1. Geometric Correction It is vital for many applications using remotely sensed images to know the ground locations for points in the image. There are two similar processes that can help build the link between images and real world locations: image-to-map rectification and image-to-image registration. Image-to-map rectification: a process by which the geometry of an image is made planimetric with reference to a projected map. Image-to-image registration: a process which translate the geometry of one image to another (usually projected) image so that corresponding elements of the same ground area appear in the same place on the registered images. The image used as reference (with known projection and coordinates) is called the master image, and the image to be registered is called the subject image. It is important that the reference map or image is rendered in a standard map projection and coordinate systems.

2. Map Projection Map projection is the process of systematic transformation of points on the Earth’s surface to corresponding points on a plane surface. Cylindrical Conical Planar

3. Commonly Used Spheroid in Map Projection Ellipsoids Date Semi-major axis Semi-minor axis Ellipticity Clarke 1866 6,378,206.4 6,356,583.6 1/294.98 WGS72 1972 6,378,135 6,356,750 1/298.26 GRS80 1980 6,378,137 6,356,752 1/298.257 WGS84 1984 6,378,137 6,356,752 1/298.257 … Many of the earlier US maps are based on Clarke 1866 ellipsoid which was determined by Sir Alexander Clarke in 1866. The World Geodetic System (WGS72 and 84) ellipsoids, determined from satellite orbital data are considered more accurate. GRS80 (Geodetic Reference System) ellipsoid is adopted by the International Association of Geodesy

4. The Global Coordinate System spherical coordinate system unprojected! expressed in terms of two angles (latitude & longitude) longitude: angle formed by a line going from the intersection of the prime meridian and the equator to the center of the earth, and a second line from the center of the earth to the point in question latitude: angle formed by a line from the equator toward the center of the earth, and a second line perpendicular to the reference ellipsoid at the point in question

5. latitude positive in n. hemisphere negative in s. hemisphere longitude positive east of Prime Meridian negative west of Prime Meridian Origin of Geographic Coordinate System Global Coordinate System

6. The Universal Transverse Mercator Coordinate System 60 zones, each 6° longitude wide Starting from 180 degrees eastward zones run from 80° S to 84° N poles covered by Universal Polar System (UPS

7. Transverse Mercator Projection applied to each 6 o zone to minimize distortion UTM Zone Projection

8. UTM Coordinate Parameters Unit: meters Zones: 6 o longititue N and S zones: separate coord X-origin: 500,000 m east of central meridian Y-origin: equator

9. USA In The UTM Zones

10. State Plane Coordinate System Each state has one or more zones Zones are either N-S or E-W oriented (except Alaska) Each zone has separate coordinate system and appropriate projection Unit: feet no negative numbers

11. Map Projections for State Plane Coordinate System N-S zones: Transverse Mercator Projection E-W zones: Lambert conformal conic projection

12. Geometric Correction x’ y’ x y image map GCP Ground Control Points Master x Master y Subject x Subject y x1 y1 x2 y2 x3 y3 … x1 y1 x2 y2 x3 y3 … Note: Coordinates must be in file coordinates (lines, samples).

13. First order polynomial: Second order polynomial: Third order polynomial … Goodness of fit: Unit of RMSE: pixels

14. Image Grids on Reference Grids The output of geometric correction is a grid that exactly overlays the reference grid. Image-to-image registration: Reference grids already exist. Image-to-map rectification: Need to create a reference grid first. (1). Specify an origin (2). Translate map coordinates to image coordinates based on pixel size.

15. Resampling Methods 1.Nearest Neighbor: The DN values in the output grid takes from the pixel that is nearest in the input grid. The output grid maintains all the original DN values in the input grid. 2. Bilinear Interpolation: Inverse distance weighted average of the four nearest pixels to the output pixel. 3. Cubic Convolution: Inverse distance weighted average of the 16 nearest pixels to the output pixel.