scholarly journals Analysis of Landslide Mapping With Multicopter in Somangari, Kaligesing, Purworejo, Central of Java

2021 ◽  
Vol 1908 (1) ◽  
pp. 012019
Author(s):  
Indreswari Suroso ◽  
Erwan Eko Prasetiyo
Keyword(s):  
2020 ◽  
Author(s):  
Matthew C. Morriss ◽  
◽  
Richard E. Giraud ◽  
Greg N. McDonald

Geomorphology ◽  
2014 ◽  
Vol 223 ◽  
pp. 45-60 ◽  
Author(s):  
Federica Bardi ◽  
William Frodella ◽  
Andrea Ciampalini ◽  
Silvia Bianchini ◽  
Chiara Del Ventisette ◽  
...  
Keyword(s):  

2015 ◽  
Vol 15 (9) ◽  
pp. 2111-2126 ◽  
Author(s):  
M. Santangelo ◽  
I. Marchesini ◽  
F. Bucci ◽  
M. Cardinali ◽  
F. Fiorucci ◽  
...  

Abstract. Landslide inventory maps (LIMs) show where landslides have occurred in an area, and provide information useful to different types of landslide studies, including susceptibility and hazard modelling and validation, risk assessment, erosion analyses, and to evaluate relationships between landslides and geological settings. Despite recent technological advancements, visual interpretation of aerial photographs (API) remains the most common method to prepare LIMs. In this work, we present a new semi-automatic procedure that makes use of GIS technology for the digitization of landslide data obtained through API. To test the procedure, and to compare it to a consolidated landslide mapping method, we prepared two LIMs starting from the same set of landslide API data, which were digitized (a) manually adopting a consolidated visual transfer method, and (b) adopting our new semi-automatic procedure. Results indicate that the new semi-automatic procedure (a) increases the interpreter's overall efficiency by a factor of 2, (b) reduces significantly the subjectivity introduced by the visual (manual) transfer of the landslide information to the digital database, resulting in more accurate LIMs. With the new procedure, the landslide positional error decreases with increasing landslide size, following a power-law. We expect that our work will help adopt standards for transferring landslide information from the aerial photographs to a digital landslide map, contributing to the production of accurate landslide maps.


Landslides ◽  
2020 ◽  
Vol 17 (10) ◽  
pp. 2271-2285 ◽  
Author(s):  
Benjamin B. Mirus ◽  
Eric S. Jones ◽  
Rex L. Baum ◽  
Jonathan W. Godt ◽  
Stephen Slaughter ◽  
...  

Abstract Detailed information about landslide occurrence is the foundation for advancing process understanding, susceptibility mapping, and risk reduction. Despite the recent revolution in digital elevation data and remote sensing technologies, landslide mapping remains resource intensive. Consequently, a modern, comprehensive map of landslide occurrence across the United States (USA) has not been compiled. As a first step toward this goal, we present a national-scale compilation of existing, publicly available landslide inventories. This geodatabase can be downloaded in its entirety or viewed through an online, searchable map, with parsimonious attributes and direct links to the contributing sources with additional details. The mapped spatial pattern and concentration of landslides are consistent with prior characterization of susceptibility within the conterminous USA, with some notable exceptions on the West Coast. Although the database is evolving and known to be incomplete in many regions, it confirms that landslides do occur across the country, thus highlighting the importance of our national-scale assessment. The map illustrates regions where high-quality mapping has occurred and, in contrast, where additional resources could improve confidence in landslide characterization. For example, borders between states and other jurisdictions are quite apparent, indicating the variation in approaches to data collection by different agencies and disparity between the resources dedicated to landslide characterization. Further investigations are needed to better assess susceptibility and to determine whether regions with high relief and steep topography, but without mapped landslides, require further landslide inventory mapping. Overall, this map provides a new resource for accessing information about known landslides across the USA.


2018 ◽  
Vol 9 (1) ◽  
pp. 544-567 ◽  
Author(s):  
M. Alvioli ◽  
A. C. Mondini ◽  
F. Fiorucci ◽  
M. Cardinali ◽  
I. Marchesini

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