Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

UAV Based Agricultural Crop Canopy Mapping for Crop Field Monitoring

View through CrossRef
Abstract. Nowadays, mapping of agricultural crop canopy in different growing stages are vital data for crop field monitoring than field-based observations in large scale agricultural crop fields. By mapping agricultural crop canopy, it is very easy to analyse the status of an agricultural crop field by using different vegetation indices. Further, the data can be used to estimate the yield. These information are timely and reliable spatial information to the farmers and decision makers. Mapping of crop canopy in an agricultural crop field in different growing stages are very challenging using satellite imagery mainly due to the difficulty of recording with high cloud coverage. Also, the cost for satellite imagery are higher in proportion to the spatial resolution. It takes some time to order a satellite imagery and sometimes can’t cover some growing stages. This problem can be solved by using low cost RGB based UAV imageries which can be operated at low altitudes (below the clouds) which and when necessary. This study is therefore aimed at mapping of a maize crop canopy using RGB based UAV imageries. UAV flights at different growth stages were carried out with a high resolution RGB camera over a maize field in Ampara District, Sri Lanka. For accurate crop canopy mapping, very high-resolution multi-temporal ortho-mosaicked images were derived from UAV imageries using free and open source image processing platforms with spatial resolution in centimetre level. The resultant multi-temporal ortho-mosaicked images can be used to map and monitor the crop field’s precise and efficient manner. These information are very important for farmers and decision makers to properly manage the crop fields.
Title: UAV Based Agricultural Crop Canopy Mapping for Crop Field Monitoring
Description:
Abstract.
Nowadays, mapping of agricultural crop canopy in different growing stages are vital data for crop field monitoring than field-based observations in large scale agricultural crop fields.
By mapping agricultural crop canopy, it is very easy to analyse the status of an agricultural crop field by using different vegetation indices.
Further, the data can be used to estimate the yield.
These information are timely and reliable spatial information to the farmers and decision makers.
Mapping of crop canopy in an agricultural crop field in different growing stages are very challenging using satellite imagery mainly due to the difficulty of recording with high cloud coverage.
Also, the cost for satellite imagery are higher in proportion to the spatial resolution.
It takes some time to order a satellite imagery and sometimes can’t cover some growing stages.
This problem can be solved by using low cost RGB based UAV imageries which can be operated at low altitudes (below the clouds) which and when necessary.
This study is therefore aimed at mapping of a maize crop canopy using RGB based UAV imageries.
UAV flights at different growth stages were carried out with a high resolution RGB camera over a maize field in Ampara District, Sri Lanka.
For accurate crop canopy mapping, very high-resolution multi-temporal ortho-mosaicked images were derived from UAV imageries using free and open source image processing platforms with spatial resolution in centimetre level.
The resultant multi-temporal ortho-mosaicked images can be used to map and monitor the crop field’s precise and efficient manner.
These information are very important for farmers and decision makers to properly manage the crop fields.

Related Results

Estimation of Rice Canopy Height and Density Research Using LiDAR Data
Estimation of Rice Canopy Height and Density Research Using LiDAR Data
Rice canopy height and density are directly usable crop phenotypic traits for the direct estimation of crop biomass. Therefore, it is crucial to rapidly and accurately estimate ric...
Quantifying corn emergence using UAV imagery and machine learning
Quantifying corn emergence using UAV imagery and machine learning
Corn (Zea mays L.) is one of the important crops in the United States for animal feed, ethanol production, and human consumption. To maximize the final corn yield, one of the criti...
Mixed-reality for unmanned aerial vehicle operations in near earth environments
Mixed-reality for unmanned aerial vehicle operations in near earth environments
Future applications will bring unmanned aerial vehicles (UAVs) to near Earth environments such as urban areas, causing a change in the way UAVs are currently operated. Of concern i...
ASSESSING THE CANOPY INTEGRITY USING CANOPY DIGITAL IMAGES IN SEMIDECIDUOUS FOREST FRAGMENT IN SÃO CARLOS - SP- BRAZIL1
ASSESSING THE CANOPY INTEGRITY USING CANOPY DIGITAL IMAGES IN SEMIDECIDUOUS FOREST FRAGMENT IN SÃO CARLOS - SP- BRAZIL1
ABSTRACT It is well-known that conducting experimental research aiming the characterization of canopy structure of forests can be a difficult and costly task and, generally, requir...
Assessing a VTOL UAV-Based Digital Imaging System for Agricultural Monitoring using Low-Cost Digital Camera
Assessing a VTOL UAV-Based Digital Imaging System for Agricultural Monitoring using Low-Cost Digital Camera
A vertical take-off and landing unmanned aerial vehicle (VTOL-UAV) was used to assess the possibilities of a digital image-based for agricultural surveillance system. The VTOL-UAV ...
Design of LABVIEW-based UAV Online Monitoring and Security Situation Assessment System
Design of LABVIEW-based UAV Online Monitoring and Security Situation Assessment System
Abstract In this paper, we design a LabVIEW-based UAV online monitoring and safety situation assessment system to address the deficiencies in the monitoring of UAV flight s...
ACOUSTIC FIELD CHARACTERISTICS UAV SCREW
ACOUSTIC FIELD CHARACTERISTICS UAV SCREW
Unmanned aerial vehicles (UAVs) began to be actively used in civil and military spheres. During flight, UAV nodes emit noise into the environment, while the main radiation node is ...
Mixed-Reality Geotechnical Cell Mapping for Slope Stability Assessment at Rio Tinto Bingham Canyon Mine
Mixed-Reality Geotechnical Cell Mapping for Slope Stability Assessment at Rio Tinto Bingham Canyon Mine
ABSTRACT: In this paper, the applicability of Mixed Reality (MR) in combination with Uncrewed Aerial Vehicle (UAV) photogrammetry data is investigated to aid the ...

Back to Top