Evidence map›Paper›PMID 36643993›Full record

ArticleAgricultural and forest meteorology2022

Hyperspectral response of agronomic variables to background optical variability: Results of a numerical experiment.

Lin Gao, Roshanak Darvishzadeh, Ben Somers, Brian Alan Johnson, Yu Wang, Jochem Verrelst, Xiaofei Wang, Clement Atzberger

Open access · greenAbstract read
In one paragraph

Article in Agricultural and forest meteorology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
4.4field-weighted citation impact, top 5% 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

2 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. 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 at 7 institutions in 6 countries.

Lin GaoCollege of Geography and Environment, Shandong Normal University, Jinan 250014, China.
Roshanak DarvishzadehFaculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, 7500 AE Enschede, the Netherlands.
Ben SomersDivision Forest, Nature and Landscape, Department Earth and Environmental Sciences, KU Leuven, Celestijnenlaan 200E-2411, Leuven B-3001, Belgium.
Brian Alan JohnsonInstitute for Global Environmental Strategies, Hayama, Kanagawa 240-0115, Japan.
Yu WangSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China.
Jochem VerrelstImage Processing Laboratory (IPL), Parc Científic, Universitat de València, Paterna 46980, Spain.
Xiaofei WangCollege of Geography and Environment, Shandong Normal University, Jinan 250014, China.
Clement AtzbergerInstitute of Geomatics, University of Natural Resources and Life Sciences (BOKU), Vienna 1090, Austria.
Shandong Normal University · CNBOKU University · ATHenan Polytechnic University · CNInstitute for Global Environmental Strategies · JPKU Leuven · BEParc Científic de la Universitat de València · ESUniversity of Twente · NL

Funding

European Research Council 755617
6 · The paper itself

Abstract

Understanding how biophysical and biochemical variables contribute to the spectral characteristics of vegetation canopies is critical for their monitoring. Quantifying these contributions, however, remains difficult due to extraneous factors such as the spectral variability of canopy background materials, including soil/crop-residue moisture, soil-type, and non-photosynthetic vegetation (NPV). This study focused on exploring the spectral response of two important agronomic variables (1) leaf chlorophyll content (

Indexed as

Global sensitivity analysisHyperspectral responseLeaf area indexLeaf chlorophyll contentNon-photosynthetic vegetationSoil type

Identifiers

PMID36643993
PMCPMC7614047
OpenAlexW4297908040

What OpenQuestion holds

Textmetadata
LicenceTDM
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.