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Applied Cartography and Introduction to GIS GEOG 2017 EL Lecture-3 Chapters 5 and 6.

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Applied Cartography and Introduction to GIS GEOG 2017 EL Lecture-3 Chapters 5 and 6
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Applied Cartography and Introduction to GIS

GEOG 2017 ELLecture-3

Chapters 5 and 6

Metadata

• Metadata provide information about geospatial data. They are therefore an integral part of GIS data and are usually prepared and entered during the data production process.

• Metadata are important to anyone who plans to use public data for a GIS project.

Conversion of Existing Data

• Data conversion refers to the mechanism for converting GIS data from one format to another.

• Data conversion includes direct translation and use of neutral format.

MIF to Shapefile Tool in ArcGIS

Neutral Format Translation

Creating New Data

• A variety of data sources and methods can be used to create new data:– Remotely sensed data– Field data (survey data and GPS data)– Text files with x-, y-coordinates– Digitizing using a digitizing table– Scanning– On-screen digitizing

Bearing and Distance

GPS Data

Portable GPS Receiver

Elevation from GPS

Digitizing Table

Manual Digitization

Many GIS packages have a built-in digitizing module for manual digitizing. The module is likely to have commands that can help move or snap a feature (i.e., a point or line) to a precise location in relation to another feature either in the same layer or a different layer.

Snapping Tolerance

Snapping Tolerance

Scanning

• Scanning is a digitizing method that converts an analog map into a scanned file, which is then converted back to vector format through tracing.

• Results of tracing depend on the robustness of the tracing algorithm that is built in the GIS package. Examples of problems that must be solved by the tracing algorithm include: how to trace an intersection, where the width of a raster line may double or triple; how to continue when a raster line is broken or when two raster lines are close together; and how to separate a line from a polygon.

Binary Scanned File

Raster Error in Scanned Image

Geometric Transformation

• Geometric transformation is the process of using a set of control points and transformation equations to register a digitized map, a satellite image, or an air photograph onto a projected coordinate system.

• In GIS, geometric transformation includes map-to-map transformation and image-to-map transformation.

Transformation Methods

Different methods have been proposed for transformation from one coordinate system to another. Each method is distinguished by the geometric properties it can preserve and by the changes it allows.

Types of Geometric Transformations

Affine Transformations

Control Points

• Control points play a key role in determining the accuracy of an affine transformation.

• Selection of control points for a map-to-map transformation is relatively straightforward. What we need are points with known real-world coordinates.

• Control points for an image-to-map transformation, also called ground control points, are points where both image coordinates (in rows and columns) and real-world coordinates can be identified. GCPs are selected directly from a satellite image; the selection is not as straightforward as selecting four tics for a digitized map.

Transformation Steps

RMS Error

The root mean square (RMS) error is a common measure of the goodness of the control points. It measures the deviation between the actual (true) and estimated (digitized) locations of the control points.

RMS Error Interpretation

• If a RMS error is within the acceptable range, we usually assume that the transformation of the entire map is also acceptable.

• This assumption can be quite wrong, however, if gross errors are made in digitizing the control points or in inputting the longitude and latitude readings of the control points.

Location Errors

Location Errors

Pixel Resampling

Resampling is a process that fills each pixel of the new image derived from an image-to-map transformation with a value or a derived value from the original image.

Resampling Methods

• 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.

• The cubic convolution method uses the average of the 16 nearest pixel values from five cubic polynomial interpolations.

Resampling


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