Open AccessPemantauan Tanaman Padi Menggunakan Sistem Maklumat Geografi dan Imej Multispektral
Author(s) -
Rowena Mat Halip,
Nik Norasma,
Wan Fazilah Ilahi Fadzli,
Rhushalshafira Rosle,
Nor Athirah Roslin,
Mohd Razi Ismail,
Zulkarami Berahim,
Mohamed Ariff Omar
Publication year - 2020
Publication title -
advances in agricultural and food research journal
Language(s) - English
Resource type - Journals
ISSN - 2735-1084
DOI - 10.36877/aafrj.a0000118
Subject(s) - orthophoto , irrigation , normalized difference vegetation index , leaf area index , agricultural engineering , agriculture , compost , environmental science , precision agriculture , remote sensing , mathematics , agronomy , geography , engineering , biology , archaeology
This study is focused on paddy growth monitoring using Geographic Information System (GIS) and multispectral imagery via unmanned aerial vehicle (UAV). The objective of the study is to identify the best treatment that produces the highest yield. This combined technology is an effective farming management known as precision farming. UAV was used as a tool for field data capturing to produce orthophoto which will be a source for vegetative index and also for vector data digitizing purposes using ArcGIS 10.2. Data will be used as a source to analyze and monitor paddy growth. Geographical features that are digitized will able to provide farmer a full visual of their crop area such as crop layout, treatment type and also vegetative index. As a result, plot with treatment type Compost with Inoculum is able to produce the highest yield with 2494.7287 t/ha yield comparing to other treatment plots. However, treatment type U Grow producing the highest NDVI reading which is 0.4327 with yield producing only 2411.3080 t/ha lower than the plot with treatment type Compost with Inoculum. Maximum value of NDVI is not a guarantee of highest yield production. However, this research has shown that vegetative index value is able to become a benchmark for paddy growth monitoring while spatial analysis is able to make farming management more efficient. Other factors such as terrain model and effectiveness of current irrigation system can be a next sub topic for the research.