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Title: Unmanned Aerial Vehicle(UAV), for Oil Palm Plantation


1
Unmanned Aerial Vehicle(UAV), for Oil Palm
Plantation
By JWAN M ALDOSKI Geospatial Information
Science Research Center (GISRC), Faculty of
Engineering, Universiti Putra Malaysia, 43400
UPM Serdang, Selangor Darul Ehsan. Malaysia.
2
Outline
  • What is the UAV
  • How UAS Works
  • Purposes for UASTheir benefits
  • Where they are headed
  • Questions

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What is a UAV?
  • It also called Drones, Remotely Piloted Vehicle
    (RPV) by the Federal Aviation Administration
    (FAA) adopted by United States Department of
    Defense (DOD) Civil Aviation Authority(UK).
  • Powered, aerial vehicles
  • No human operator on board
  • Can fly autonomously or be piloted remotely
  • Can be expendable or recoverable
  • Can carry weapons or surveillance equipment)

4
UAV types
  • Fixed wing
  • Rotary Wing

5
UAV components
  1. Vehicle or platform itself

Predator
Nano Hummingbird
Puma AE
Solar Eagle
Honeywell T-Hawk
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Payload
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support equipment
  • like control station, data links, telemetry,
    communications and navigation and related
    equipment necessary to operate the UA.

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How UAS Works
  • Collects Data 
  • Processes it into images
  • Sends images to centers for furfure analysis

9
Purposes for UAS
  • Firefighting 
  • Police Disturbances (crime scenes, etc)
  • natural disasters
  • atmospheric research scientific research,
  • oceanographic research,
  • geophysical research,
  • mineral exploration,
  • imaging spectrometry,
  • traffic
  • agricultural spraying,
  • aerial photography,

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UAV Advantages
  • Safety, No pilot to be shot down, Can fly into
    hurricanes or at low altitudes over the ocean
  • Little damage when they crash due to their light
    weight
  • It can be made and built in a time of 3-4 days.
  • All components are locally available.
  • Flight need not be scheduled. It can be based on
    the weather conditions and preferences of the
    farmer.
  • Availability of data and imagery immediately
    after the flight.
  • Disadvantages
  • Significant experience required to fly the UAV.
  • Easily destructible.

11
UAV for oil palm plantation
  • The oil palm plantation business involves
    extensive area and getting reliable ground
    information is critical. Plantation managements
    rely on ground staffs to report
    on field conditions. Most of the times, you need
    a holistic view to see what's out there.
  • With our experience and technology, we are not
    only just providing you with this holistic view
    via our Sensefly UAVs, we go 2 steps beyond. We
    extract and produce crucial analysis through GIS,
    helping you to make that important business
    decision on remedial actions required to improve
    your estate conditions.

12
Palm stand per hectare / palm census
13
Mapping for Oil Palm Plantations
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Actual planted area by block
  • 2. Palm stand per hectare / palm census 
  • 3. 4. Unplantable area (river riparians, steep
    regions, lake)
  • 5. Road network and their density for each block

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oil palm plant density
Poor plant density
good plant density
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Identify Unplanted area
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Land Feasibility Scouting For Establishment Of
Oil Palm Plantation
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Oil palm growing rate
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Ganoderma detection in oil palm plantation
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Bagworms
  • Standard operating procedures (SOP) guidelines
    for bagworms control

21
  • The census methods is based on the international
    standards of phytosanitary Measures, ISPM. No.
    6- Guidelines for Surveillance (1997), Fronds
    with inclination of 45 O or upper fronds with
    sign of bagworms attack need to be cut down
    (figure). As precisely estimating the percentage
    of oil palm foliar affected by bagworms damage
    was difficult, bagworms damage ratings were
    assigned based estimation of damage severity
    corresponding to the ratings suggested by Pickel
    et al. (2006) however in this study, each foliar
    was given a damage rating ranging from 0 (no
    damage) to 3 (sever damage) the criteria used to
    assign the damage ratings is listed in table. Oil
    palm leaves measurement samples were taken from
    healthy and 4 different levels of infection. The
    samples were classified into five classes of T0,
    T1, T2, T3 and T4. T0 represents healthy oil
    palms, T2 represents the very light symptom, T2
    represents the light symptom, T3 represents the
    medium symptom of bagworms infection and T4
    represents severe bagworms infection

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  • Detection of Attack and buffer zone measure
  • Attack zone
  • is defined as the area in which there are signs
    of bagworms attacks and damage on one or more
    trees regardless of the area of cultivation
    attack zone can be confirmed by visual damage (
    through field viewing and Arial photo view ).
  • Buffer zone
  • It is defined as the adjacent surrounding areas
    to the attack zone which needs to be monitored
    and treated if necessary. The zone covers at
    least 500 metre radius from the border of the
    attack zone.

Figure Attack and buffer zone
23
Bagworm census
  • Standard operating procedures (SOP) guidelines
    for bagworms control

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Bagworms effect
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Questions?
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Detection of Bagworms in Oil Palm Plantation
Using UAV
Dr. JWAN M ALDOSKI Geospatial Information
Science Research Center (GISRC), Faculty of
Engineering, Universiti Putra Malaysia, 43400
UPM Serdang, Selangor Darul Ehsan. Malaysia.
45
Introduction
  • Insect cause serious economic losses in yield and
    quality of cultivated plants around the world
    (MacLeod, et al, 2014.
  • Like any other agricultural crops, oil palm is
    not freed from the problem of insects.

Total Annual Loss in Cultivated Plants ()
46
Oil Palm distribution in Malaysia
Introduction
  • The palm oil industry is one of the key economic
    drivers of the agricultural sector in Malaysia
    and other countries

Global distribution of oil palm
47
Yield Losses in Oil Palm
  • According to the Malaysian Palm Oil Board
    (MPOB), the major threats for the oil palm yield
    losses can be categories into

(Ramlah et al., 2007)
48
Some Common Insect Their Effects in Oil Palm ,
Malaysia
Termite
Thirathaba Bunch Moth
49
Some Common Insect Their Effects in Oil Palm ,
Malaysia
Rhinoceros Beetles
Nettle Caterpillars
50
Problem Statement
Newly, bagworms is considered as one of the
most serious insect in oil palm plantation,
Malaysia , which has a severe impact on both the
yield and quality of oil palm production. Until
now , traditional method is the main way for
detection this insect. Therefore , applying new
detection techniques for detection is
needed. According to Lee (2010), and Seidl
(2011), trees that attack by insects show many
indicators such as decrease in reflectance across
the electromagnetic spectrum owing to an increase
of shadow and background within the field of
view, reduction in leaf area, changes in overall
contents of leaf pigments or leaf water and crown
discoloration. Fortunately, remote sensing
techniques particularly UAV and ground base
remote sensing are enable to measure these
indicators in a wide area at constant time
periods. Thus, UAV and ground base remote sensing
will be valuable for early detecting, mapping and
monitoring bagworm damage in oil plantation .
51
Bagworms -Leaf Insect
Biology
Damages
52
Bagworm Life Cycle
Characteristic Bagworms species Bagworms species Bagworms species
Characteristic Mahasena Corbetti Metisa plana Pteroma Pendula
Development time (day) 124 69-120 80
average egg per female 3,000 100-300 65 220
Family of host plants (number) 25 7 19
53
Bagworms species in Malaysia
Metisa plana
Mahasena Corbetti
Pteroma pendula
54
Distribution of Bagworms Outbreak In Peninsular
Malaysia
2011
2015
55
Bagworms Effect in Oil Palm Yield
Kalidas P (2004)
56
Insect Detection Methods
Base on symptoms
Base on Biophysical and biochemical properties
and reflectance of plants
(Lucas, 1998, p. 54)
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Remote Sensing Technology for Insect Detection
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Remote Sensing Technology for Insect Detection
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Remote Sensing Technology for Insect Detection
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Remote Sensing Technology for Insect Detection
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Remote Sensing Technology for Insect Detection
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Indices/Techniques for Insect Detection Base on
RS
Riedell and Blackmer (1999) , Yang et al. (2005)
, Yang et al. (2009) , Mirik et al. (2006a),
Mirik et al. (2006b), Elliott et al. (2007),
Genc et al. (2008) , Pena and Altman (2009),
Coops et al. (2009)
63
Objectives
  • Develop a bagworm index based on canopy
    hyperspectral reflectance data.
  • Identify the most sensitive VI for assessing
    damage by bagworms in oil palm
  • Estimation LAI and chlorophyll content over a
    variety of bagworms infestation levels in oil
    palm plantation.
  • Distinguish the level of correlation between
    chlorophyll content, LAI and NDVI value of
    bagworms infestation levels.
  • Identifying and mapping oil-palm bagworms
    infestation levels using UAV-CIR and NDVI
    imaging.

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Tree (Canopy ) , Leaf and leaflets choice for
data acquisition
Tree Selection
Leaves Leaflets Selection and Taking
Measurements
Canopy measuring
66
Field Instruments
Leaf Area Index Measurements with the LAI-2200C
UNISPEC hyperspectral spectrometer and Handheld
spectroradiometers with fibre optics
  • GPS

The CCM-200 plus leaf Chlorophyll Content Meter
67
Critical Threshold Levels For Bagworms
      Tree / leaves Damage Rating Class Name Class Name Description
      Tree / leaves 0 Nil /Healthy trees / leaves Nil /Healthy trees / leaves No visible bagworms damage
      Tree / leaves 1 Light / Slight effected Light / Slight effected Very few bagworms larvae and pups on leaflet
      Tree / leaves 2 Medium /Medium effect Medium /Medium effect Most of leaflet with bagworms larvae and pups many holes on leaflet with slight necrosis
      Tree / leaves 3 Serious /Sever effect Serious /Sever effect Lots of bagworms larvae and pups on almost all leaflets. Lots of holes and necrosis. Leaflets turning brown and dessicated .

Group Species Species No. of Live Larvae/Frond No. of Live Larvae/Frond
Bagworms Metisa plana Metisa plana 10 10
Bagworms Mahasena corbetti Mahasena corbetti 5 5
Bagworms Pteroma pendula Pteroma pendula 5     5    
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UAV Data
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Pre- Processing Data
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Arial photograph
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  • Thank You
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