The Role of Unmanned Aerial Vehicle for Biosecurity Risk Management

Technological advancements in data acquisition using Unmanned Aerial Vehicles (UAVs) are increasingly applied in biosecurity, particularly for monitoring forest plantations like Eucalyptus pellita . This research has two objectives, i.e. to compare the challenges in obtaining accurate information on Industrial Forest Plantation plants and to provide an overview of the efforts made in solving this problem and the optimal results of the information obtained.The method used in the research is to conduct a Strength, Weakness, Opportunity, and Threat (SWOT) assessment on the utilization of UAVs in biosecurity development and focus on (1) Leaf Disease Severity Detection, (2) Crown Density Modelling, (3) CHM for Individual Tree Detection (4) DBH Estimation Modelling (5) Large Scale Acquisition Procedures. Strengths of UAVs include their ability to provide fast, efficient, and highly accurate data for early detection of plant diseases and pests. Weaknesses from UAVs’ reliance on favorable weather conditions. Opportunities exist in integrating UAV data with advanced analytical methods to improve biosecurity. Rapid technological advancements can become a threat as they compel organizations to continuously upgrade equipment, while widespread UAV use may raise legal and ethical concerns, including privacy and regulatory challenges. However, UAV can be a technological instrument for implementing biosecurity risk management.

Authors

Institutions

Publication Details

Journal
Engineering headway
Published
2025-10-13
DOI
https://doi.org/10.4028/p-0i52dp
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Role of Unmanned Aerial Vehicle for Biosecurity Risk Management

Abeer Firdaus Adiva Hadi, Barandi Sapta Widartono, Francisca Nova Puspatiyaningrum
Engineering headway
Smart Agriculture and AI
article

The Role of Unmanned Aerial Vehicle for Biosecurity Risk Management

Abeer Firdaus Adiva Hadi, Barandi Sapta Widartono, Francisca Nova Puspatiyaningrum
article en

Abstract

Technological advancements in data acquisition using Unmanned Aerial Vehicles (UAVs) are increasingly applied in biosecurity, particularly for monitoring forest plantations like Eucalyptus pellita . This research has two objectives, i.e. to compare the challenges in obtaining accurate information on Industrial Forest Plantation plants and to provide an overview of the efforts made in solving this problem and the optimal results of the information obtained.The method used in the research is to conduct a Strength, Weakness, Opportunity, and Threat (SWOT) assessment on the utilization of UAVs in biosecurity development and focus on (1) Leaf Disease Severity Detection, (2) Crown Density Modelling, (3) CHM for Individual Tree Detection (4) DBH Estimation Modelling (5) Large Scale Acquisition Procedures. Strengths of UAVs include their ability to provide fast, efficient, and highly accurate data for early detection of plant diseases and pests. Weaknesses from UAVs’ reliance on favorable weather conditions. Opportunities exist in integrating UAV data with advanced analytical methods to improve biosecurity. Rapid technological advancements can become a threat as they compel organizations to continuously upgrade equipment, while widespread UAV use may raise legal and ethical concerns, including privacy and regulatory challenges. However, UAV can be a technological instrument for implementing biosecurity risk management.

Engineering headwayVol. 27
Universitas Gadjah Mada (ID)
Openalex Percentile: Top 79%
Smart Agriculture and AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.