INTEGRATING INSAR INFORMATION AND SPATIAL-TEMPORAL FACTORS IN MACHINE LEARNING ANALYSIS FOR LANDSLIDE PREDICTION – A CASE STUDY FOR PROVINCIAL HIGHWAY 18 AREA IN TAIWAN

INTEGRATING INSAR INFORMATION AND SPATIAL-TEMPORAL FACTORS IN MACHINE LEARNING ANALYSIS FOR LANDSLIDE PREDICTION – A CASE STUDY FOR PROVINCIAL HIGHWAY 18 AREA IN TAIWAN

Taiwan is located in subtropical monsoon area and Pacific Ring of Fire. Both the rate of crustal uplift and annual rainfall are among the highest in the world. Earthquakes and heavy rainfall have led to massive landslides and debris flow. Frequent disasters and the high rate of surface erosion have...

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Bibliographic Details
Main Authors: Y. K. Chen, Y. T. Lin, H. Y. Yen, N. H. Chang, H. M. Lin, K. H. Yang, C. S. Chen, L. P. Wang, H. K. Cheng, H. H. Wu, J. Y. Han
Format: Article
Language:English
Published: Copernicus Publications 2022-05-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2022/1091/2022/isprs-archives-XLIII-B3-2022-1091-2022.pdf

Internet

https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2022/1091/2022/isprs-archives-XLIII-B3-2022-1091-2022.pdf

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