Treffer: Crown counting and mapping of missing oil palm tree using airborne imaging system

Title:
Crown counting and mapping of missing oil palm tree using airborne imaging system
Authors:
Publication Year:
2019
Collection:
Universiti Putra Malaysia: PSAS (Perpuskataan Sultan Abuld Samad) Institutional Repository
Document Type:
Dissertation thesis
File Description:
text
Language:
English
Relation:
http://psasir.upm.edu.my/id/eprint/84266/1/FK%202019%20106%20-%20ir.pdf; Kee, Ya Wern (2019) Crown counting and mapping of missing oil palm tree using airborne imaging system. Masters thesis, Universiti Putra Malaysia.
Accession Number:
edsbas.7F33A24B
Database:
BASE

Weitere Informationen

Unmanned aerial vehicles (UAV) have been recently deployed in the agriculture sector for various applications such as crop monitoring and yield prediction in order to achieve the precise agriculture objectives. In Malaysia, there are plenty of large-scale oil palm plantations, but the counting of oil palm trees and missing trees processes are still manually done which is time consuming and costly. The demand of automated missing oil palm tree counting is increasing yet none of relevant research has been published. Therefore, this study implemented different image processing techniques to true color and multispectral UAV imageries for automated existing and missing oil palm tree counting. The study found that multispectral data provides higher accuracy compared to visible bands data and Normalized Difference Vegetation Index (NDVI) index is the best index for oil palm discrimination among all the vegetation indices tested in this research. Hue, Saturation, Value (HSV) color space was found to be effective for distinguishing between the trees and weeds while the index of subtraction red from green (RG) is useful for separation of soil and greenness objects in tree identification. Integration of vegetation indices, color space model conversion and blob analysis was found capable to generate a better oil palm discrimination map. Watershed segmentation function was employed to separate the connected trees and missing trees regions. Different structuring elements of morphological filtering were applied to oil palm trees and missing trees counting for the purpose of noise removal. The undetected group of missing oil palms trees are estimated based on the planting pattern design. Over-counting error can be eliminated by merging the detected trees which depart from each other within a threshold value. For comparison purpose, the other approach of counting trees was carried out; the commercial eCognition software was tested for oil palm counting in template matching approach. The overall accuracy of counting existing oil ...