Journal cover Journal topic
Earth System Science Data The data publishing journal
Journal topic

Journal metrics

IF value: 9.197
IF 5-year value: 9.612
IF 5-year
CiteScore value: 12.5
SNIP value: 3.137
IPP value: 9.49
SJR value: 4.532
Scimago H <br class='widget-line-break'>index value: 48
Scimago H
h5-index value: 35
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  29 Jun 2020

29 Jun 2020

Review status
A revised version of this preprint was accepted for the journal ESSD.

Constructing a complete landslide inventory dataset for the 2018 Monsoon disaster in Kerala, India, for land use change analysis

Lina Hao1,2, Rajaneesh A.3, Cees van Westen2, Sajinkumar K. S.3,4, Tapas Ranjan Martha5, Pankaj Jaiswal6, and Brian McAdoo7 Lina Hao et al.
  • 1State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Faculty of Earth Sciences, Chengdu University of Technology, Chengdu, China
  • 2Faculty of Geoinformation Science and Earth Observation (ITC), University of Twente, Enschede, the Netherlands
  • 3Department of Geology, University of Kerala, Thiruvananthapuram 695581, Kerala, India
  • 4Department of Geological & Mining Engineering & Sciences, Michigan Technological University, USA
  • 5National Remote Sensing Centre, Indian Space Research Organisation, Hyderabad, India
  • 6Geological Survey of India (GSI)
  • 7Yale-NUS College, Singapore

Abstract. Event-based landslide inventories are important for analyzing the relationship between the intensity of the trigger (e.g. rainfall, earthquake) and the density of the landslides in a particular area, as a basis for the estimation of the landslide probability and the conversion of susceptibility maps into hazard maps required for risk assessment. They are also crucial for the establishment of local rainfall thresholds that are the basis of Early Warning Systems, and for evaluating which land use/land cover changes are related to landslide occurrence. The completeness and accuracy of event-based landslide inventories are crucial aspects to derive at reliable results or the above types of analysis. In this study we generated a relatively complete landslide inventory for the 2018 Monsoon landslide event in the state of Kerala, India, based on two inventories that were generated using different methods: one based on Object Based Image Analysis (OBIA) and the other on field surveys of damaging landslides. We used a collaborative mapping approach based on the visual interpretation of pre-and post-event high-resolution satellite images available in Google Earth, adjusted the two inventories and digitize landslides that were missed in the two inventories. The reconstructed landslide inventory database contains 4728 landslides consisting of 2477 landslides mapped by OBIA method, 973 landslides mapped by field survey, 422 landslides mapped both by OBIA and field method and an additional 856 landslides mapped using the visual image (GE) interpretation. The dataset is available at (van Westen, 2020). Also, the location of the landslides was adjusted, based on the image interpretation, and the initiation points were used to evaluate the land use/land cover changes as a causal factor for the 2018 Monsoon landslides. A total of 45 % of the landslides that damaged buildings occurred due to cut-slope failure while 34 % of those impacting on roads were due to road cut-slope failures. The resulting landslide inventory is made available for further studies.

Lina Hao et al.

Interactive discussion

Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Login for Authors/Topical Editors] [Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Lina Hao et al.

Data sets


Lina Hao et al.


Total article views: 253 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
136 86 31 253 28 27
  • HTML: 136
  • PDF: 86
  • XML: 31
  • Total: 253
  • BibTeX: 28
  • EndNote: 27
Views and downloads (calculated since 29 Jun 2020)
Cumulative views and downloads (calculated since 29 Jun 2020)

Viewed (geographical distribution)

Total article views: 244 (including HTML, PDF, and XML) Thereof 243 with geography defined and 1 with unknown origin.
Country # Views %
  • 1



No saved metrics found.


No discussed metrics found.
Latest update: 30 Sep 2020
Short summary
Kerala in India was impacted by an extreme rainfall event in the Monsoon season of 2018, which triggered extensive floods, and landslides. In order to study whether the landslides were related with recent land use changes, we generated an accurate and almost complete landslide inventory based on two existing datasets and detailed interpretation of images in the Google Earth platform. The final dataset contains 4728 landslides with attributes of land use in 2010, and land use in 2018, etc.
Kerala in India was impacted by an extreme rainfall event in the Monsoon season of 2018, which...