Rowena Mat Halip*, Nik Norasma Che’ Ya, Wan Fazilah Ilahi Fadzli, Rhushalshafira Roslee and Nor Athirah Roslin
Department of Agriculture Technology, Faculty of Agriculture, Universiti Putra Malaysia, UPM Serdang, Selangor, Malaysia
*Corresponding Author: Rowena Mat Halip, Department of Agriculture Technology, Faculty of Agriculture, Universiti Putra Malaysia, UPM Serdang, Selangor, Malaysia.
Received: January 29, 2020; Published: March 10, 2020
The objective of this study is to monitor the crop growth based on the different treatment using vegetative indices on paddy field (PadiU Putra’s seed) that provided by multispectral imagery from unmanned aerial vehicle (UAV) and geographic information system (GIS) analysis. UAV imagery were processed as raster images and translated into vector format in ArcGIS software. The details of the treatment and crop information were stored as attribute data. Multispectral imagery were generated normalized different vegetative indices (NDVI) map using the ArcGIS software to monitor the crop growth based on the different treatment. Result shows that NDVI map responds with different value based on the treatment. It shows that treatment type commercial compost gives highest crop growth at 18% more. The aerial imagery allowed user to have overall view on crop monitoring without physically access to the wide crop field. The aerial imagery can help farmers to identify some problem areas and it can help farmers to plan and manage their field in cost effective, time efficient and minimize labour. It can help farmers in terms of better decision making. This study conclude that crop area with treatment u grow producing highest yield compare to commercial compost and control. RGB images captured providing farmer actual view of crop area on screen without physically accessing the area. NDVI map generated from multispectral images providing a reference of crop status. Vector data digitized were used to stored crop information such as crop ID and crop treatment type. This will help farmer to improve their crop management more efficiently.
Keywords: Crop Growth Monitoring; Precision Agriculture; GIS; UAV; NDVI
Citation: Rowena Mat Halip. “Improving Rice Production Through the Crop Growth Monitoring for Different Treatment using Multispectral Images and Geographic Information System" Acta Scientific Agriculture 4.4 (2020): 25-32.
Copyright: © 2020 Rowena Mat Halip. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.