Automated digital data acquisition for landslide inventories

被引:0
|
作者
Thomas M. Kreuzer
Bodo Damm
机构
[1] University of Vechta,
来源
Landslides | 2020年 / 17卷
关键词
Landslide inventory; Data acquisition; Machine learning; Document classification; Information filtering;
D O I
暂无
中图分类号
学科分类号
摘要
Landslide research relies on landslide inventories for a multitude of spatial, temporal, or process analyses. Generally, it takes high effort to populate a landslide inventory with relevant data. In this context, the present work investigated an effective way to handle vast amounts of automatically acquired digital data for landslide inventories by the use of machine learning algorithms and information filtering. Between July 2017 and February 2019, a keyword alert system provided 4381 documents that were automatically processed to detect landslide events in Germany. Of all those documents, 91% were automatically recognized as irrelevant or duplicates; thereby, the data volume was significantly reduced to contain only actual landslide documents. Moreover, it was shown that inclusion of the document’s images into the automated process chain for information filtering is recommended, since otherwise unobtainable important information was found in them. Compared with manual methods, the automated process chain eliminated personal idiosyncrasies and human error and replaced it with a quantifiable machine error. The applied individual algorithms for natural language processing, information retrieval, and classification have been tried and tested in their respective fields. Furthermore, the proposed method is not restricted to a specific language or region. All languages on which these algorithms are applicable can be used with the proposed method and the training of the process chain can take any geographical restriction into account. Thus, the present work introduced a method with a quantifiable error to automatically classify and filter large amounts of data during automated digital data acquisition for landslide inventories.
引用
收藏
页码:2205 / 2215
页数:10
相关论文
共 50 条
  • [1] Automated digital data acquisition for landslide inventories
    Kreuzer, Thomas M.
    Damm, Bodo
    [J]. LANDSLIDES, 2020, 17 (09) : 2205 - 2215
  • [2] Digital Data Acquisition
    Asarpota, Jyotsna
    [J]. JPT, Journal of Petroleum Technology, 2024, 76 (01): : 86 - 87
  • [3] Digital Data Acquisition
    Asarpota, Jyotsna
    [J]. JPT, Journal of Petroleum Technology, 2023, 75 (01): : 84 - 85
  • [4] Digital data acquisition
    Sarma, Pallav
    [J]. JPT, Journal of Petroleum Technology, 2021, 73 (01):
  • [5] 802 AUTOMATED ON-LINE DIGITAL DATA ACQUISITION SYSTEM FOR SMA ANALYZERS
    LAESSIG, RH
    TONG, PP
    HOFFMAN, GG
    [J]. CLINICAL CHEMISTRY, 1969, 15 (08) : 813 - &
  • [6] Digital data acquisition
    Sarma, Pallav
    [J]. JPT, Journal of Petroleum Technology, 2020, 72 (01):
  • [7] Landslide inventories and their statistical properties
    Malamud, BD
    Turcotte, DL
    Guzzetti, F
    Reichenbach, P
    [J]. EARTH SURFACE PROCESSES AND LANDFORMS, 2004, 29 (06) : 687 - 711
  • [8] A Semi-Automated Object-Based Approach for Landslide Detection Validated by Persistent Scatterer Interferometry Measures and Landslide Inventories
    Hoelbling, Daniel
    Fuereder, Petra
    Antolini, Francesco
    Cigna, Francesca
    Casagli, Nicola
    Lang, Stefan
    [J]. REMOTE SENSING, 2012, 4 (05): : 1310 - 1336
  • [9] Landslide manual and automated inventories, and susceptibility mapping using LIDAR in the forested mountains of Guerrero, Mexico
    Gaidzik, Krzysztof
    Teresa Ramirez-Herrera, Maria
    Bunn, Michael
    Leshchinsky, Ben A.
    Olsen, Michael
    Regmi, Netra R.
    [J]. GEOMATICS NATURAL HAZARDS & RISK, 2017, 8 (02) : 1054 - 1079
  • [10] PRINCIPLES OF DIGITAL DATA ACQUISITION
    HULL, ML
    [J]. ISA TRANSACTIONS, 1980, 19 (03) : 25 - 36