Gabriel Legorreta Paulín

A GIS method for landslide inventory and susceptibility mapping in the Río El Estado watershed, Pico de Orizaba volcano, México

Abstract In volcanic terrains, dormant stratovolcanoes are very common and can trigger landslides and debris flows continually along stream systems, thereby affecting human settlements and economic activities. It is important to assess their potential impact and damage through the use of landslide inventory maps and landslide models. In Mexico, numerous geographic information systems (GIS)-based applications have been used to represent and assess slope stability. However, there is no practical and standardized landslide mapping methodology under a GIS. This work provides an overview of the ongoing research project from the Institute of Geography at the National Autonomous University of Mexico that seeks to conduct a multi-temporal landslide inventory and produce a landslide susceptibility map by using GIS. The Río El Estado watershed on the southwestern flank of Pico de Orizaba volcano, the highest mountain in Mexico, is selected as a study area. The geologic and geomorphologic factors in combination with high seasonal precipitation, high degree of weathering, and steep slopes predispose the study area to landslides. The method encompasses two main levels of analysis to assess landslide susceptibility. First, the project aims to derive a landslide inventory map from a representative sample of landslides using aerial orthophotographs and field work. Next, the landslide susceptibility is modelled by using multiple logistic regression implemented in a GIS platform. The technique and its implementation of each level in a GISs-based technology is presented and discussed.

Comparing landslide susceptibility models in the Río El Estado watershed on the SW flank of Pico de Orizaba volcano, Mexico

A comprehensive study of landslide susceptibility models is carried out in the Río El Estado watershed on the SW flank of Pico de Orizaba volcano. A detailed multitemporal landslide inventory map in the watershed is used as a framework for the quantitative comparison of three landslide susceptibility models. The first landslide susceptibility map is created by using the Stability Index MAPping model. The second and the third landslide susceptibility maps are created using multiple logistic regression (MLR) and multicriteria evaluation models. The validation of the resulting susceptibility maps is performed by comparing them with an inventory map in a contingency table and through the area under the receiver operating characteristic curve. The results point out that the models tend to over-predict and have a moderate to high match with the landslide areas. In this research, MLR is preferred over the other two models because MLR obtains similar or better results with fewer significant variables.

Landslide inventory mapping and landslide susceptibility modeling assessment on the SW flank of Pico de Orizaba volcano, Puebla-Veracruz, Mexico

Volcanic regions with stratovolcanoes and monogenetic fields are very common and have the potential to trigger along their stream systems landslides and debris flows that damage human settlements, industrial development, cattle raising, forestry, and agricultural activities. However, a practical and standardized landslide mapping methodology using GIS for landslides that occur continually along the stream systems in volcanic terrains has not been applied in Mexico. As a result, landslide inventory maps and related geo-databases that support the prediction of future slope instability in volcanic terrains are lacking. Also, little work has been done on the systematic comparison of different models to predict landslide susceptibility. In this study, a landslide inventory map is derived from a representative sample of landslides using multi-temporal aerial-photo-interpretation and field investigations. The stability is modeled using LOGISNET (Multiple Logistic Regression, Geographic Information System, and Neural Network) as a tool to compare and contrasts the advantages and limitations of two landslides susceptibility models: Stability Index MAPping (SINMAP) and Multiple Logistic Regression (MLR). Both models are embedded in LOGISNET to predict landslides and facilitate the analysis. The validations of the resulting susceptibility maps were performed by comparing them with the inventory map in a contingency table. This research uses the stream system of the Rio Chiquito-Barranca del Muerto watershed as a case-study area. The study area is located in the SW flank of Pico de Orizaba, Volcano, Veracruz-Puebla.

Gravitational Processes in the Eastern Flank of the Nevado de Toluca Mexico

Landslides in volcanic mountainous terrains covered by poorly consolidated materials are common in Mexico. This investigation illustrates the landslides and geomorphologic changes of debris flow deposits in the town of Santa Cruz Pueblo Nuevo, State of Mexico, by using a multicriteria analysis in Geographic Information Systems (GIS) to obtain a potential hazard map.

Landslide susceptibility of volcanic landforms in the Río El Estado watershed, Pico de Orizaba volcano, Mexico

Abstract The combination of high-quality landslide inventories and geomorphic attributes that can be derived and analyzed by geographic information systems can provide powerful and straightforward input into mapping landscape-wide landslide susceptibility. A methodology for generating landslide susceptibility maps can assist land managers in reducing risk to populations and economic land use from landslide hazards, particularly in areas prone to landslide disasters, such as tropical mountain ranges. Pico de Orizaba is the highest stratovolcano in Mexico, and throughout its geologic history, it has had large landslides triggered by flank collapse as well as small landslides triggered by high seasonal rainfall on terrains covered by poorly consolidated materials. The present work analyzes the distribution of small landslides embedded in volcanic landforms to characterize slope instability. The Río El Estado watershed on the southwestern flank of Pico de Orizaba volcano has been selected as a study area. In the area, landforms are ascertained through aerial photographs, field investigations, and an adaptation of the Landslide Hazard Zonation Protocol of the Washington State Department of Natural Resources, Forest Practices Division in a GIS-based technology. For each landform, a semi-quantitative overall susceptibility rating is derived by using the landslide area rate and the landslide frequency rate. This analysis divides the watershed into seven mass-wasting landforms that are assigned slope stability susceptibility ratings from low to very high. The overall susceptibility rating for this watershed is very high. The technique and its implementation are presented and discussed.

Assessing Landslide Frequency for Landform Hazard Zoning Purposes

This work provides an overview of the on-going research project (Grant PAPIIT, no. IB100412-RR180412 and IPL project #170) from the Institute of Geography at the National Autonomous University of Mexico (UNAM). The project seeks to conduct a multi-temporal landslide inventory, analyze the distribution of landslides, and characterize landforms that are prone to slope instability by using Geographic Information Systems (GIS). The study area is the Rio Chiquito-Barranca del Muerto watershed that covers 111 km2 and lies on the south-western flank of Pico de Orizaba volcano. The watershed was studied using aerial photographs, fieldwork, and adaptation of the Landslide Hazard Zonation Protocol of the Washington State Department of Natural Resources, USA. A total of 571 gravitational features were recognized, of six types: shallow landslides, debris-avalanche, deep-seated landslides, debris flows, earthflows, and rock falls. This analysis divided the watershed into 12 mass-wasting landforms on which gravitational processes occur: inner gorges, headwalls, active scarps of deep-seated landslides, meanders, plains, three types of hillslopes classified by their gradient (low, moderate, and high), rockfalls, non-rule-identified inner gorges, non-rule-identified headwalls, and non-rule-identified converging hillslopes. For each landform the landslide area rate and the landslide frequency rate were calculated, as well as the overall hazard rating. The slope-stability hazard rating has a range that goes from low to very high. The overall hazard rating for this watershed was very high.

TXT-tool 1.052-1.2: GIS Using Landslides Susceptibility Mapping Model for Volcanoes

This tool is a systematic methodology for making landslide susceptibility maps using GIS technology. The main goal of this tool is to provide the foundation for mapping landslides susceptibility per landforms in areas where there is little information. Derivation of landform units used classification of morphometric parameters, expert knowledge, field verification, and adaptation of the Landslide Hazard Zonation Protocol of the Washington State Department of Natural Resources, USA. For each landform the landslide area rate (LAR) and the landslide frequency rate (LFR) is calculated in order to determine the landslide susceptibility. The training area is along the stream system of Rio La Carbonera watershed on the SE flank of Pico de Orizaba volcano, Mexico.

TXT-tool 1.052-1.1 GIS Using Landslides Inventory Mapping for Volcanoes

This tool is a systematic method for carrying out a landslide inventory on Quaternary volcanoes. The goal of this tool is to provide the foundation for mapping landslides in volcanic areas using Geographic Information System (GIS). The mapping methodology uses aerial photographs, fieldwork, and adaptation of the Landslide Hazard Zonation Protocol of the Washington State Department of Natural Resources, USA to address the distribution, type, and abundance of landslides. The training area is along the Rio La Carbonera watershed on the SE flank of Pico de Orizaba volcano, Mexico. The area is predisposed to landslides due to physiographic conditions (loose volcanic materials and high seasonal rainfall) and decades of deforestation.

Mapping landforms for landslide hazards assessment on the SW flank of Pico de Orizaba volcano, Puebla-Veracruz, Mexico

Landslides that occur along stream systems are very common and have the potential to damage human settlements and economic activities. On the highest mountains in Mexico the potential for landslides and debris flows is great because of the large area of weakened rocks at high altitudes and under high seasonal rainfall. In Mexico, in spite of the effort to represent and assess slope stability by local authorities and scientists, there is a lack of standardized and systematized landslide inventory maps, landslide hazard maps, and related geo-databases that support the prediction of future slope instability. The present work illustrates a method to analyze the distribution of landslides and characterize landforms that are prone to slope instability. For the Río Chiquito-Barranca del Muerto watershed on the southwestern flank of Pico de Orizaba volcano, landforms and landslide distribution were ascertained through a landslide inventory map created from multi-temporal aerial photographs, field investigations and, an adaptation of the Landslide Hazard Zonation Protocol of the Washington State Department of Natural Resources, Forest Practices Division, in a GIS-based technology. This analysis divided the watershed into 12 mass-wasting landforms that were assigned slope-stability hazard ratings from low to very high. The overall hazard rating for this watershed was very high.

Introduction: Landslide Inventories and Databases

This is a short introduction to the Session B9 of the WLF3 entitled “Inventory and Database” with summarized overview of all contributions. Papers included in this part of the volume deals with landslide mapping and landslide identification techniques as well as with presentation of landslide inventories and data bases. There are examples of landslide identification and inventory development from Southern Kyrgyzstan, Mexico, Turkey and Croatia. Event and seasonal landslide inventories are presented in the form of Global Landslide Catalog and simple seasonal inventory from Croatia. National landslide databases encompass large archives of landslide data from Poland, Germany and Switzerland.