Landslide Susceptibility Mapping at Hoa Binh Province (Vietnam) using an Adaptive Neuro-fuzzy Inference System and GIS

Computers & GeosciencesComputers & Geosciences, Volume 45, August 2012, Pages 199–211

Dieu Tien Bui, Biswajeet Pradhan, Owe Lofman, Inge Revhaug, and Oystein B. Dick

“The objective of this study is to investigate a potential application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Geographic Information System (GIS) as a relatively new approach for landslide susceptibility mapping in the Hoa Binh province of Vietnam. Firstly, a landslide inventory map with a total of 118 landslide locations was constructed from various sources. Then the landslide inventory was randomly split into a testing dataset 70% (82 landslide locations) for training the models and the remaining 30% (36 landslides locations) was used for validation purpose. Ten landslide conditioning factors such as slope, aspect, curvature, lithology, land use, soil type, rainfall, distance to roads, distance to rivers, and distance to faults were considered in the analysis. The hybrid learning algorithm and six different membership functions (Gaussmf, Gauss2mf, Gbellmf, Sigmf, Dsigmf, Psigmf) were applied to generate the landslide susceptibility maps.

Landslide inventory of the study area.

Landslide inventory of the study area.

“The validation dataset, which was not considered in the ANFIS modeling process, was used to validate the landslide susceptibility maps using the prediction rate method. The validation results showed that the area under the curve (AUC) for six ANFIS models vary from 0.739 to 0.848. It indicates that the prediction capability depends on the membership functions used in the ANFIS. The models with Sigmf (0.848) and Gaussmf (0.825) have shown the highest prediction capability. The results of this study show that landslide susceptibility mapping in the Hoa Binh province of Vietnam using the ANFIS approach is viable. As far as the performance of the ANFIS approach is concerned, the results appeared to be quite satisfactory, the zones determined on the map being zones of relative susceptibility.”

URISA Announces 2012 Exemplary Systems in Government Award Winners

URISAURISA is pleased to announce the recipients of 2012 URISA Exemplary Systems in Government (ESIG) Awards. Since 1980, URISA’s ESIG Awards have recognized exceptional achievements in the application of information technology that have improved the delivery and quality of government services. URISA congratulates all of the participants in the 2012 Exemplary Systems in Government Award program. The recognized systems will be celebrated during the Awards Breakfast at GIS-Pro 2012: URISA’s 50th Annual Conference in Portland. This year’s competition resulted in two exemplary systems in the Enterprise Systems category and one distinguished system.

ENTERPRISE SYSTEMS – Systems in this category are outstanding and working examples of using information systems technology in a multi-department environment as part of an integrated process. These systems exemplify effective use of technology yielding widespread improvements in the process(es) and/or service(s) involved and/or cost savings to the organization.

2012 ESIG Winners:

  • Orange County’s Addressing and Land Development Information Network (ALADIN)
    Submitted by Louis Schoolkate, Orange County GIS Coordinator, Orlando, Florida

This solution was deemed exemplary by the ESIG Review Committee because it not only integrates GIS into addressing, zoning, document management and land development systems, but it also integrates GIS into the daily workflows of management and front-line staff to facilitate decision-making. Aladin further exemplifies success in the way it enables Orange County, the world’s number one tourist destination, to not only support its permanent population of one million, but it also allows the County to meet the annual demands and expectations presented by 52 million tourists.  Orange County, like many government agencies over the past years, has had to deal with annual budget cuts and staffing reductions.  Aladin, because of the efficiencies built into its workflows, enables County staff to continue to deliver the same level of customer service with fewer resources.  Projects like Aladin, and Orange County’s vision to pursue integrated enterprise GIS systems, exemplify excellence in GIS.  The Aladin system developed by Orange County is a strong example of successful GIS integration and a model for URISA to share.

  • PSMA Australia’s PSMA System
    Submitted by: Kate Mann, Communications Manager, PSMA Australia, Griffith ACT Australia

This solution was deemed exemplary by the ESIG Review Committee because it involves the engagement, collaboration and partnership between all government in Australia, including federal, six state and two territorial governments, in the delivery of a single system for the creating and facilitating access to national datasets for government, industry and community use. The provision of GIS data by the PSMA system isn’t just a cool GIS project, it actually has a significant impact on the country as a whole as it contributes to a variety of economic, social and environmental benefits.  The PSMA system was developed with the intention of being a world-class system that enables the collection, standardization, integration, manipulation and delivery of GIS data in an automated fashion.  The example of inter-government collaboration and the scale in which PSMA operates and because the PSMA system has revolutionized the manner in which data is gathered, integrated and disseminated make it an exemplary system.

2012 Distinguished System:

  • Will County Master Address Point System
    Submitted by Tong Zhou, Director – GIS Department, County of Will, Joliet, Illinois

URISA congratulates all of the participants in the 2012 Exemplary Systems in Government Award program. For more information and to read each winning and distinguished system submission, visit

All of these systems will be celebrated during the Awards Breakfast at GIS-Pro 2012: URISA’s 50th Annual Conference in Portland, Oregon on October 3, 2012.

[Source: URISA press release]

Esri and PCI Geomatics Imagery Grant Program to Support Natural Resources Management

Esri logoGIS and Imagery Software, Data, and Training to Be Awarded for Natural Resources Analysis Projects

Esri, PCI Geomatics, MDA, and RapidEye today announced their new Natural Resources Imagery Grant Program. The grant program will provide software, data, and training for detecting and analyzing land-cover change through the combined use of geographic information system (GIS), image processing, and remote-sensing technologies.

Designed to foster innovative approaches that solve natural resources management problems, the Natural Resources Imagery Grant Program will provide 20 grants valued at $100,000 each. The grant includes the following:

  • Esri GIS software and training
  • PCI Geomatics imagery processing and analysis software and training
  • MDA RADARSAT-2 synthetic aperture radar (SAR) imagery
  • RapidEye 5-meter multispectral imagery

“GIS and image processing are mission-critical technologies in natural resources management,” said Jack Dangermond, president, Esri. “This grant opportunity will help organizations expand their existing imagery or GIS infrastructure and more efficiently support sustainable land-use management.”

Companies, educational institutions, nongovernmental organizations (NGOs), state and regional governments, or tribal governments within the United States may apply. Eligible projects are those that focus on remotely sensed imagery beyond the visible spectrum. Preferred projects will also demonstrate increased efficiency, productivity, or accuracy.

“Technology leaders and innovators should be presented with opportunities to advance their resources projects,” said Terry Maloney, president and CEO, PCI Geomatics. “This imagery grant program will bring solutions to the natural resources industries through inventive and operational use of satellite imagery.”

Applications for the Natural Resources Imagery Grant Program will be accepted beginning in September 2012 and ending November 16, 2012. Learn more at

[Source: Esri press release]