The percentiles tell you how many points fit within a given range. I used the 68th and 95th percentiles for this lab. This means, for example, that the difference between the DEM and the field report data for the 95th percentile of urban land cover is within 0.384 m 95% of the time.
RMSE tells you how similar one set of values is to another. The lower the number the more accurate the data is. RMSE does not tell you about the distribution of error. I found that bare earth and low grass land covers were the most accurate while fully forested areas were the least accurate.
ME tells you about possible bias in the data. A negative number indicates underestimation while a positive number indicates overestimation. The urban area was the most biased with a ME of 0.164 while bare earth was the least biased with -0.005. I have attached below a table summarizing the values I arrived at during this lab.
Accuracy Metric
|
Accuracy (m)
|
|||||
Bare earth and low grass
|
High grass, weeds, and crops
|
Brush land and low trees
|
Fully forested
|
Urban
|
Combined
|
|
Sample size
|
48
|
55
|
45
|
98
|
41
|
287
|
Accuracy 68th (m)
|
0.098
|
0.151
|
0.22
|
0.222
|
0.189
|
0.276
|
Accuracy 95th (m)
|
0.163
|
0.44
|
0.481
|
0.463
|
0.384
|
0.171
|
RMSE (m)
|
0.105
|
0.181
|
0.246
|
0.394
|
0.2
|
0.429
|
ME
|
-0.005
|
-0.069
|
-0.103
|
0.003
|
0.164
|
-0.006
|
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