
High Mountain Asia Landslide Catalog, Version 1
Data set id:
HMA_LS_Cat
DOI: 10.5067/5ST0TZCD9RQ3
There is a more recent version of these data.
Version Summary
Version Summary
Initial release
Overview
This data set is an open global landslide inventory with input from citizen scientists. The data include the time and location of various landslide events, as well as event characteristics, such as triggers, the number of fatalities, country of occurrence, and the length and area of the slide.
Parameter(s):
LANDSLIDES
Platform(s):
GROUND-BASED OBSERVATIONS
Sensor(s):
MULTIPLE
Data Format(s):
Shapefile
Temporal Coverage:
- 10 February 1956 to 18 December 2018
Temporal Resolution:
- Varies
Spatial Resolution:
- varies
- varies
Spatial Reference System(s):
- WGS 84EPSG:4326
Spatial Coverage:
- N:72.7S:-46.8E:180W:-180
Blue outlined yellow areas on the map below indicate the spatial coverage for this data set.
Data Access & Tools
Documentation
User Guide
Help Articles
General Questions & FAQs
This article covers frequently asked questions about the NASA NSIDC DAAC's Earthdata cloud migration project and what it means to data users.
The NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) is migrating its primary data access from its legacy, on-premises archive to the NASA Earthdata Cloud.
How to Articles
This article shows how to download NSIDC DAAC data from NASA Earthdata Cloud to your computer using three tools: wget and curl—popular command-line utilities for downloading files—and Data Downloader, a Python-based command-line tool developed by the Physical Oceanography Distributed Active Archi
Many NSIDC DAAC data sets can be accessed using NSIDC DAAC's Data Access Tool. This tool provides the ability to search and filter data with spatial and temporal constraints using a map-based interface.Users have the option to:
The NASA Earthdata Cloud is the NASA cloud-based archive of Earth observations. It is hosted by Amazon Web Services (AWS). Learn how to find and access NSIDC DAAC data directly in the cloud.