Modelling Leaf Chlorophyll Content in Coffee (Coffea Arabica) Plantations Using Sentinel 2 Msi Data

Abel Chemura; Onisimo Mutanga; John Odindi

doi:10.1109/IGARSS.2018.8518848

Modelling Leaf Chlorophyll Content in Coffee (Coffea Arabica) Plantations Using Sentinel 2 Msi Data

Abel Chemura
, Onisimo Mutanga
, John Odindi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

2 Citations (Scopus)

Abstract

Coffee leaf chlorophyll (ChI) is an important proxy for coffee plant photosynthetic rates, nitrogen content, leaf health and yield potential. Whereas the recently launched Sentinel 2 multi -spectral instrument (MSI) data has great potential for plant condition assessment, the value of its spectral settings at variable spatial resolutions in relation to crop canopy cover on ChI content prediction remains largely unexplored. In this study, we apply an empirical model to estimate coffee leaf ChI with Sentinel 2 MSI data. Results showed that coffee biophysical parameters (height and canopy cover) are significantly influenced by stand age while plant water concentration and total ChI are age invariant. Results further showed that the best modelling results (R2=0.69, RMSE=64.4) were achieved when all the bands at 10m spatial resolution with all data were used. We concluded that Sentinel 2 MSI is a valuable dataset for predicting coffee leaf ChI, however, based on our findings, we suggest that finer spatial resolutions of 10m on mature coffee stands should be adopted for better prediction results.

Original language	English
Title of host publication	IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
Publisher	IEEE
Pages	8228-8231
Number of pages	4
ISBN (Electronic)	9781538671504
ISBN (Print)	978-1-5386-7151-1
DOIs	https://doi.org/10.1109/IGARSS.2018.8518848
Publication status	Published - 31 Oct 2018
Externally published	Yes
Event	38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018: Observing, Understanding and Forcasting the Dynamics of Our Planet - Feria Valencia Convention & Exhibition Center, Valencia, Spain Duration: 22 Jul 2018 → 27 Jul 2018 Conference number: 38 https://www.igarss2018.org/

Conference

Conference	38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Abbreviated title	2018
Country/Territory	Spain
City	Valencia
Period	22/07/18 → 27/07/18
Internet address	https://www.igarss2018.org/

Keywords

Spatial resolution
Data models
Agriculture
Biological system modeling
Nitrogen
Remote sensing
Reflectivity
ITC-CV

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10.1109/IGARSS.2018.8518848

Cite this

@inproceedings{ca3fe8747997401ebd207c3041955d5e,

title = "Modelling Leaf Chlorophyll Content in Coffee (Coffea Arabica) Plantations Using Sentinel 2 Msi Data",

abstract = "Coffee leaf chlorophyll (ChI) is an important proxy for coffee plant photosynthetic rates, nitrogen content, leaf health and yield potential. Whereas the recently launched Sentinel 2 multi -spectral instrument (MSI) data has great potential for plant condition assessment, the value of its spectral settings at variable spatial resolutions in relation to crop canopy cover on ChI content prediction remains largely unexplored. In this study, we apply an empirical model to estimate coffee leaf ChI with Sentinel 2 MSI data. Results showed that coffee biophysical parameters (height and canopy cover) are significantly influenced by stand age while plant water concentration and total ChI are age invariant. Results further showed that the best modelling results (R2=0.69, RMSE=64.4) were achieved when all the bands at 10m spatial resolution with all data were used. We concluded that Sentinel 2 MSI is a valuable dataset for predicting coffee leaf ChI, however, based on our findings, we suggest that finer spatial resolutions of 10m on mature coffee stands should be adopted for better prediction results.",

keywords = "Spatial resolution, Data models, Agriculture, Biological system modeling, Nitrogen, Remote sensing, Reflectivity, ITC-CV",

author = "Abel Chemura and Onisimo Mutanga and John Odindi",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE; 38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 : Observing, Understanding and Forcasting the Dynamics of Our Planet, 2018 ; Conference date: 22-07-2018 Through 27-07-2018",

year = "2018",

month = oct,

day = "31",

doi = "10.1109/IGARSS.2018.8518848",

language = "English",

isbn = "978-1-5386-7151-1",

pages = "8228--8231",

booktitle = "IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium",

publisher = "IEEE",

address = "United States",

url = "https://www.igarss2018.org/",

}

Chemura, A, Mutanga, O & Odindi, J 2018, Modelling Leaf Chlorophyll Content in Coffee (Coffea Arabica) Plantations Using Sentinel 2 Msi Data. in IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium., 8518848, IEEE, pp. 8228-8231, 38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain, 22/07/18. https://doi.org/10.1109/IGARSS.2018.8518848

Modelling Leaf Chlorophyll Content in Coffee (Coffea Arabica) Plantations Using Sentinel 2 Msi Data. / Chemura, Abel; Mutanga, Onisimo; Odindi, John.
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. p. 8228-8231 8518848.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Modelling Leaf Chlorophyll Content in Coffee (Coffea Arabica) Plantations Using Sentinel 2 Msi Data

AU - Chemura, Abel

AU - Mutanga, Onisimo

AU - Odindi, John

N1 - Conference code: 38

PY - 2018/10/31

Y1 - 2018/10/31

N2 - Coffee leaf chlorophyll (ChI) is an important proxy for coffee plant photosynthetic rates, nitrogen content, leaf health and yield potential. Whereas the recently launched Sentinel 2 multi -spectral instrument (MSI) data has great potential for plant condition assessment, the value of its spectral settings at variable spatial resolutions in relation to crop canopy cover on ChI content prediction remains largely unexplored. In this study, we apply an empirical model to estimate coffee leaf ChI with Sentinel 2 MSI data. Results showed that coffee biophysical parameters (height and canopy cover) are significantly influenced by stand age while plant water concentration and total ChI are age invariant. Results further showed that the best modelling results (R2=0.69, RMSE=64.4) were achieved when all the bands at 10m spatial resolution with all data were used. We concluded that Sentinel 2 MSI is a valuable dataset for predicting coffee leaf ChI, however, based on our findings, we suggest that finer spatial resolutions of 10m on mature coffee stands should be adopted for better prediction results.

AB - Coffee leaf chlorophyll (ChI) is an important proxy for coffee plant photosynthetic rates, nitrogen content, leaf health and yield potential. Whereas the recently launched Sentinel 2 multi -spectral instrument (MSI) data has great potential for plant condition assessment, the value of its spectral settings at variable spatial resolutions in relation to crop canopy cover on ChI content prediction remains largely unexplored. In this study, we apply an empirical model to estimate coffee leaf ChI with Sentinel 2 MSI data. Results showed that coffee biophysical parameters (height and canopy cover) are significantly influenced by stand age while plant water concentration and total ChI are age invariant. Results further showed that the best modelling results (R2=0.69, RMSE=64.4) were achieved when all the bands at 10m spatial resolution with all data were used. We concluded that Sentinel 2 MSI is a valuable dataset for predicting coffee leaf ChI, however, based on our findings, we suggest that finer spatial resolutions of 10m on mature coffee stands should be adopted for better prediction results.

KW - Spatial resolution

KW - Data models

KW - Agriculture

KW - Biological system modeling

KW - Nitrogen

KW - Remote sensing

KW - Reflectivity

KW - ITC-CV

UR - https://www.scopus.com/pages/publications/85064165214

U2 - 10.1109/IGARSS.2018.8518848

DO - 10.1109/IGARSS.2018.8518848

M3 - Conference contribution

SN - 978-1-5386-7151-1

SP - 8228

EP - 8231

BT - IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium

PB - IEEE

T2 - 38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018

Y2 - 22 July 2018 through 27 July 2018

ER -

Modelling Leaf Chlorophyll Content in Coffee (Coffea Arabica) Plantations Using Sentinel 2 Msi Data

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