Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/23088
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jin, Xiuliang | en |
dc.contributor.author | Kumar, Lalit | en |
dc.contributor.author | Li, Zhenhai | en |
dc.contributor.author | Feng, Haikuan | en |
dc.contributor.author | Xu, Xingang | en |
dc.contributor.author | Yang, Guijun | en |
dc.contributor.author | Wang, Jihua | en |
dc.date.accessioned | 2018-05-24T14:23:00Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | European Journal of Agronomy, v.92, p. 141-152 | en |
dc.identifier.issn | 1873-7331 | en |
dc.identifier.issn | 1161-0301 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/23088 | - |
dc.description.abstract | Timely and accurate estimation of crop yield before harvest to allow crop yields management decision-making at a regional scale is crucial for national food policy and security assessments. Modeling dynamic change of crop growth is of great help because it allows researchers to determine crop management strategies for maximizing crop yield. Remote sensing is often used to provide information about important canopy state variables for crop models of large regions. Crop models and remote sensing techniques have been combined and applied in crop yield estimation on a regional scale or worldwide based on the simultaneous development of crop models and remote sensing. Many studies have proposed models for estimating canopy state variables and soil properties based on remote sensing data and assimilating these estimated canopy state variables into crop models. This paper, firstly, summarizes recent developments of crop models, remote sensing technology, and data assimilation methods. Secondly, it compares the advantages and disadvantages of different data assimilation methods (calibration method, forcing method, and updating method) for assimilating remote sensing data into crop models and analyzes the impacts of different error sources on the different parts of the data assimilation chain in detail. Finally, it provides some methods that can be used to reduce the different errors of data assimilation and presents further opportunities and development direction of data assimilation for future studies. This paper presents a detailed overview of the comparative introduction, latest developments and applications of crop models, remote sensing techniques, and data assimilation methods in the growth status monitoring and yield estimation of crops. In particular, it discusses the impacts of different error sources on the different portions of the data assimilation chain in detail and analyzes how to reduce the different errors of data assimilation chain. The literature shows that many new satellite sensors and valuable methods have been developed for the retrieval of canopy state variables and soil properties from remote sensing data for assimilating the retrieved variables into crop models. Additionally, new proposed or modified crop models have been reported for improving the simulated canopy state variables and soil properties of crop models. In short, the data assimilation of remote sensing and crop models have the potential to improve the estimation accuracy of canopy state variables, soil properties and yield based on these new technologies and methods in the future. | en |
dc.language | en | en |
dc.publisher | Elsevier BV | en |
dc.relation.ispartof | European Journal of Agronomy | en |
dc.title | A review of data assimilation of remote sensing and crop models | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.1016/j.eja.2017.11.002 | en |
dc.subject.keywords | Photogrammetry and Remote Sensing | en |
dc.subject.keywords | Agronomy | en |
dc.subject.keywords | Geospatial Information Systems | en |
local.contributor.firstname | Xiuliang | en |
local.contributor.firstname | Lalit | en |
local.contributor.firstname | Zhenhai | en |
local.contributor.firstname | Haikuan | en |
local.contributor.firstname | Xingang | en |
local.contributor.firstname | Guijun | en |
local.contributor.firstname | Jihua | en |
local.subject.for2008 | 070302 Agronomy | en |
local.subject.for2008 | 090905 Photogrammetry and Remote Sensing | en |
local.subject.for2008 | 090903 Geospatial Information Systems | en |
local.subject.seo2008 | 960904 Farmland, Arable Cropland and Permanent Cropland Land Management | en |
local.profile.school | School of Environmental and Rural Science | en |
local.profile.email | lkumar@une.edu.au | en |
local.output.category | C1 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.identifier.epublicationsrecord | une-20180523-122039 | en |
local.publisher.place | Netherlands | en |
local.format.startpage | 141 | en |
local.format.endpage | 152 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 92 | en |
local.contributor.lastname | Jin | en |
local.contributor.lastname | Kumar | en |
local.contributor.lastname | Li | en |
local.contributor.lastname | Feng | en |
local.contributor.lastname | Xu | en |
local.contributor.lastname | Yang | en |
local.contributor.lastname | Wang | en |
dc.identifier.staff | une-id:lkumar | en |
local.profile.orcid | 0000-0002-9205-756X | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:23272 | en |
local.identifier.handle | https://hdl.handle.net/1959.11/23088 | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | A review of data assimilation of remote sensing and crop models | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.search.author | Jin, Xiuliang | en |
local.search.author | Kumar, Lalit | en |
local.search.author | Li, Zhenhai | en |
local.search.author | Feng, Haikuan | en |
local.search.author | Xu, Xingang | en |
local.search.author | Yang, Guijun | en |
local.search.author | Wang, Jihua | en |
local.uneassociation | Unknown | en |
local.identifier.wosid | 000418967900015 | en |
local.year.published | 2018 | en |
local.fileurl.closedpublished | https://rune.une.edu.au/web/retrieve/84e9b948-e0ac-46de-907d-3efe879d5d30 | en |
local.subject.for2020 | 300403 Agronomy | en |
local.subject.for2020 | 401304 Photogrammetry and remote sensing | en |
local.subject.for2020 | 401302 Geospatial information systems and geospatial data modelling | en |
local.subject.seo2020 | 180603 Evaluation, allocation, and impacts of land use | en |
local.subject.seo2020 | 180607 Terrestrial erosion | en |
Appears in Collections: | Journal Article School of Environmental and Rural Science |
Files in This Item:
File | Description | Size | Format |
---|
SCOPUSTM
Citations
331
checked on Mar 30, 2024
Page view(s)
1,640
checked on Mar 24, 2024
Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.