Rice Crop Counting Using Aerial Imagery and GIS for the Assessment of Soil Health to Increase Crop Yield.
- Publisher:
- MDPI
- Publication Type:
- Journal Article
- Citation:
- Sensors, 2022, 22, (21), pp. 1-19
- Issue Date:
- 2022-11-07
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Full metadata record
Field | Value | Language |
---|---|---|
dc.contributor.author | Hassan, SI | |
dc.contributor.author | Alam, MM | |
dc.contributor.author | Zia, MYI | |
dc.contributor.author | Rashid, M | |
dc.contributor.author | Illahi, U | |
dc.contributor.author | Su'ud, MM | |
dc.date.accessioned | 2023-07-08T20:53:05Z | |
dc.date.available | 2022-11-01 | |
dc.date.available | 2023-07-08T20:53:05Z | |
dc.date.issued | 2022-11-07 | |
dc.identifier.citation | Sensors, 2022, 22, (21), pp. 1-19 | |
dc.identifier.issn | 1424-8220 | |
dc.identifier.issn | 1424-8220 | |
dc.identifier.uri | http://hdl.handle.net/10453/171349 | |
dc.description.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. | |
dc.format | Electronic | |
dc.language | eng | |
dc.publisher | MDPI | |
dc.relation.ispartof | Sensors | |
dc.relation.isbasedon | 10.3390/s22218567 | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.subject | 0301 Analytical Chemistry, 0502 Environmental Science and Management, 0602 Ecology, 0805 Distributed Computing, 0906 Electrical and Electronic Engineering | |
dc.subject.classification | Analytical Chemistry | |
dc.subject.classification | 3103 Ecology | |
dc.subject.classification | 4008 Electrical engineering | |
dc.subject.classification | 4009 Electronics, sensors and digital hardware | |
dc.subject.classification | 4104 Environmental management | |
dc.subject.classification | 4606 Distributed computing and systems software | |
dc.subject.mesh | Crops, Agricultural | |
dc.subject.mesh | Geographic Information Systems | |
dc.subject.mesh | Oryza | |
dc.subject.mesh | Plant Weeds | |
dc.subject.mesh | Soil | |
dc.subject.mesh | Soil | |
dc.subject.mesh | Geographic Information Systems | |
dc.subject.mesh | Oryza | |
dc.subject.mesh | Crops, Agricultural | |
dc.subject.mesh | Plant Weeds | |
dc.subject.mesh | Crops, Agricultural | |
dc.subject.mesh | Soil | |
dc.subject.mesh | Geographic Information Systems | |
dc.subject.mesh | Plant Weeds | |
dc.subject.mesh | Oryza | |
dc.subject.mesh | Soil | |
dc.subject.mesh | Geographic Information Systems | |
dc.subject.mesh | Oryza | |
dc.subject.mesh | Crops, Agricultural | |
dc.subject.mesh | Plant Weeds | |
dc.title | Rice Crop Counting Using Aerial Imagery and GIS for the Assessment of Soil Health to Increase Crop Yield. | |
dc.type | Journal Article | |
utslib.citation.volume | 22 | |
utslib.location.activity | Switzerland | |
utslib.for | 0301 Analytical Chemistry | |
utslib.for | 0502 Environmental Science and Management | |
utslib.for | 0602 Ecology | |
utslib.for | 0805 Distributed Computing | |
utslib.for | 0906 Electrical and Electronic Engineering | |
pubs.organisational-group | /University of Technology Sydney | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Engineering and Information Technology | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science | |
utslib.copyright.status | open_access | * |
pubs.consider-herdc | false | |
dc.date.updated | 2023-07-08T20:52:59Z | |
pubs.issue | 21 | |
pubs.publication-status | Published online | |
pubs.volume | 22 | |
utslib.citation.issue | 21 |
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.
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