Abstract

The historical landslide data in GIS (Geographic Information System) environment is valuable to estimate pattern in landslides distribution and frequency, which are useful for landslide hazard analysis and mitigation. By using the landslide reports released officially by The National Agency for Disaster Management (BNPB), those non-spatial data need to be converted into the spatial ones. The reports primarily contain location, date of event, impact and triggering factor. This study is exploring Google Maps which is a web mapping service to process the historical landslide data of Indonesia. By preparing historical landslide data in the form of spreadsheet, Google Maps directly can change the whole data into a custom map ‘landslide distribution map’. The attribute can be edited, the map can change interactively, and vice versa. The appearance of the custom map can be styled by a certain column so its statistical information comes up. A landslide distribution map produced in Google Maps can be shared to others and can be exported as a GIS layer for further analysis. This article shows the utilization of facilities provided by Google Maps to prepare and analyse the landslide inventory map.

Details

Title
Utilization of google maps for depicting landslide pattern in Indonesia
Author
Sukristiyanti, S 1 ; Wikantika, K 2 ; Sadisun, I A 3 ; Yayusman, L F 4 ; Pamela, P 5 

 Remote Sensing and GIS Research Group, Faculty of Earth Sciences and Technology, ITB, Bandung, Indonesia; Center for Remote Sensing, ITB, Bandung, Indonesia; Research Centre for Geotechnology, Indonesian Institute of Sciences (LIPI), Bandung, Indonesia 
 Remote Sensing and GIS Research Group, Faculty of Earth Sciences and Technology, ITB, Bandung, Indonesia; Center for Remote Sensing, ITB, Bandung, Indonesia 
 Applied Geology Research Group, Faculty of Earth Sciences and Technology, ITB, Bandung, Indonesia 
 Center for Remote Sensing, ITB, Bandung, Indonesia 
 Geological Agency of Indonesia, Bandung, Indonesia 
Publication year
2020
Publication date
Jun 2020
Publisher
IOP Publishing
ISSN
17551307
e-ISSN
17551315
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2555741387
Copyright
© 2020. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.