<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0188-4611</journal-id>
<journal-title><![CDATA[Investigaciones geográficas]]></journal-title>
<abbrev-journal-title><![CDATA[Invest. Geog]]></abbrev-journal-title>
<issn>0188-4611</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Instituto de Geografía]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0188-46112016000300043</article-id>
<article-id pub-id-type="doi">10.14350/rig.46503</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Sistemas de información geográfica y cartografía geomorfológica aplicados al inventario de deslizamientos y cartografía de susceptibilidad en la cuenca del río El Estado, Pico de Orizaba, México]]></article-title>
<article-title xml:lang="en"><![CDATA[Geographic Information Systems and geomorphological mapping applied to landslide inventory and susceptibility mapping in El Estado river, Pico de Orizaba, Mexico]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Aceves Quesada]]></surname>
<given-names><![CDATA[José Fernando]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Legorreta Paulín]]></surname>
<given-names><![CDATA[Gabriel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Lugo Hubp]]></surname>
<given-names><![CDATA[José]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Umaña Romero]]></surname>
<given-names><![CDATA[Juan]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Legorreta Cuevas]]></surname>
<given-names><![CDATA[Héctor Alfredo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Nacional Autónoma de México Instituto de Geografía Laboratorio de Análisis Geoespacial]]></institution>
<addr-line><![CDATA[Ciudad de México ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Nacional Autónoma de México Instituto de Geografía Departamento de Geografía Física]]></institution>
<addr-line><![CDATA[Ciudad de México ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad Nacional Autónoma de México Facultad de Ingeniería Laboratorio de Mecánica de suelos]]></institution>
<addr-line><![CDATA[Ciudad de México ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2016</year>
</pub-date>
<numero>91</numero>
<fpage>43</fpage>
<lpage>55</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0188-46112016000300043&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0188-46112016000300043&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0188-46112016000300043&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: Con el propósito de fortalecer el conocimiento y la prevención de los desastres por deslizamientos en este trabajo se desarrolla una metodología que integra la cartografía geomorfológica con la elaboración de mapas de susceptibilidad a deslizamientos usando los sistemas de información geográfica (SIG) y el método de regresión logística múltiple (RLM). En México se han realizado algunos trabajos aislados con los SIG para evaluar la estabilidad de laderas. Sin embargo, hasta ahora no se ha desarrollado ningún método práctico y estandarizado que integre los mapas geomorfológicos con los inventarios de deslizamientos utilizando los SIG. Este artículo muestra el análisis llevado a cabo para elaborar un inventario de deslizamientos multitemporal junto con la técnica de análisis y cartografía morfométrica de la cuenca del río El Estado. La cuenca del río El Estado, seleccionada como área de estudio, se localiza en la ladera sudoeste del volcán Citlaltepetl o Pico de Orizaba. Los factores geológicos y geomorfológicos en combinación con la alta precipitación estacional, el alto grado de intemperismo y las laderas escarpadas predisponen sus superficies a deslizamientos. Para evaluar la susceptibilidad por deslizamientos de tierras se elaboró un mapa de inventario de deslizamientos usando fotografías aéreas, a continuación se elaboró la cartografía geomorfométrica (altimétrico, pendientes y geomorfográfico) y se realizó trabajo de campo. Con esta información se modeló la susceptibilidad por deslizamientos usando regresión logística múltiple (RLM) dentro de la plataforma de un SIG y se obtuvo el mapa de susceptibilidad por deslizamientos.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: With the aim of raising awareness on the prevention of landslide disasters, this work develops a methodology that incorporates geomorphological mapping into the mapping of landslide susceptibility using Geographic Information Systems (GIS) and Multiple Logistic Regression (MLR). In Mexico, some studies have evaluated the stability of hillsides using GIS. However, these studies set a general framework and guidance (that includes basic concepts and explanations of landslide classification, triggering mechanisms, criteria, considerations, and analysis for landslide hazard reconnaissance, etc.) for preparing a landslide atlas at state and city levels. So far, these have not developed a practical and standardized approach incorporating geomorphological maps into the landslide inventory using GIS. This paper describes the analysis conducted to develop an analytical technique and morphometric analysis for a multi-temporal landslide inventory. Three data management levels are used to create GIS thematic layers. For the first level, analogue topographic, geological, land-use, and climate paper are converted to raster format, georeferenced, and incorporated as GIS thematic layers. For the second level, five layers are derived from topographic elevation data: slope angles, slope curvature, contributing area, flow direction, and saturation. For the third level, thematic maps are derived from the previous two levels of data: a hypsometric map (heuristically classified to highlight altimetric levels), a reclassified slope map (allowing to highlight differences in relief), and a morphographic map (derived from a heuristic reclassification of the slope map to highlight volcanic landforms). The theoretical aspects of geomorphological mapping contribute to set the conceptual basis to support landslide mapping. The GIS thematic layers provide context and establish an overall characterization of landslide processes within the watershed. Through the retrieval and on-off switching of layers in the GIS system, a base map is created to assist in the digitizing of landslides and the modeling of susceptibility. A landslide inventory is created from aerial photographs, field investigations, and all the above GIS thematic layers. El Estado river watershed on the southwestern flank of Pico de Orizaba volcano has been selected as study area. The watershed is located in the southwestern slope of Citlaltepetl or Pico de Orizaba volcano. Geological (the stream channel of El Estado river erodes Tertiary and Quaternary lavas, disjointed volcanoclastic materials such as pyroclastic flows, fall deposits, lahars deposits, and alluvium) and geomorphological factors (steep slopes, energy relief, and vertical erosion) in combination with high seasonal rainfall (annual rainfall averages 1000-1100 mm/yr at &gt; 4000 m a.s.l. and 927 mm/yr at &lt;1500 m a.s.l.), and the high degree of weathering, make the study area susceptible to landslides. To assess landslide susceptibility, a landslide inventory map and geomorphometric cartography (altimetry, slope and geomorphography) were reviewed, and field work was conducted. In the study area, more than one hundred landslides were mapped. Shallow landslides (including debris slides and debris flows) are the predominant type. Shallow landslides predominate on hills capped with ash and pyroclastic deposits. The second major landslide process includes rock falls (which occur where the stream erodes lava flows and lahars) and deep-seated landslides (which occur in ash and pyroclastic deposits where lava flows act as a slip plane). In parallel, the spatial geodatabase of landslides was constructed from standardized GIS datasets. Pertinent attributes are recorded on a geo-dataset. These include 1) mass wasting process, 2) level of certainty of the observation, 3) photo identification date, 4) landslide size, 5) landslide activity, 6) landslide parts (head, evacuation zone, deposit), 7) slope shape, 8) field slope gradient, 9) map gradient measured from the 10 m digital elevation model (DEM), 10) landslide delivery, 11) land use, 12) elevation at which the landslide started, 13) aerial photograph identification number, 14) landslide area, and 15) researcher comments. Each attribute is standardized by the geo-dataset domains in the GIS system. With this information the landslide susceptibility is modeled using MLR within a GIS platform. MLR is used to examine the relation between land sliding and several independent variables (elevation, slope, contributing area, land use, geology, and terrain curvature) to create the susceptibility map. With six independent variables, the multiple logistic model susceptibility map tends to overpredict landslides at a 10 m pixel resolution. However, the model is statistically valid and able to predict 79.81% of the existing landslides. The implementation of a landslide inventory and susceptibility mapping techniques demonstrate the feasibility of the method for use in other volcanic areas of Mexico.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[GIS]]></kwd>
<kwd lng="en"><![CDATA[Geomorphologic Maps]]></kwd>
<kwd lng="en"><![CDATA[Landslide Inventory Map]]></kwd>
<kwd lng="en"><![CDATA[Landslide Susceptibility Map]]></kwd>
<kwd lng="en"><![CDATA[Multiple Logistics Regression]]></kwd>
<kwd lng="en"><![CDATA[Pico de Orizaba Volcano]]></kwd>
<kwd lng="es"><![CDATA[SIG]]></kwd>
<kwd lng="es"><![CDATA[cartografía geomorfológica]]></kwd>
<kwd lng="es"><![CDATA[mapa de inventario de deslizamientos]]></kwd>
<kwd lng="es"><![CDATA[mapa de susceptibilidad de deslizamientos]]></kwd>
<kwd lng="es"><![CDATA[regresión múltiple logística]]></kwd>
<kwd lng="es"><![CDATA[Volcán Pico de Orizaba]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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