Store or “cache” rasters to the computer doing the processing • Include performance evaluation as part of the modeling design