地理信息系统导论 课后习题英文版7.doc

Chapter 7 Review Questions1. Explain map-to-map transformation.Map-to-map transformation is one type of geometric transformation that converts the newly digitized map into projected coordinates.2. Explain image-to-map transformation.Image-to-map transformation is one type of geometric transformation that converts the rows and columns (i.e., the image coordinates) of a satellite image into projected coordinates.3. An image-to-map transformation is sometimes called an image-to-world transformation. Why?An image-to-map transformation is also called an image-to-world transformation because the process converts a satellite image into real-world coordinates.4. The affine transformation allows rotation, translation, skew, and differential scaling. Describe each of these transformations.Rotation can rotate a maps x- and y-axis from the origin. Translation can shift its origin to a new location. Skew can allow a nonperpendicularity (or affinity) between the axes, thus changing its shape to a parallelogram with a slanted direction. And differential scaling can change the scale by expanding or reducing in the x and/or y direction.5. Operationally, an affine transformation involves three sequential steps. What are these steps?Step 1: update the x- and y-coordinates of selected control points to real-world coordinates. Step 2: run an affine transformation on the control points and examines the RMS error. Step 3: use the estimated coefficients and the transformation equations to compute the x- and y-coordinates of map features in the digitized map or pixels in the image.6. Explain the role of control points in an affine transformation.The control points are used to estimate the coefficients of the affine transformation and to compute the root mean square (RMS) error. Therefore, the control points play a key role in the transformation process.7. How are control points selected for a map-to-map transformation?Control points are selected directly from the source map. A USGS 1:24,000 scale quadrangle map has 16 points with known longitude and latitude values: 12 points along the border, and 4 additional points within the quadrangle. These 16 points are potential control points for a map-to-map transformation.8. How are ground control points chosen for an image-to-map transformation?Ground control points (GCPs) are selected from a satellite image. GCPs are points where both image coordinates (in rows and columns) and real-world coordinates can be identified.9. Define the root mean square (RMS) error in geometric transformation.The root mean square (RMS) error measures the deviation between the actual (true) and estimated (digitized) locations of the control points. In other words, the RMS error measures the goodness of the control points.10. Explain the role of the RMS error in an affine transformation.The RMS error is a measure of the accuracy of an affine transformation. If the RMS error is within the acceptable range, then the assumption is that this same level of accuracy based on the control points can also apply to the entire map or image. 11. Describe a scenario in which the RMS error may not be a reliable indicator of the goodness of a map-to-map transformation.Suppose the control points are located at the four corner points of a USGS quadrangle map. Even if the control points are shifted from their true locations, the RMS error remains unchanged as long as the object formed by the control points retains the shape of a parallelogram.12. Why do we have to perform the resampling of pixel values following an image-to-map transformation?Because the new image created from an image-to-map transformation has no pixel values, resampling must be followed to fill each pixel of the new image with a value or a derived value from the original image.13. Describe three common resampling methods for raster data.Three common resampling methods are nearest neighbor, bilinear interpolation, and cubic convolution. The nearest neighbor resampling method fills each pixel of the new image with the nearest pixel value from the original image. The bilinear interpolation method uses the average of the four nearest pixel values from three linear interpolations. And the cubic convolution method uses the average of the 16 nearest pixel values from five cubic polynomial interpolations.14. The nearest neighbor method is recommended for resampling categorical data. Why?The nearest neighbor method is recommended for resampling categorical data because it can preserve the original pixel values.15. What is pyramiding?Pyramiding is a technique commonly used for displaying large raster data sets. Pyramiding builds different pyramid lev