Evidence map›Paper›PMID 36778148›Full record

ArticlePeerJ2023

Remote sensing technology for rapid extraction of burned areas and ecosystem environmental assessment.

Shiqi Zhang, Maoyang Bai, Xiao Wang, Xuefeng Peng, Ailin Chen, Peihao Peng

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2023. 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
1.9field-weighted citation impact, top 15% of its field
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, 12 citations in OpenAlex.

  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

6 authors at 3 institutions in 1 country.

Shiqi ZhangCollege of Earth Sciences, Chengdu University of Technology, Chengdu, China.
Maoyang BaiCollege of Earth Sciences, Chengdu University of Technology, Chengdu, China.
Xiao WangSchool of Architecture and Civil Engineering, Chengdu University, Chengdu, China.
Xuefeng PengCollege of Tourism and Urban-Rural Planning, Chengdu University of Technology, Chengdu, China.
Ailin ChenSichuan Earthquake Agency, Chengdu, China.
Peihao PengCollege of Earth Sciences, Chengdu University of Technology, Chengdu, China.
Chengdu University of Technology · CNChengdu University · CNHeilongjiang Earthquake Agency · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Forest fires are one of the significant disturbances in forest ecosystems. It is essential to extract burned areas rapidly and accurately to formulate forest restoration strategies and plan restoration plans. In this work, we constructed decision trees and used a combination of differential normalized burn ratio (dNBR) index and OTSU threshold method to extract the heavily and mildly burned areas. The applicability of this method was evaluated with three fires in Muli County, Sichuan, China, and we concluded that the extraction accuracy of this method could reach 97.69% and 96.37% for small area forest fires, while the extraction accuracy was lower for large area fires, only 89.32%. In addition, the remote sensing environment index (RSEI) was used to evaluate the ecological environment changes. It analyzed the change of the RSEI level through the transition matrix, and all three fires showed that the changes in RSEI were stronger for heavily burned areas than for mildly burned areas, after the forest fire the ecological environment (RSEI) was reduced from good to moderate. These results realized the quantitative evaluation and dynamic evaluation of the ecological environment condition, providing an essential basis for the restoration, decision making and management of the affected forests.

Indexed as

BurnsEcosystemEnvironmental MonitoringForestsHumansRemote Sensing TechnologyBurned areasForest fireGEE platformOTSU thresholdRemote sensing environment indexSentinel-2

Identifiers

PMID36778148
PMCPMC9910190
OpenAlexW4319318087

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.