Integration Between Satellite Images and Spectral Analysis Using The ASD Device to Distinguish Wheat and Barley Plants

Authors

  • Basman Younis Hamid Mosul University , Remote Sensing Center, Mosul, Iraq.
  • Sabah Hussein Ali Mosul University , Remote Sensing Center, Mosul, Iraq.

The cultivation of wheat and barley crops is one of the most important crops cultivated in Iraq,  which contributes to the economic and social development in the country. Iraq seeks to adopt economic policies aimed at cultivating the two crops and undermining their import with the aim of self-sufficiency in them. The current study relied on studying the spatial distribution of the two crops in Nimrud sub-district and the possibility of distinguishing between them by  remote sensing data, where a landsat 8 images acquired on March 5, 2020 were used, then a digital processing was performed on them. The spectral signature of the two crops was measured, the NDVI was calculated, then the supervised classification was performed by (ILWIS) program. The results showed the appropriateness of choosing the satellite image in March, which is the season for planting these two crops, as they constitute the two main crops in this period before planting other summer agricultural crops, which helped in identifying and distinguishing the two crops. The results also showed that the wheat crop is predominantly cultivated in the region, with an area of (271,797) km2, while the area of land cultivated with barley was small, with an area of (7,303) km2.

Keywords:

Wheat and barley, ILWIS, Supervised classification, NDVI, Spectral signature

[1] Directorate of Agricultural Statistics, (2020) . Production of wheat and barley for the year 2020. Central Statistical Organization, Ministry of Planning, Republic of Iraq (in Arabic).

[2] Al-Khaled, Iyad Ahmed, Hassoun, Omar, Akkad, Basil, Ghazala, Jalal, Ismail, Ali and Humaidan, Ghadir. (2018). Estimating the area of wheat, barley and chickpea crops in As-Suwayda governorate using remote sensing technology. Syrian Journal of Agricultural Research 5(3), 98-211, (in Arabic).

[3] Janssen, L.; Gerrit, H. ( 2001), Principles of Remote Sensing, ITC Educational Textbook 2, 2nd ed., Paul Klee, Amstelveen, p 410

[4] Rao, P. P. N. and Mohankumar, A. (1994). Cropland inventory in the command area of Krishnarajasagar Project Using Satellite Data, International Journal of Remote Sensing , .15 (6), 1295-1305, https://doi.org/10.1080/01431169408954162

[5] Hanna, R. F. B.; Deif, M A.; Allah; El Berry, A. M.;Sharobeem, Y. F. (2004). Crop Estimation Using Satellite – Based and Ground – (Based Surveys Comparative Study) Paper number 041121, ASAE Annual Meeting.

[6] Goswami, S.B.; A. Saxena; and G.D. Bairagi (2012). Remote sensing and GIS based wheat crop acreage estimation of Indore district, M.P., International Journal of Emerging Technology and Advanced Engineering. 2(3), 200- 203.

[7] Ibrahim, Nasser Tarraf (2014). Design and modeling of spectral prediction algorithms for wheat production from multi-stage multispectral satellite imagery data. Remote Sensing Journal, Issue 26, General Authority for Remote Sensing, Syrian Arab Republic, (in Arabic).

[8] Ahmed, R.; and H. Sajjad (2015). Crop acreage estimation of Boro Paddy using remote sensing and GIS techniques: A Case from Nagaon district, Assam, India. Advances in Applied Agricultural Science. 3(3), 16-25.

[9] Lillesand, T. M. and Kiefer, R. W. (2004). Remote Sensing and Image Interpretation. 4th Edition, John Wiley and Sons, p. 307.

[10] Cui, Li, (2008). Research on Monitoring the Changes of Desertification Based on Remote Sensing. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. xxxVII. Part B7, Beijing.

[11] Ali, Mohamed Merghani And Bayoumi, Abdel Aziz, (2004). Assessment and Mapping of Desertification in Western Sudan Using Remote sensing Techniques and GIS. International conference on Water Resources and Arid Environment.16p.

[12] [Janssen, L.; Gerrit, H., (2001), Principles of Remote Sensing, ITC Educational Textbook 2, 2nd ed., Paul Klee, Amstelveen, p 410.

[13] [13] Dagestani, Hikmat Sobhi, Ali, Sabah Hussein, (2014), Radiometric Spectrometer Device, Publications of the Remote Sensing Center, University of Mosul, 17 pages, (in Arabic).

[14] [14] Campbell, J.B. and Wynne, R. (2011). Introduction to Remote Sensing. Taylor & Francis, London. D. Lu, Q. Weng, 2007 "A survey of image classification methods and techniques for improving classification performance", International Journal of Remote Sensing, 28 (5), 823-870,. https://doi.org/10.1080/01431160600746456

[15] [15] Liu, JianGuo and Mason, Philippa G. (2009). Essential Image Processing and GIS For Remote Sensing. John Willy & Sons Ltd, UK. https://doi.org/10.1002/9781118687963.ch11

Integration Between Satellite Images and Spectral Analysis Using The ASD Device to Distinguish Wheat and Barley Plants. (2024). Journal Port Science Research, 6(special), 118-126. https://doi.org/10.36371/port.2023.special.15

License

Copyright (c) 2023 Journal Port Science Research

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

How to Cite

Integration Between Satellite Images and Spectral Analysis Using The ASD Device to Distinguish Wheat and Barley Plants. (2024). Journal Port Science Research, 6(special), 118-126. https://doi.org/10.36371/port.2023.special.15