2016
DOI: 10.7763/ijesd.2016.v7.738
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Early Detection of Spots High Water Saturation for Landslide Prediction Using Thermal Imaging Analysis

Abstract: Abstract-Nowadays, landslide phenomenon has become a serious problem in Malaysia. Landslide can cause human injury, loss of life and economical problem. One of the factors is due to the heavy rain. Hence, to overcome this problem, this study investigates a new method to detect spots of high water saturation which is integrated with a thermal camera system to provide early detection of landslide. The thermal camera is selected because it provides accurate predict where landslide going to occur. Thermal camera c… Show more

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Cited by 4 publications
(3 citation statements)
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“…Cara ini memantau kondisi tanah dari bagian atas, sedangkan kondisi tanah bagian dalam cenderung tidak terpantau. Pemanfaatan sinyal geophone dalam [9] dan analisis termal dalam [10] juga telah dilakukan, namun metode-metode ini justru mendapatkan masukan data untuk diproses ketika saat terjadi atau sekilas sebelum terjadinya tanah longsor. Ishihara dkk.…”
Section: Pendahuluanunclassified
See 1 more Smart Citation
“…Cara ini memantau kondisi tanah dari bagian atas, sedangkan kondisi tanah bagian dalam cenderung tidak terpantau. Pemanfaatan sinyal geophone dalam [9] dan analisis termal dalam [10] juga telah dilakukan, namun metode-metode ini justru mendapatkan masukan data untuk diproses ketika saat terjadi atau sekilas sebelum terjadinya tanah longsor. Ishihara dkk.…”
Section: Pendahuluanunclassified
“…A B C D E Sistem informasi geografis [7], [8] x x √ √ x Citra satelit [9] x √ √ x √ Sinyal geophone [10] √ x x x √ Analisis termal [11] √ √ √ √ √ Penjadwalan [12] x x √ x x Pemantauan keadaan tanah √ √ √ √ √…”
Section: Metodeunclassified
“…Multi-field information is very important in understanding the deformation characteristics of a landslide. Over the last decade, some new technologies have been developed to monitor landslide deformation, such as GB-InSAR, TLS, IRT, digital photogrammetry (DP), and so on (Nicola et al, 2010;Del Ventisette et al, 2011;Bardi et al, 2014;Crosetto et al, 2016;Zin et al, 2016;Casagli et al, 2017;Li et al, 2020;Zhou et al, 2020), and have achieved remarkable achievements in monitoring, prediction, and early warning of the landslides (Xu et al, 2016;Piciullo et al, 2018;Ouyang et al, 2019). Those technologies are characterized by more efficient operation and higher accuracy of monitoring data, compared with traditional monitoring sensors: offering high-resolution image data acquisition, data diversity, device portability, and easy and fast data processing (Casagli et al, 2017).…”
Section: Introductionmentioning
confidence: 99%