Soil Saturation and Stability Analysis of a Test Site Slope Using the Shallow Landslide Instability Prediction (SLIP) Model View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-08

AUTHORS

Lorella Montrasio, Roberto Valentino, Claudia Meisina

ABSTRACT

It is well-known that the degree of saturation is a soil state condition able to represent the hydrological response of a shallow soil to weather conditions. One of the oldest models that referred on the degree of saturation to carry out the slope stability analysis at different scales, was the Shallow Landslide Instability (SLIP) Model. This paper shows how the SLIP model can be used to derive a simplified method to estimate multiple seasonal cycles of the mean degree of saturation of soil and to carry out the time-varying stability analysis of a test site slope. The simplified method to assess the degree of saturation uses easily available climatic data, such as air temperature and rainfall depth, and is validated through the comparison with long-term field measurements on a slope in Canneto Pavese, northern Italy. The SLIP model is also applied to obtain the safety factor of the slope, that was subjected to a rainfall-induced shallow landslide during the field monitoring period. Comparisons between field measurements and model outputs are used to validate the capability of the model of predicting both the mean degree of saturation of the topsoil and the observed unstable condition. More... »

PAGES

2331-2342

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10706-018-0465-3

DOI

http://dx.doi.org/10.1007/s10706-018-0465-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1100709036


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0406", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Physical Geography and Environmental Geoscience", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/04", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Earth Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Parma", 
          "id": "https://www.grid.ac/institutes/grid.10383.39", 
          "name": [
            "Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze 181/A, 43124, Parma, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Montrasio", 
        "givenName": "Lorella", 
        "id": "sg:person.07546024720.30", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07546024720.30"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Parma", 
          "id": "https://www.grid.ac/institutes/grid.10383.39", 
          "name": [
            "Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze 181/A, 43124, Parma, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Valentino", 
        "givenName": "Roberto", 
        "id": "sg:person.014122710377.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014122710377.24"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Pavia", 
          "id": "https://www.grid.ac/institutes/grid.8982.b", 
          "name": [
            "Department of Earth and Environmental Sciences, University of Pavia, Via Ferrata 1, 27100, Pavia, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Meisina", 
        "givenName": "Claudia", 
        "id": "sg:person.010071162253.20", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010071162253.20"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.jhydrol.2010.03.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004315729"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2009jf001321", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005469518"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/t10-098", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007213685"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10346-015-0642-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007248402", 
          "https://doi.org/10.1007/s10346-015-0642-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0921-8181(01)00095-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009620644"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/nhess-11-1927-2011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020670293"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.proeps.2014.06.023", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021955587"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10346-009-0154-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029077917", 
          "https://doi.org/10.1007/s10346-009-0154-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10346-009-0154-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029077917", 
          "https://doi.org/10.1007/s10346-009-0154-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10346-009-0154-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029077917", 
          "https://doi.org/10.1007/s10346-009-0154-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11069-014-1239-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030628407", 
          "https://doi.org/10.1007/s11069-014-1239-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10346-007-0082-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032385317", 
          "https://doi.org/10.1007/s10346-007-0082-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10346-007-0082-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032385317", 
          "https://doi.org/10.1007/s10346-007-0082-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/nhess-15-1025-2015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033387402"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.enggeo.2015.04.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034852865"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/nhess-13-559-2013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035830359"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/nhess-8-1149-2008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042376871"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11069-011-9906-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045523600", 
          "https://doi.org/10.1007/s11069-011-9906-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/t96-065", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046036530"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2008wr006976", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053561655"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1680/geot.11.p.142", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068208314"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1201/b10526", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095906068"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1201/b21520", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095907385"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/9780470172759", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1109698930"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-08", 
    "datePublishedReg": "2018-08-01", 
    "description": "It is well-known that the degree of saturation is a soil state condition able to represent the hydrological response of a shallow soil to weather conditions. One of the oldest models that referred on the degree of saturation to carry out the slope stability analysis at different scales, was the Shallow Landslide Instability (SLIP) Model. This paper shows how the SLIP model can be used to derive a simplified method to estimate multiple seasonal cycles of the mean degree of saturation of soil and to carry out the time-varying stability analysis of a test site slope. The simplified method to assess the degree of saturation uses easily available climatic data, such as air temperature and rainfall depth, and is validated through the comparison with long-term field measurements on a slope in Canneto Pavese, northern Italy. The SLIP model is also applied to obtain the safety factor of the slope, that was subjected to a rainfall-induced shallow landslide during the field monitoring period. Comparisons between field measurements and model outputs are used to validate the capability of the model of predicting both the mean degree of saturation of the topsoil and the observed unstable condition.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10706-018-0465-3", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1136344", 
        "issn": [
          "0960-3182", 
          "1573-1529"
        ], 
        "name": "Geotechnical and Geological Engineering", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "36"
      }
    ], 
    "name": "Soil Saturation and Stability Analysis of a Test Site Slope Using the Shallow Landslide Instability Prediction (SLIP) Model", 
    "pagination": "2331-2342", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "1b9741138ad8a32416d5374e79d6e556447e62a8432bacd9b28464898b03d18e"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10706-018-0465-3"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1100709036"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10706-018-0465-3", 
      "https://app.dimensions.ai/details/publication/pub.1100709036"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T22:47", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8690_00000603.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007/s10706-018-0465-3"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10706-018-0465-3'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10706-018-0465-3'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10706-018-0465-3'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10706-018-0465-3'


 

This table displays all metadata directly associated to this object as RDF triples.

146 TRIPLES      21 PREDICATES      48 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10706-018-0465-3 schema:about anzsrc-for:04
2 anzsrc-for:0406
3 schema:author N7f607c631eb24c2387f7c69963a95735
4 schema:citation sg:pub.10.1007/s10346-007-0082-3
5 sg:pub.10.1007/s10346-009-0154-7
6 sg:pub.10.1007/s10346-015-0642-x
7 sg:pub.10.1007/s11069-011-9906-5
8 sg:pub.10.1007/s11069-014-1239-8
9 https://doi.org/10.1002/9780470172759
10 https://doi.org/10.1016/j.enggeo.2015.04.006
11 https://doi.org/10.1016/j.jhydrol.2010.03.018
12 https://doi.org/10.1016/j.proeps.2014.06.023
13 https://doi.org/10.1016/s0921-8181(01)00095-9
14 https://doi.org/10.1029/2008wr006976
15 https://doi.org/10.1029/2009jf001321
16 https://doi.org/10.1139/t10-098
17 https://doi.org/10.1139/t96-065
18 https://doi.org/10.1201/b10526
19 https://doi.org/10.1201/b21520
20 https://doi.org/10.1680/geot.11.p.142
21 https://doi.org/10.5194/nhess-11-1927-2011
22 https://doi.org/10.5194/nhess-13-559-2013
23 https://doi.org/10.5194/nhess-15-1025-2015
24 https://doi.org/10.5194/nhess-8-1149-2008
25 schema:datePublished 2018-08
26 schema:datePublishedReg 2018-08-01
27 schema:description It is well-known that the degree of saturation is a soil state condition able to represent the hydrological response of a shallow soil to weather conditions. One of the oldest models that referred on the degree of saturation to carry out the slope stability analysis at different scales, was the Shallow Landslide Instability (SLIP) Model. This paper shows how the SLIP model can be used to derive a simplified method to estimate multiple seasonal cycles of the mean degree of saturation of soil and to carry out the time-varying stability analysis of a test site slope. The simplified method to assess the degree of saturation uses easily available climatic data, such as air temperature and rainfall depth, and is validated through the comparison with long-term field measurements on a slope in Canneto Pavese, northern Italy. The SLIP model is also applied to obtain the safety factor of the slope, that was subjected to a rainfall-induced shallow landslide during the field monitoring period. Comparisons between field measurements and model outputs are used to validate the capability of the model of predicting both the mean degree of saturation of the topsoil and the observed unstable condition.
28 schema:genre research_article
29 schema:inLanguage en
30 schema:isAccessibleForFree false
31 schema:isPartOf N070cadfd44fd446db625b5417f315665
32 N4cbfb4fa151245a1924d12a56342d1bc
33 sg:journal.1136344
34 schema:name Soil Saturation and Stability Analysis of a Test Site Slope Using the Shallow Landslide Instability Prediction (SLIP) Model
35 schema:pagination 2331-2342
36 schema:productId N5a7ba12330414a94b9ecc09aad03db66
37 N97dd434b1cb04646b69f7aaa6c59db13
38 Nd080bb673a7d440cb66d0c4afbf6b416
39 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100709036
40 https://doi.org/10.1007/s10706-018-0465-3
41 schema:sdDatePublished 2019-04-10T22:47
42 schema:sdLicense https://scigraph.springernature.com/explorer/license/
43 schema:sdPublisher N463facd5b7f34cb491ec0e8fab28ae7e
44 schema:url http://link.springer.com/10.1007/s10706-018-0465-3
45 sgo:license sg:explorer/license/
46 sgo:sdDataset articles
47 rdf:type schema:ScholarlyArticle
48 N070cadfd44fd446db625b5417f315665 schema:issueNumber 4
49 rdf:type schema:PublicationIssue
50 N463facd5b7f34cb491ec0e8fab28ae7e schema:name Springer Nature - SN SciGraph project
51 rdf:type schema:Organization
52 N4cbfb4fa151245a1924d12a56342d1bc schema:volumeNumber 36
53 rdf:type schema:PublicationVolume
54 N5a7ba12330414a94b9ecc09aad03db66 schema:name dimensions_id
55 schema:value pub.1100709036
56 rdf:type schema:PropertyValue
57 N7f607c631eb24c2387f7c69963a95735 rdf:first sg:person.07546024720.30
58 rdf:rest N9c4147a84c5f43e6939e50eb32d2f503
59 N97dd434b1cb04646b69f7aaa6c59db13 schema:name readcube_id
60 schema:value 1b9741138ad8a32416d5374e79d6e556447e62a8432bacd9b28464898b03d18e
61 rdf:type schema:PropertyValue
62 N9c4147a84c5f43e6939e50eb32d2f503 rdf:first sg:person.014122710377.24
63 rdf:rest Ne063b2427bf74e4aabc04425f858a3e5
64 Nd080bb673a7d440cb66d0c4afbf6b416 schema:name doi
65 schema:value 10.1007/s10706-018-0465-3
66 rdf:type schema:PropertyValue
67 Ne063b2427bf74e4aabc04425f858a3e5 rdf:first sg:person.010071162253.20
68 rdf:rest rdf:nil
69 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
70 schema:name Earth Sciences
71 rdf:type schema:DefinedTerm
72 anzsrc-for:0406 schema:inDefinedTermSet anzsrc-for:
73 schema:name Physical Geography and Environmental Geoscience
74 rdf:type schema:DefinedTerm
75 sg:journal.1136344 schema:issn 0960-3182
76 1573-1529
77 schema:name Geotechnical and Geological Engineering
78 rdf:type schema:Periodical
79 sg:person.010071162253.20 schema:affiliation https://www.grid.ac/institutes/grid.8982.b
80 schema:familyName Meisina
81 schema:givenName Claudia
82 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010071162253.20
83 rdf:type schema:Person
84 sg:person.014122710377.24 schema:affiliation https://www.grid.ac/institutes/grid.10383.39
85 schema:familyName Valentino
86 schema:givenName Roberto
87 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014122710377.24
88 rdf:type schema:Person
89 sg:person.07546024720.30 schema:affiliation https://www.grid.ac/institutes/grid.10383.39
90 schema:familyName Montrasio
91 schema:givenName Lorella
92 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07546024720.30
93 rdf:type schema:Person
94 sg:pub.10.1007/s10346-007-0082-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032385317
95 https://doi.org/10.1007/s10346-007-0082-3
96 rdf:type schema:CreativeWork
97 sg:pub.10.1007/s10346-009-0154-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029077917
98 https://doi.org/10.1007/s10346-009-0154-7
99 rdf:type schema:CreativeWork
100 sg:pub.10.1007/s10346-015-0642-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1007248402
101 https://doi.org/10.1007/s10346-015-0642-x
102 rdf:type schema:CreativeWork
103 sg:pub.10.1007/s11069-011-9906-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045523600
104 https://doi.org/10.1007/s11069-011-9906-5
105 rdf:type schema:CreativeWork
106 sg:pub.10.1007/s11069-014-1239-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030628407
107 https://doi.org/10.1007/s11069-014-1239-8
108 rdf:type schema:CreativeWork
109 https://doi.org/10.1002/9780470172759 schema:sameAs https://app.dimensions.ai/details/publication/pub.1109698930
110 rdf:type schema:CreativeWork
111 https://doi.org/10.1016/j.enggeo.2015.04.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034852865
112 rdf:type schema:CreativeWork
113 https://doi.org/10.1016/j.jhydrol.2010.03.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004315729
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1016/j.proeps.2014.06.023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021955587
116 rdf:type schema:CreativeWork
117 https://doi.org/10.1016/s0921-8181(01)00095-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009620644
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1029/2008wr006976 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053561655
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1029/2009jf001321 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005469518
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1139/t10-098 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007213685
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1139/t96-065 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046036530
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1201/b10526 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095906068
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1201/b21520 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095907385
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1680/geot.11.p.142 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068208314
132 rdf:type schema:CreativeWork
133 https://doi.org/10.5194/nhess-11-1927-2011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020670293
134 rdf:type schema:CreativeWork
135 https://doi.org/10.5194/nhess-13-559-2013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035830359
136 rdf:type schema:CreativeWork
137 https://doi.org/10.5194/nhess-15-1025-2015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033387402
138 rdf:type schema:CreativeWork
139 https://doi.org/10.5194/nhess-8-1149-2008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042376871
140 rdf:type schema:CreativeWork
141 https://www.grid.ac/institutes/grid.10383.39 schema:alternateName University of Parma
142 schema:name Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze 181/A, 43124, Parma, Italy
143 rdf:type schema:Organization
144 https://www.grid.ac/institutes/grid.8982.b schema:alternateName University of Pavia
145 schema:name Department of Earth and Environmental Sciences, University of Pavia, Via Ferrata 1, 27100, Pavia, Italy
146 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...