Citation

Hassan, Syeda Iqra and Alam, Muhammad Mansoor and Zia, Muhammad Yousuf Irfan and Rashid, Muhammad and Illahi, Usman and Mohd Su'ud, Mazliham (2022) Rice Crop Counting Using Aerial Imagery and GIS for the Assessment of Soil Health to Increase Crop Yield. Sensors, 22 (21). p. 8567. ISSN 1424-8220

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Abstract

first_pagesettingsOrder Article Reprints Open AccessArticle Rice Crop Counting Using Aerial Imagery and GIS for the Assessment of Soil Health to Increase Crop Yield by Syeda Iqra Hassan 1,2,3ORCID,Muhammad Mansoor Alam 4,5,6,7ORCID,Muhammad Yousuf Irfan Zia 3ORCID,Muhammad Rashid 8ORCID,Usman Illahi 9ORCID andMazliham Mohd Su’ud 5,10,* 1 Department of Electronics and Electrical Engineering, Universiti Kuala Lumpur British Malaysian Institute (UniKL BMI), Batu 8, Jalan Sungai Pusu, Gombak 53100, Malaysia 2 National Centre for Big Data and Cloud Computing, Ziauddin University, Karachi 74600, Pakistan 3 Department of Electrical Engineering, Ziauddin University, Karachi 74600, Pakistan 4 Faculty of Computing, Riphah International University, Islamabad 46000, Pakistan 5 Faculty of Computing and Informatics, Multimedia University, Cyberjaya 63100, Malaysia 6 Malaysian Institute of Information Technology, University of Kuala Lumpur, Kuala Lumpur 50250, Malaysia 7 Faculty of Engineering and Information Technology, School of Computer Science, University of Technology, Sydney 2006, Australia 8 Department of Computer Engineering, Umm Al Qura University, Makkah 21955, Saudi Arabia 9 Department of Electrical Engineering, FET, Gomal University, Dera Ismail Khan 29050, Pakistan 10 Water and Engineering Section, MFI, Universiti Kuala Lumpur Malaysian France Institute (UniKL MFI), Section 14, Jalan Damai, Seksyen 14, Bandar Baru Bangi 43650, Malaysia * Author to whom correspondence should be addressed. Sensors 2022, 22(21), 8567; https://doi.org/10.3390/s22218567 Received: 16 September 2022 / Revised: 23 October 2022 / Accepted: 1 November 2022 / Published: 7 November 2022 (This article belongs to the Section Smart Agriculture) Download Browse Figures Versions Notes Abstract Rice is one of the vital foods consumed in most countries throughout the world. To estimate the yield, crop counting is used to indicate improper growth, identification of loam land, and control of weeds. It is becoming necessary to grow crops healthy, precisely, and proficiently as the demand increases for food supplies. Traditional counting methods have numerous disadvantages, such as long delay times and high sensitivity, and they are easily disturbed by noise. In this research, the detection and counting of rice plants using an unmanned aerial vehicle (UAV) and aerial images with a geographic information system (GIS) are used. The technique is implemented in the area of forty acres of rice crop in Tando Adam, Sindh, Pakistan. To validate the performance of the proposed system, the obtained results are compared with the standard plant count techniques as well as approved by the agronomist after testing soil and monitoring the rice crop count in each acre of land of rice crops. From the results, it is found that the proposed system is precise and detects rice crops accurately, differentiates from other objects, and estimates the soil health based on plant counting data; however, in the case of clusters, the counting is performed in semi-automated mode.

Item Type:	Article
Uncontrolled Keywords:	Aerial imaginary, GIS, rice crop, soil testing, UAV, yield estimation
Subjects:	Q Science > QH Natural history S Agriculture > S Agriculture (General)
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	04 Jan 2023 03:10
Last Modified:	04 Jan 2023 03:10
URII:	http://shdl.mmu.edu.my/id/eprint/10742

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