Evidence map›Paper›PMID 41433003›Full record

ArticleCarbon balance and management2025

Modeling neighborhood association decay effects improves forest stock volume estimation using UAV lidar and optical data.

Zilong Qin, Jinling Fang, Na Jiang, Ke Hou, Zongyao Sha

Abstract read
In one paragraph

Article in Carbon balance and management, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Zilong Qin *School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, Hubei, China. zilongqin@whu.edu.cn.
Jinling FangWuhan Geomatics Institute, Wuhan, 430079, Hubei, China.
Na JiangShandong Provincial Institute of Land Surveying and Mapping, Jinan, 250102, Shandong, China.
Ke HouShandong Provincial Institute of Land Surveying and Mapping, Jinan, 250102, Shandong, China.
Zongyao Sha *School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Forest stock volume (FSV) is an important indicator for assessing the carbon sequestration potential of forests and is influenced by neighborhood environmental factors. However, most studies have disregarded the spatial neighborhood association of the modeled variables and its decay effect with increasing spatial distance in estimating the FSV. We propose an FSV estimation method that considers the neighborhood association decay (NAD) effect, that is, NAD-based FSV modelling, and constructed a framework for expressing and quantifying the NAD effect, specifically including the design of NAD models, determination of the optimal neighborhood size, and optimization of the NAD strategy. Finally, we estimated the FSV of the dominant tree species using UAV LiDAR and optical remote sensing data from Mengyin County, China, and evaluated the estimated results using field sample data. The results suggest that the proposed NAD-based model can effectively improve the accuracy of FSV estimation for each tree species (R

Indexed as

Forest stock volumeMulti-source dataNeighborhood associationSpatial decay effect

Identifiers

PMID41433003
PMCPMC12866329

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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.