Development of a Positioning Technique for an Urban Area Using Omnidirectional Infrared Camera and Aerial Survey Data

2008 ◽  
Vol 22 (6-7) ◽  
pp. 731-747 ◽  
Author(s):  
Jun-ichi Meguro ◽  
Taishi Murata ◽  
Yoshiharu Amano ◽  
Takumi Hasizume ◽  
Jun-ichi Takiguchi
Author(s):  
Jun-ichi Meguro ◽  
Taishi Murata ◽  
Hidetoshi Nishimura ◽  
Yoshiharu Amano ◽  
Takumi Hasizume ◽  
...  

Author(s):  
M. A. Altyntsev ◽  
S. A. Arbuzov ◽  
R. A. Popov ◽  
G. V. Tsoi ◽  
M. O. Gromov

A dense digital surface model is one of the products generated by using UAV aerial survey data. Today more and more specialized software are supplied with modules for generating such kind of models. The procedure for dense digital model generation can be completely or partly automated. Due to the lack of reliable criterion of accuracy estimation it is rather complicated to judge the generation validity of such models. One of such criterion can be mobile laser scanning data as a source for the detailed accuracy estimation of the dense digital surface model generation. These data may be also used to estimate the accuracy of digital orthophoto plans created by using UAV aerial survey data. The results of accuracy estimation for both kinds of products are presented in the paper.


2008 ◽  
Vol 35 (4) ◽  
pp. 253 ◽  
Author(s):  
Jim Hone

Bias, precision and accuracy have been studied extensively in wildlife population estimation including aerial surveys. A review of the literature shows that the concepts of bias and precision are used broadly consistently. Aerial survey data from known populations of feral pig carcases and white-tailed deer show that few density estimates are unbiased and precise. Research is needed, however, to clarify how much bias and how much precision are enough for the various types of wildlife management activities. Accuracy is used in two closely related but different ways. One set of definitions of accuracy relates to deviations from the true value (bias) and the second set relates to squared deviations from the true value (bias and precision). The implications are that authors are encouraged to clearly state which definition of accuracy they use, or focus solely on bias and precision.


Biometrics ◽  
1997 ◽  
Vol 53 (2) ◽  
pp. 524 ◽  
Author(s):  
Bruce A. Craig ◽  
Michael A. Newton ◽  
Robert A. Garrott ◽  
John E. Reynolds III ◽  
J. Ross Wilcox

2016 ◽  
Vol 55 (3) ◽  
pp. 270-281 ◽  
Author(s):  
Henry Ndaimani ◽  
Amon Murwira ◽  
Mhosisi Masocha ◽  
Tawanda W. Gara ◽  
Fadzai M. Zengeya

2009 ◽  
Vol 10 (1) ◽  
pp. 22-30 ◽  
Author(s):  
J.-i. Meguro ◽  
T. Murata ◽  
J.-i. Takiguchi ◽  
Y. Amano ◽  
T. Hashizume

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