Evidence map›Paper›PMID 39517785›Full record

ArticleSensors (Basel, Switzerland)2024

Space-Ground Remote Sensor Network for Monitoring Suspended Sediments in the Yellow River Basin.

Yingzhuo Hou, Yonggang Ma, Zheng Hou, Maham Arif, Jinghu Li, Xing Ming, Xinyue Liu, Qianguo Xing

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. 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

8 authors.

Yingzhuo HouCAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China.ORCID 0009-0005-6320-5171
Yonggang MaNingxia Hui Autonomous Region Hydrology and Water Resources Monitoring and Early Warning Center, Yinchuan 750001, China.
Zheng HouNingxia Hui Autonomous Region Hydrology and Water Resources Monitoring and Early Warning Center, Yinchuan 750001, China.
Maham ArifCAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China.
Jinghu LiCAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China.ORCID 0009-0004-6664-2492
Xing MingCollege of Physical Science and Technology, Hebei University, Baoding 071002, China.
Xinyue LiuCollege of Physical Science and Technology, Hebei University, Baoding 071002, China.
Qianguo XingCAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China.ORCID 0000-0002-9136-9051

Funding

Instrument Developing Project of the Chinese Academy of Sciences YJKYYQ20170048Key R&D Program of Ningxia Hui Autonomous Region, China 2023BEG02052Key R&D Program of Shandong Province, China 2022CXPT019National Natural Science Foundation of China 42076188Seed Project of Yantai Institute of Coastal Zone Research, Chinese Academy of Scienc-es YICE351030601
6 · The paper itself

Abstract

The Yellow River, China's second-largest river, is renowned for its high sediment content. In response to the potential impacts of climate change on Yellow River water resources and water environmental management, an advanced monitoring and forecasting system for water and sediment throughout the entire Yellow River basin-from its source to the sea-is urgently needed. In this paper, based on the current status of water and sediment monitoring technologies, we proposed an integrated remote sensing monitoring network that combines satellite remote sensing, drone remote sensing, and ground-based wireless automatic monitoring networks, aiming to achieve the digital monitoring of water and sediment across the entire Yellow River basin, from its upper reaches to its estuary in the Bohai Sea. By utilizing ground-based in situ hyperspectral stations for sediment source areas in the upper reaches, such as the Qingshui River basin in Ningxia, and satellite remote sensing for midstream processes in the Xiaolangdi reservoir before the flood season in 2023, as well as downstream monitoring at the Yellow River estuary, this paper demonstrates the novelty and efficiency of the space-air-ground integrated remote sensing monitoring technology.

Indexed as

ground hyperspectral stationsatellitesensor networksuspended sediment concentrationthe Yellow River

Identifiers

PMID39517785
PMCPMC11548588

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.