Evidence map›Paper›PMID 28256522›Full record

ArticleScientific reports2017

Formation of the 2015 Shenzhen landslide as observed by SAR shape-from-shading.

Chisheng Wang, Qingquan Li, Jiasong Zhu, Wei Gao, Xinjian Shan, Jun Song, Xiaoli Ding

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Chisheng WangShenzhen Key Laboratory of Spatial Smart Sensing and Services and the Key Laboratory for Geo-Environment Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation, Shenzhen University, Shenzhen, Guangdong, China.
Qingquan LiShenzhen Key Laboratory of Spatial Smart Sensing and Services and the Key Laboratory for Geo-Environment Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation, Shenzhen University, Shenzhen, Guangdong, China.
Jiasong ZhuShenzhen Key Laboratory of Spatial Smart Sensing and Services and the Key Laboratory for Geo-Environment Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation, Shenzhen University, Shenzhen, Guangdong, China.
Wei GaoShenzhen Integrated Geotechnical Investigation and Surveying Co., Ltd., Shenzhen, China.
Xinjian ShanState Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration, Beijing, China.
Jun SongShenzhen Integrated Geotechnical Investigation and Surveying Co., Ltd., Shenzhen, China.
Xiaoli DingThe Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The time-series topography change of a landfill site before its failure has rarely been surveyed in detail. However, this information is important for both landfill management and early warning of landslides. Here, we take the 2015 Shenzhen landslide as an example, and we use the radar shape-from-shading (SFS) technique to retrieve time-series digital elevation models of the landfill. The results suggest that the total filling volume reached 4,074,300 m

Identifiers

PMID28256522
PMCPMC5335704

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.