A model for estimating parameters of rotational landslide using a first-order differential equation
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
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Yayıncı
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
A first-order differential equation was developed and proposed as a search tool in the detection and determination of rotational landslides from two epochs of light detection and ranging (LiDAR) system data in the form of 3D points. To test the proposed method two epochs of LiDAR data were used: one before and one after a rotational landslide occurred. The first epoch of LiDAR data was real, while the second epoch of LiDAR data was simulated based on the first epoch to ensure one or more rotational landslides were included. From the last returns of LiDAR data of both epochs, two functional surfaces were created. Then elevation differences were obtained for identical points in both surfaces. The differenced elevations mainly contain two types of data; one type consists of unchanged elevation differences and the other type includes changed elevation differences. The second type may be considered as outliers with respect to the former. Next, segmentation was performed using the determined outliers. Finally, segmented data were used to estimate the rotational landslide parameters. Using the model, all rotational landslides were detected and their parameters estimated, which were consistent with simulation parameters. In conclusion, the developed model is capable of detecting and determining rotational landslides from 3D data.
A first-order differential equation was developed and proposed as a search tool in the detection and determination of rotational landslides from two epochs of light detection and ranging (LiDAR) system data in the form of 3D points. To test the proposed method two epochs of LiDAR data were used: one before and one after a rotational landslide occurred. The first epoch of LiDAR data was real, while the second epoch of LiDAR data was simulated based on the first epoch to ensure one or more rotational landslides were included. From the last returns of LiDAR data of both epochs, two functional surfaces were created. Then elevation differences were obtained for identical points in both surfaces. The differenced elevations mainly contain two types of data; one type consists of unchanged elevation differences and the other type includes changed elevation differences. The second type may be considered as outliers with respect to the former. Next, segmentation was performed using the determined outliers. Finally, segmented data were used to estimate the rotational landslide parameters. Using the model, all rotational landslides were detected and their parameters estimated, which were consistent with simulation parameters. In conclusion, the developed model is capable of detecting and determining rotational landslides from 3D data.
A first-order differential equation was developed and proposed as a search tool in the detection and determination of rotational landslides from two epochs of light detection and ranging (LiDAR) system data in the form of 3D points. To test the proposed method two epochs of LiDAR data were used: one before and one after a rotational landslide occurred. The first epoch of LiDAR data was real, while the second epoch of LiDAR data was simulated based on the first epoch to ensure one or more rotational landslides were included. From the last returns of LiDAR data of both epochs, two functional surfaces were created. Then elevation differences were obtained for identical points in both surfaces. The differenced elevations mainly contain two types of data; one type consists of unchanged elevation differences and the other type includes changed elevation differences. The second type may be considered as outliers with respect to the former. Next, segmentation was performed using the determined outliers. Finally, segmented data were used to estimate the rotational landslide parameters. Using the model, all rotational landslides were detected and their parameters estimated, which were consistent with simulation parameters. In conclusion, the developed model is capable of detecting and determining rotational landslides from 3D data.
Açıklama
Anahtar Kelimeler
Jeoloji, Yerbilimleri, Ortak Disiplinler
Kaynak
Turkish Journal of Earth Sciences
WoS Q Değeri
Q4
Scopus Q Değeri
Q2
Cilt
26
Sayı
4
