Evaluation of Sentinel-2 imagery for the estimation of Silage maize biomass: A case study of Magsal Animal Husbandry & Agriculture, Qazvin, Iran

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Haddadi Farzaneh; AGHIGHI HOSSEIN; Moradi Ayob

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Iranian Journal of Remote Sensing & GIS Year:2019 | Volume:10 | Issue:4 Page(s): 00-00

Download Full-Text

Persian Verion

View:

390

Download:

Cites:

Information Journal Paper

Title

Evaluation of Sentinel-2 imagery for the estimation of Silage maize biomass: A case study of Magsal Animal Husbandry & Agriculture, Qazvin, Iran

Author(s)

Haddadi Farzaneh | AGHIGHI HOSSEIN | Moradi Ayob | Issue Writer Certificate

Keywords

Remote sensingQ1

Time Series AnalysisQ1

Red edge IndexQ1

Biomass estimationQ1

Silage maizeQ1

Abstract

The accurate estimation of crop biomass using satellite data is one of the important challenges in environmental Remote sensing. Traditionally, spectral vegetation indices (VIs) derived from spectral reflectances in red (R) and near infrared (NIR) bands have been employed to statistically estimate the crop biomass; however, most of these VIs saturate at some level of LAI. Therefore, most of the recent studies have been investigated on using the reflectance spectra in the red-edge region to overcome the saturation limitation. In order to evaluate the performance of different VIs for the estimation of crop biomass, we conducted five sampling campaigns during the growing season of Silage maize in Magsal, Qazvin and we totally collected 182 Silage maize biomass samples. Then, ten spectral indices from the time series of Sentinel-2 images of 2117 which were simultaneous with our campaigns were computed and employed to statistically estimate the Silage maize biomass. The Silage maize biomasses were evaluated with the field measurements. The results showed that 𝐶 𝐼 𝑟 𝑒 𝑑 𝑒 𝑑 𝑔 𝑒 index with 𝑅 2 = 1. 55 and the lowest root mean square error (𝑅 𝑀 𝑆 𝐸 = 2. 874 𝑘 𝑔 𝑚 2 ⁄ ) was the best index to estimate Silage maize biomass. Moreover, this work also showed that Sentinel-2 satellite which delivers high spatial resolution images of the red-edge band can be employed to accurately estimate the Silage maize biomasses.

Cites

No record.

References

No record.

Cite

APA: Copy

Haddadi, Farzaneh, AGHIGHI, HOSSEIN, & Moradi, Ayob. (2019). Evaluation of Sentinel-2 imagery for the estimation of Silage maize biomass: A case study of Magsal Animal Husbandry & Agriculture, Qazvin, Iran. REMOTE SENSING & GIS, 10(4 ), 00-00. SID. https://sid.ir/paper/362766/en

Vancouver: Copy

Haddadi Farzaneh, AGHIGHI HOSSEIN, Moradi Ayob. Evaluation of Sentinel-2 imagery for the estimation of Silage maize biomass: A case study of Magsal Animal Husbandry & Agriculture, Qazvin, Iran. REMOTE SENSING & GIS[Internet]. 2019;10(4 ):00-00. Available from: https://sid.ir/paper/362766/en

IEEE: Copy

Farzaneh Haddadi, HOSSEIN AGHIGHI, and Ayob Moradi, “Evaluation of Sentinel-2 imagery for the estimation of Silage maize biomass: A case study of Magsal Animal Husbandry & Agriculture, Qazvin, Iran,” REMOTE SENSING & GIS, vol. 10, no. 4 , pp. 00–00, 2019, [Online]. Available: https://sid.ir/paper/362766/en

Related Journal Papers