Integration of Remotely Sensed Soil Sealing Data in Landslide Susceptibility Mapping

被引:29
|
作者
Luti, Tania [1 ]
Segoni, Samuele [1 ]
Catani, Filippo [1 ]
Munafo, Michele [2 ]
Casagli, Nicola [1 ]
机构
[1] Univ Firenze, Dipartimento Sci Terra, Via La Pira 4, I-50121 Florence, Italy
[2] ISPRA Italian Inst Environm Protect & Res, Via Brancati 48, I-00144 Rome, Italy
关键词
landslide susceptibility; soil sealing; land take; land consumption; land cover; imperviousness; landslide hazard; landslide risk; random forest; urban density; SPATIAL PREDICTION MODELS; SENSING DATA; LOGISTIC-REGRESSION; HAZARD ASSESSMENT; VALIDATION; RAINFALL; GIS; CLASSIFICATION; OPTIMIZATION; MULTIVARIATE;
D O I
10.3390/rs12091486
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Soil sealing is the destruction or covering of natural soils by totally or partially impermeable artificial material. ISPRA (Italian Institute for Environmental Protection Research) uses different remote sensing techniques to monitor this process and updates yearly a national-scale soil sealing map of Italy. In this work, for the first time, we tried to combine soil sealing indicators as additional parameters within a landslide susceptibility assessment. Four new parameters were derived from the raw soil sealing map: Soil sealing aggregation (percentage of sealed soil within each mapping unit), soil sealing (categorical variable expressing if a mapping unit is mainly natural or sealed), urbanization (categorical variable subdividing each unit into natural, semi-urbanized, or urbanized), and roads (expressing the road network disturbance). These parameters were integrated with a set of well-established explanatory variables in a random forest landslide susceptibility model and different configurations were tested: Without the proposed soil-sealing-derived variables, with all of them contemporarily, and with each of them separately. Results were compared in terms of AUC ((area under receiver operating characteristics curve, expressing the overall effectiveness of each configuration) and out-of-bag-error (estimating the relative importance of each variable). We found that the parameter "soil sealing aggregation" significantly enhanced the model performances. The results highlight the potential relevance of using soil sealing maps on landslide hazard assessment procedures.
引用
收藏
页数:19
相关论文
共 50 条
  • [31] Remotely sensed burn severity mapping
    Bertolette, D
    Spotskey, D
    Crossing Boundaries in Park Management: Proceedings of the 11th Conference on Research and Resource Management in Parks and on Public Lands, 2001, : 44 - 51
  • [32] The importance of input data on landslide susceptibility mapping
    Krzysztof Gaidzik
    María Teresa Ramírez-Herrera
    Scientific Reports, 11
  • [33] The importance of input data on landslide susceptibility mapping
    Gaidzik, Krzysztof
    Teresa Ramirez-Herrera, Maria
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [34] IHS TRANSFORM FOR THE INTEGRATION OF RADAR IMAGERY WITH OTHER REMOTELY SENSED DATA
    HARRIS, JR
    MURRAY, R
    HIROSE, T
    PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 1990, 56 (12): : 1631 - 1641
  • [35] Integration of thematic vector data in the analysis of remotely sensed images for reconnaissance
    Schwan, H
    Schulz, K
    Thonnessen, U
    IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING V, 1999, 3871 : 315 - 324
  • [36] Fuzzy logic and neural techniques integration: An application to remotely sensed data
    Blonda, P
    Bennardo, A
    Satalino, G
    Pasquariello, G
    PATTERN RECOGNITION LETTERS, 1996, 17 (13) : 1343 - 1348
  • [37] Integration of remotely sensed data with hydrological modelling of Mount Liban (Lebanon)
    Bernier, M
    Fortin, JP
    Gauthier, Y
    Corbane, C
    Somma, J
    Dedieu, JP
    HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES, 2003, 48 (06): : 999 - 1012
  • [38] Experience with mapping of bog ecosystems based on remotely sensed spectral data
    Nichiporovich, Z. A.
    Radevich, E. A.
    JOURNAL OF APPLIED SPECTROSCOPY, 2013, 79 (06) : 944 - 948
  • [39] Soft classifications for the mapping of land cover from remotely sensed data
    Foody, GM
    APPLICATIONS AND SCIENCE OF NEURAL NETWORKS, FUZZY SYSTEMS, AND EVOLUTIONARY COMPUTATION, 1998, 3455 : 23 - 34
  • [40] Experience with mapping of bog ecosystems based on remotely sensed spectral data
    Z. A. Nichiporovich
    E. A. Radevich
    Journal of Applied Spectroscopy, 2013, 79 : 944 - 948