Assessing the Accuracy of Remotely Sensed Data: Principles by Russell G. Congalton PDF

By Russell G. Congalton

ISBN-10: 1420055127

ISBN-13: 9781420055122

Congalton does an excellent activity featuring distant sensing accuracy review techniques. as well as the speculation, he presents sensible examples to assist in making use of the idea to actual international situations.

The booklet turns out manner over-priced for its measurement.

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Extra resources for Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, Second Edition (Mapping Science)

Sample text

This is not a big leap of faith, as the normal distribution characterizes a multitude of natural phenomena ranging from organism population dynamics to human polling behavior. However, it is always important to fully understand whether or not the population you are studying is actually normally distributed or not. 9 expresses the dispersal around the mean of the variable Xi at the stipulated probability level if and only if, the population of Xi’s is normally distributed. 6 illustrates the portions of the normal distribution and the corresponding Zi values that match various levels of probability.

6 illustrates the portions of the normal distribution and the corresponding Zi values that match various levels of probability. To summarize, determining the interval at a specific probability within which the mean (m) of our population of interest will fall requires simply: 1. Assuming that the population is normally distributed, 2. Looking up the Zi value for the specified probability level in a standard normal table (which may be found in the back of any statistics text or by searching on the Internet), 3.

An alternative estimator that would also deal with negative values would be to take the absolute value of the arithmetic mean of the errors. The estimate of the standard deviation (S) of the squared differences is also an important parameter in many positional accuracy assessment standards (Greenwalt and Schultz, 1962, 1968; ASPRS, 1989). This chapter also suggests the use of the estimated standard error of the RMSE (SRMSE) to build a confidence interval around the estimate of RMSE. All positional accuracy parameters are estimated by comparing reference coordinates or elevations to the map or image coordinates or elevations of the data set being assessed at each sample location.

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Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, Second Edition (Mapping Science) by Russell G. Congalton


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