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The prediction errors in height estimation are discussed in relation to the possible interactions with spatial scale, landform types, and data density.
Inaccuracy in height estimation ranged from -9.5% to +25% with a mean inaccuracy of 4.75%.
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To overcome this problem, coherence and backscatter based threshold technique is introduced for forest area identification and accurate height estimation in non-forested regions.
In [26], a barometer height estimation with topographic maps (outdoor environment) is investigated and it is shown that it can improve performance in a GPS-INS-based system.
In other studies, visual height estimation was the only method to be used, even if it seemed to be usually inconsistent [17, 21].
Figure 7 shows the height estimation error in the ruler-based evaluation, including the distribution and the LOA.
Figure 4 shows the height estimation error in the evaluation based on the walking human, including the distribution and the limits of agreement (LOA; also known as the Bland-Altman plot).
In such case, substantial error of height estimation will be caused.
The method demonstrated 25 to 30% improvement in altimetric precision over the interferometric method and increased flexibility in trading off spatial resolution and height estimation accuracy.
Simulations also indicated that the expected number of signal photons from ATLAS will be substantially lower, a situation that reduces canopy height estimation precision especially in areas of low density vegetation cover.
c The process of height measurement (the experimenter raised the hand to indicate the ruler is in a vertical position) Fig. 7 Height estimation results for the ruler-based evaluation.
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