Abstract
Landslide spatial decision support systems (LS-DSS) are computer-based systems that combine the geographic storage, search, and retrieval capabilities of geographic information systems with the decision models and optimizing algorithms used to support decision-making for landslide problems. This study proposes an optimization process of region object-oriented classification (ROC) to analyze the landslide image information. The surface information from the Wan Da reservoir area is collected and studied. We collected different spectrum with several texture information to analyze the surrounding area of the Wan Da reservoir. ROC is used to classify the landslide area. Entropy-based classification is used as a classifier in ROC to determine the landslide/nonlandslide area. The parameters of S (similarity) and A (area) are used and then the best combinations are found. An optimize algorithm is developed to access the above variables to perform the best classification outcomes. The relations of occurrence vs. non-occurrence of landslide which are linked to the attributes of land surface are studied. An improved translation model (Expert Knowledge Translation Platform) is also presented to increase the accuracy. This could be of help to manage/monitor the landslide area near the reservoir.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
