Combining crop modelling and remote sensing to create yield maps for management zone delineation in small scale farming systems

H. Zha; D. Cammarano; L. Wilson; Y. Li; W. D. Batchelor; Y. Miao

doi:10.3920/978-90-8686-888-9_109

Combining crop modelling and remote sensing to create yield maps for management zone delineation in small scale farming systems

H. Zha, D. Cammarano, L. Wilson, Y. Li, W. D. Batchelor, Y. Miao

Soil, Water, and Climate

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

The objective of this study was to develop a management zone delineation strategy using reconstruction of yield maps with crop modelling and remote sensing data. Wangzhuang Village in Quzhou County (China), with an average farm size of 0.3 to 0.5 ha, was selected for this study. Satellite images, detailed soil nutrient samples from fields in the village and satellite-derived soil brightness images were available. Their integration allowed for the delineation of management zones at the village level.

Original language	English (US)
Title of host publication	Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019
Editors	John V. Stafford
Publisher	Wageningen Academic Publishers
Pages	883-889
Number of pages	7
ISBN (Electronic)	9789086863372
DOIs	https://doi.org/10.3920/978-90-8686-888-9_109
State	Published - 2019
Event	12th European Conference on Precision Agriculture, ECPA 2019 - Montpellier, France Duration: Jul 8 2019 → Jul 11 2019

Publication series

Name	Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019

Conference

Conference	12th European Conference on Precision Agriculture, ECPA 2019
Country/Territory	France
City	Montpellier
Period	7/8/19 → 7/11/19

Bibliographical note

Funding Information:
This project was funded by the ACTNN+ Network, the National Basic Research Program (2015CB150405), and Norwegian Ministry of Foreign Afairs (SINOGRAIN II, CHN-17/0019). We thank Prof. Hu Kelin and Li Baoguo from China Agricultural University and Dr Yong He from the Chinese Academy of Agricultural Science for providing the spatial soil texture information of the Village. We thank the anonymous reviewers for the feedback provided.

Publisher Copyright:
© Wageningen Academic Publishers 2019

Keywords

Crop model
Fertilization
Management zones
Remote sensing

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access

10.3920/978-90-8686-888-9_109

OpenUrl availability

Full text

Cite this

Zha, H., Cammarano, D., Wilson, L., Li, Y., Batchelor, W. D., & Miao, Y. (2019). Combining crop modelling and remote sensing to create yield maps for management zone delineation in small scale farming systems. In J. V. Stafford (Ed.), Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019 (pp. 883-889). (Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-888-9_109

Combining crop modelling and remote sensing to create yield maps for management zone delineation in small scale farming systems. / Zha, H.; Cammarano, D.; Wilson, L. et al.
Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019. ed. / John V. Stafford. Wageningen Academic Publishers, 2019. p. 883-889 (Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zha, H, Cammarano, D, Wilson, L, Li, Y, Batchelor, WD & Miao, Y 2019, Combining crop modelling and remote sensing to create yield maps for management zone delineation in small scale farming systems. in JV Stafford (ed.), Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019. Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019, Wageningen Academic Publishers, pp. 883-889, 12th European Conference on Precision Agriculture, ECPA 2019, Montpellier, France, 7/8/19. https://doi.org/10.3920/978-90-8686-888-9_109

Zha H, Cammarano D, Wilson L, Li Y, Batchelor WD, Miao Y. Combining crop modelling and remote sensing to create yield maps for management zone delineation in small scale farming systems. In Stafford JV, editor, Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019. Wageningen Academic Publishers. 2019. p. 883-889. (Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019). doi: 10.3920/978-90-8686-888-9_109

Zha, H. ; Cammarano, D. ; Wilson, L. et al. / Combining crop modelling and remote sensing to create yield maps for management zone delineation in small scale farming systems. Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019. editor / John V. Stafford. Wageningen Academic Publishers, 2019. pp. 883-889 (Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019).

@inproceedings{ff39792600584cc09244c3070ff5267e,

title = "Combining crop modelling and remote sensing to create yield maps for management zone delineation in small scale farming systems",

abstract = "The objective of this study was to develop a management zone delineation strategy using reconstruction of yield maps with crop modelling and remote sensing data. Wangzhuang Village in Quzhou County (China), with an average farm size of 0.3 to 0.5 ha, was selected for this study. Satellite images, detailed soil nutrient samples from fields in the village and satellite-derived soil brightness images were available. Their integration allowed for the delineation of management zones at the village level.",

keywords = "Crop model, Fertilization, Management zones, Remote sensing",

author = "H. Zha and D. Cammarano and L. Wilson and Y. Li and Batchelor, {W. D.} and Y. Miao",

note = "Funding Information: This project was funded by the ACTNN+ Network, the National Basic Research Program (2015CB150405), and Norwegian Ministry of Foreign Afairs (SINOGRAIN II, CHN-17/0019). We thank Prof. Hu Kelin and Li Baoguo from China Agricultural University and Dr Yong He from the Chinese Academy of Agricultural Science for providing the spatial soil texture information of the Village. We thank the anonymous reviewers for the feedback provided. Publisher Copyright: {\textcopyright} Wageningen Academic Publishers 2019; 12th European Conference on Precision Agriculture, ECPA 2019 ; Conference date: 08-07-2019 Through 11-07-2019",

year = "2019",

doi = "10.3920/978-90-8686-888-9_109",

language = "English (US)",

series = "Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019",

publisher = "Wageningen Academic Publishers",

pages = "883--889",

editor = "Stafford, {John V.}",

booktitle = "Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019",

}

TY - GEN

T1 - Combining crop modelling and remote sensing to create yield maps for management zone delineation in small scale farming systems

AU - Zha, H.

AU - Cammarano, D.

AU - Wilson, L.

AU - Li, Y.

AU - Batchelor, W. D.

AU - Miao, Y.

N1 - Funding Information: This project was funded by the ACTNN+ Network, the National Basic Research Program (2015CB150405), and Norwegian Ministry of Foreign Afairs (SINOGRAIN II, CHN-17/0019). We thank Prof. Hu Kelin and Li Baoguo from China Agricultural University and Dr Yong He from the Chinese Academy of Agricultural Science for providing the spatial soil texture information of the Village. We thank the anonymous reviewers for the feedback provided. Publisher Copyright: © Wageningen Academic Publishers 2019

PY - 2019

Y1 - 2019

N2 - The objective of this study was to develop a management zone delineation strategy using reconstruction of yield maps with crop modelling and remote sensing data. Wangzhuang Village in Quzhou County (China), with an average farm size of 0.3 to 0.5 ha, was selected for this study. Satellite images, detailed soil nutrient samples from fields in the village and satellite-derived soil brightness images were available. Their integration allowed for the delineation of management zones at the village level.

AB - The objective of this study was to develop a management zone delineation strategy using reconstruction of yield maps with crop modelling and remote sensing data. Wangzhuang Village in Quzhou County (China), with an average farm size of 0.3 to 0.5 ha, was selected for this study. Satellite images, detailed soil nutrient samples from fields in the village and satellite-derived soil brightness images were available. Their integration allowed for the delineation of management zones at the village level.

KW - Crop model

KW - Fertilization

KW - Management zones

KW - Remote sensing

UR - http://www.scopus.com/inward/record.url?scp=85073479115&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85073479115&partnerID=8YFLogxK

U2 - 10.3920/978-90-8686-888-9_109

DO - 10.3920/978-90-8686-888-9_109

M3 - Conference contribution

AN - SCOPUS:85073479115

T3 - Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019

SP - 883

EP - 889

BT - Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019

A2 - Stafford, John V.

PB - Wageningen Academic Publishers

T2 - 12th European Conference on Precision Agriculture, ECPA 2019

Y2 - 8 July 2019 through 11 July 2019

ER -

Combining crop modelling and remote sensing to create yield maps for management zone delineation in small scale farming systems

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access

OpenUrl availability

Other files and links

Fingerprint

Cite this