Data · dataset · 2026
Rainfall Event and Landslide Triggering Dataset from Automatic Rainfall Stations in Guangdong Province, China (2018-2023)
Listed in ScienceDB
This dataset contains 57,438 rainfall event records (including 284 landslide-triggering events) from 361 automatic rainfall stations in Guangdong Province, China, covering the period from July 2018 to October 2023.
Description
Rainfall events were delineated using the CTRL-T method (an adaptive event segmentation approach based on the statistical distribution of dry spell durations), with season-specific thresholds applied: 48 hours for the wet season (April–September) and 96 hours for the dry season (October–March), in accordance with Guangdong's subtropical monsoon climate.Each record contains the following fields: anonymized station ID (StationID; original hydrological station codes have been de-identified, coded S001–S361), event start time (Event_Start), event end time (Event_End), duration in hours (Duration_Hours), cumulative event rainfall in millimeters (Total_Rainfall_mm), binary landslide triggering label (Is_Triggering_Event; 0 = non-triggering, 1 = triggering), triggering confidence score (Trigger_Confidence; range 0–1), and associated landslide count (Landslide_Count).This dataset is the supporting data associated with: Yuan et al., "Spatiotemporal landslide early warning model for South China based on CTRL-T rainfall event identification and deep learning," Acta Geographica Sinica, Vol. 81, No. 5, 2026.
It can be used for training and validation of rainfall-induced landslide early warning models and related research.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.j00100.00047 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.j00100.00047 | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |