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<front>
<journal-meta>
<journal-id journal-id-type="publisher">NHESS</journal-id>
<journal-title-group>
<journal-title>Natural Hazards and Earth System Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">NHESS</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Nat. Hazards Earth Syst. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1684-9981</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/nhess-6-803-2006</article-id>
<title-group>
<article-title>Stochastic procedure to extract and to integrate landslide susceptibility maps: an example of mountainous watershed in Taiwan</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jr-Chuan Huang</surname>
<given-names></given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Shuh-Ji Kao</surname>
<given-names></given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Mei-Ling Hsu</surname>
<given-names></given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jiun-Chuan Lin</surname>
<given-names></given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Research Center for Environmental Changes, Academia Sinica, Taipei, Taiwan</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Department of Geography, National Taiwan University, Taipei, Taiwan</addr-line>
</aff>
<pub-date pub-type="epub">
<day>25</day>
<month>09</month>
<year>2006</year>
</pub-date>
<volume>6</volume>
<issue>5</issue>
<fpage>803</fpage>
<lpage>815</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2006 Jr-Chuan Huang et al.</copyright-statement>
<copyright-year>2006</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Generic License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by-nc-sa/2.5/">https://creativecommons.org/licenses/by-nc-sa/2.5/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://nhess.copernicus.org/articles/6/803/2006/nhess-6-803-2006.html">This article is available from https://nhess.copernicus.org/articles/6/803/2006/nhess-6-803-2006.html</self-uri>
<self-uri xlink:href="https://nhess.copernicus.org/articles/6/803/2006/nhess-6-803-2006.pdf">The full text article is available as a PDF file from https://nhess.copernicus.org/articles/6/803/2006/nhess-6-803-2006.pdf</self-uri>
<abstract>
<p>The Generalized Likelihood Uncertainty Estimation (GLUE) is here
incorporated into a deterministic landslide model (SHALSTAB) to generate
4000 landslide susceptibility maps which enclose various combinations of
full range parameters. Furthermore, an improved index is adopted into GLUE
as a criterion to measure model performance, and through that, 200 maps
holding top 5% performance are retrieved. Proper ranges for parameters
are obtained through GLUE yet they only perform well if combined
appropriately. The 200 better maps are overlapped to construct an integrated
landslide susceptibility map. Instead of giving a single parameter set or a
single susceptibility map, the merit of extracting and integrating procedure
is to envelope uncertainties inherited in model structure and input
parameters. Bias due to subjective parameter input is potentially reduced.
The entire procedure is applied to the Chi-Jia-Wan, a mountainous watershed
in Taiwan. The integrated map shows high-risk area (&amp;gt;50% predicted
landslide probability) only occupies 16.4% of the entire watershed while
able to correctly identify 60% of the actual landslides. For areas above
2100 m height the map is even more successful (projects 77 of the 98 actual
landslides). Interactions among parameters are discussed to highlight the
unsolvable equifinality problem and improperness of presenting a single
model result.</p>
</abstract>
<counts><page-count count="13"/></counts>
</article-meta>
</front>
<body/>
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