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Utilizing Hyperspectral Imaging System in unmanned
aerial vehicle (UAV) for Agricultural/Palm Oil Analysis




                                       Geo	
  Sense	
  Sdn.	
  Bhd.	
  
              79A,	
  Jalan	
  Seri	
  Impian	
  1	
      T06-­‐03,	
  Jln	
  Centry	
  Square	
  
                Taman	
  Impian	
  Emas	
                          Block	
  2320	
  	
  
                 81300	
  Johor	
  Bahru	
                      63000	
  Cyberjaya	
  	
  

                                  ismaili@geosense.com.my	
  
                                       www.geosense.com.my	
  
Geo	
  Sense	
  Sdn.	
  Bhd.	
  
Brief	
  Background	
  
•  Establish	
  May	
  2006	
  
•  MSC	
  Status	
  –	
  in	
  web	
  GIS	
  and	
  aerial	
  mapping	
  
•  Pioneering	
  Civilian	
  UAV	
  applicaTons	
  /	
  
   Services	
  
•  Skudai,	
  Johor	
  Bahru	
  Base	
  Company	
  &	
  
   Cyberjaya	
  
•  CollaboraTon	
  with	
  UTM,	
  IMREC	
  and	
  Inst.	
  
   Sustainable	
  Agri	
  of	
  Cardoba	
  Spain	
  
•  Since	
  2007	
  -­‐	
  R&D	
  in	
  unmanned	
  aerial	
  
   mapping	
  and	
  remote	
  sensing	
  
•  Recepient	
  Anugerah	
  Perdana	
  Menteri	
  APICTA	
  
   ICT	
  eGov.	
  Catergory	
  in	
  2007	
  
•  Vision,	
  to	
  become	
  leading	
  tech	
  company	
  in	
  
   civilian	
  UAV	
  applicaTon	
  
Sources of Aerial Imagery

                                   Light Aircraft
        Imaging                    Altitude10k – 30k feet
        Satellite

        500-800 km          Cost
                                                                                      RC AIrcarft / UAV
                                                                                      Altitude 500 – 2000 ft

                                            •  erial Camera System
                                             A
                                            •  adiometric resolution
                                             R
                                            •  0 cm – 60 cm resolution
                                             2
                                            (avg 30 in resolution)
   Cloud Issues                             •  erial mapping survey
                                             A
                                            • PSAR (SAR) / LIDAR
                                             I                                       •  atural color (RGB)
                                                                                      N
                                                                                     •  - 15 cm resolution
                                                                                      7
                                                                                     •  urveillance / Monitoring
                                                                                      S




                                                                         200 meter
90 km                              3 km




                                                                                             300 meter
                    30 km                          3 km
Technology	
  CollaboraTon	
  	
  
Products	
  &	
  Services	
  




	
  Unmanned	
  Aerial	
       	
  GIS	
  /	
  	
     	
  GPS	
  –	
  Geo	
  Tagging	
  
       Mapping	
                Web	
  GIS	
             Mobile	
  applicaTon	
  
Experiences	
  &	
  Clients	
  
Technology	
  Brief	
  

UAV	
  FOR	
  AERIAL	
  MAPPING	
  &	
  
SURVEILLANCE	
  SERVICES	
  
UAV	
  Aerial	
  Mapping	
  –	
  Process	
  Flow	
  
UAV	
  Image	
  AcquisiTon	
  
        Flight	
                UAV	
                    Transferring	
  
                                                                            Launching	
          Monitoring	
            Recovering	
  
      Planning	
            InstallaTon	
                      Plan	
  




Image	
  Processing	
  

                Raw	
                                                                                             Overlaying	
  
                                              Mosaic	
  /	
  STtching	
             Tiling	
  
               Images	
                                                                                           RegistraTon	
  
27	
  March	
  2010	
  




  22	
  July	
  2010	
  
INTEGRATION	
  WITH	
  GIS	
  PLATFORM	
  
Batu	
  Caves,	
  Selayang	
  
Forest	
  Clearing	
  &	
  	
  
PlantaTon	
  Planning	
  
Highway	
  Monitoring	
  (JKR)	
  
Progress Monitoring
	
  Rumah Rakyat IRDA
    June	
  2010	
      Oct	
  2010	
     Feb	
  2011	
  
Potential Applications
Work Auditing /
Verification




                          Feb	
  2010	
  




                         June	
  2010	
  
Case	
  Study	
  1	
  -­‐	
  UAV	
  Mapping	
  by	
  Geo	
  Sense	
  	
  –	
  Semporna,	
  Sabah	
  (5	
  sq	
  km)	
  




     Visual	
  Using	
  UAV	
  




                                                                                     PopulaTon:	
  ~	
  130K	
  
                                                                                     Mail	
  Volume:	
  ~	
  200	
  per	
  day	
  
                                                                                     PO:	
  Semporna	
  Post	
  Office	
  
                                                                                     Mail	
  delivery:	
  limited	
  	
  
                                                                                     Address:	
  Using	
  kampung,	
  schools	
  &	
  
                                                                                     PO	
  Box	
  (710	
  units)	
  
                                                                                     Bank:	
  Maybank	
  &	
  BSN	
  
House	
  Numbering	
  and	
  Address	
  Assignment	
  by	
  Pos	
  Malaysia	
  




   DigiTzing	
  using	
  GIS	
  




                                                                            KAMPUNG	
  BANGAU-­‐BANGAU	
  
                                                                            2,436	
  houses	
  
                                                                                  ADDRESS	
  SAMPLE	
  
                                                                                  Cikgu	
  Ahmad	
  	
  
                                                                                  No2,	
  KampungBangauBangau	
  
                                             PERKAMPUNGAN	
  AIR	
  1	
           91300	
  Semporna,	
  Sabah	
  
                                             659	
  houses	
  
        PERKAMPUNGAN	
  AIR	
  2	
                                                Lat	
  4.4883	
  N	
  
                                                                                  Long	
  118.6050	
  E	
  
        3,313	
  houses	
  
                            Approximately	
  6,000	
  new	
  
                            delivery	
  points	
  idenTfied	
  	
  
Base Map Preparation – Using High Res Aerial Image from UAV




      High	
  resoluTon	
  UAV	
  Images	
                Image	
  digitalizing	
  




        Asset	
  Data	
  in	
  Base	
  Map	
     Base	
  Map	
  from	
  high	
  res	
  images	
  
3D	
  /	
  DTM	
  –	
  OrthoracTficaTon	
  Process	
  
Sojware	
  upgrade	
  
Potential Application
River Monitoring / Flood Management
Project	
  Monitoring	
  and	
  CommunicaTon	
  (PMCS)	
  
Scope	
  of	
  Work	
  &	
  Delivery	
  
                                                                        UAV	
  capturing	
  images	
  




                                                                    Image	
  process	
  &	
  digitalizing	
  



                                                                    The	
  big	
  mosaic	
  (sTtched)	
  image	
  




                                                             Image	
  presentaTon	
  &	
  potenTal	
  uTlizaTon	
  




             Big	
  Poster	
                     Tiles	
  for	
  quick	
  viewing	
        Online	
  Tles	
  visualizaTon	
     Image	
  registraTon	
  (GIS)	
  




                                                                                                                                                                               IntegraTon	
  with	
  	
  
                                                                                                                                     -­‐	
  Project	
  GIS	
  	
               Project	
  Management	
  
                                                                                                                                     -­‐	
  Project	
  monitoring	
  and	
     System	
  
                                                                                        Online	
  visualizaTon	
  
                          Quick	
  distribuTon	
  –	
  images	
                                                                      reporTng	
  system	
                      -­‐	
  Structure	
  modeling	
  
                                                                                        Online	
  archiving	
  system	
  
                          store	
  in	
  DVD	
                                                                                       -­‐	
  Decision	
  support	
              with	
  WBS	
  
                                                                                                                                     system	
  
SOLUTION	
  OVERVIEW	
  

TINJAUKOPTER	
  
 Quanta	
  Lab	
        	
  Geo	
  Sense	
  

Geo	
  Sense,	
  is	
  Malaysian	
  MSC	
  Status	
  company,	
  that	
  is	
  using	
  
unmanned	
  aerial	
  vehicle	
  (UAV)	
  for	
  aerial	
  mapping	
  and	
  remote	
  
sensing.	
  Geo	
  Sense	
  is	
  collaboraTng	
  with	
  Dr.	
  Pablo	
  J.	
  Zarco	
  Tejada	
  
the	
  Director	
  of	
  Laboratory	
  for	
  Research	
  in	
  QuanTtaTve	
  Remote	
  
Sensing,	
  under	
  the	
  InsTtute	
  of	
  Sustainable	
  Agricultural	
  in	
  Cardoba,	
  
Spain	
  in	
  uTlizing	
  UAV	
  for	
  advance	
  remote	
  sensing	
  for	
  agricultural	
  	
  
purposes.	
  	
  



                                                                                                       	
  Geo	
  Sense	
  
CollaboraTon	
  of	
  experts	
  between	
  Quantalab	
  and	
  Geo	
  Sense	
  Sdn.	
  Bhd.	
  




                     	
  Profile	
                                                   	
  Pablo	
  J.	
  Zarco	
  has	
  been	
  Course	
  Director	
  and	
  
                     Dr	
  Pablo	
  J.	
  Zarco	
  Tejada	
                         Teaching	
  Assistant	
  within	
  the	
  Departments	
  of	
  
                                                                                    Environmental	
  Science,	
  and	
  Earth	
  and	
  Space	
  
                     Ph.D.	
  in	
  Earth	
  and	
  Space	
  Science,	
  York	
     Science	
  (	
  York	
  University	
  ,	
  Canada	
  ),	
  and	
  Land,	
  Air,	
  
                     University	
  (Canada),	
  2000	
  	
                          and	
  Water	
  Resources	
  (LAWR),	
  University	
  of	
  
                     M.Sc.	
  in	
  Remote	
  Sensing,	
  Image	
                   California	
  Davis	
  ,	
  in	
  courses	
  related	
  to	
  
                     Processing	
  and	
  ApplicaTons.	
  Dept.	
  of	
             Environmental	
  Science	
  and	
  Remote	
  Sensing.	
  He	
  
                     Applied	
  Physics,	
  Electronic	
  and	
                     has	
  also	
  collaborated	
  in	
  other	
  courses	
  at	
  University	
  
                     Mechanical	
  Engineering	
  (APEME),	
                        of	
  California	
  ,	
  Davis	
  in	
  Precision	
  Agriculture	
  and	
  
                     University	
  of	
  Dundee	
  (Scotland	
  ,	
  UK),	
         Environmental	
  Remote	
  Sensing:	
  	
  
                     1997	
  	
                                                     Since	
  2008,	
  Dr	
  Pablo	
  has	
  been	
  uTlizing	
  UAV	
  for	
  
                     B.S.	
  Agricultural	
  Engineering	
  (Cordoba	
  ,	
         agri.	
  remote	
  sensing.	
  
                     Spain)	
  	
  
                                                                                                                                                     	
  Geo	
  Sense	
  
The	
  collaboraTon	
  will	
  offer	
  Malaysia	
  users	
  to	
  access	
  to	
  the	
  latest	
  technology	
  in	
  
agricultural	
  monitoring	
  and	
  analysis	
  using	
  UAV	
  for	
  quicker	
  respond	
  at	
  lower	
  cost	
  
compare	
  with	
  convenTonal	
  methods.	
  




The	
  UAV	
  with	
  mulT	
  spectral	
  camera	
  enable	
  to	
  meet	
  any	
  on	
  demand	
  request	
  for	
  
urgent	
  requirement	
  in	
  any	
  agricultural	
  respond	
  and	
  analysis,	
  eg	
  to	
  quickly	
  get	
  the	
  
assessment	
  over	
  agri.	
  epidemics	
  in	
  paddy	
  field	
  and	
  mapping	
  DOA	
  IntegraTng	
  farming	
  
area	
  without	
  the	
  need	
  to	
  wait	
  for	
  satellite	
  images	
  or	
  convenTonal	
  airplane.	
  

                                                                                                                          	
  Geo	
  Sense	
  
Sample	
  of	
  analysis	
  from	
  UAV	
  hyperspec.	
  Sensor	
  operate	
  by	
  Quantalab	
  in	
  Spain.	
  
ExisTng	
  Geo	
  Sense	
  UAV	
  
Agricultural	
  /	
  Crop	
  Monitoring	
  /Precision	
  farming	
  
Without	
  hyperspec	
  sensor	
  –	
  limited.	
  




                                                            Infrared	
  Imagery	
  
                                                            Crop	
  Analysis	
  
Sample	
  of	
  large	
  agricultural	
  area	
  (track	
  record)	
  	
  
–	
  1000	
  hectares	
  olive	
  farm	
  in	
  Cardova,	
  Spain	
  .	
  
Hyperspectral	
  imagery	
  acquired	
  with	
  an	
  UAV	
  plaOorm	
  over	
  orchard	
  crops	
  




                                                                               Imagery	
  acquired	
  at	
  40	
  cm	
  resoluTon	
  and	
  260	
  bands	
  
                                                                               in	
  the	
  400-­‐900	
  nm	
  region	
  @	
  5	
  nm	
  FWHM	
  


   Hyperspectral	
   imagery	
   acquired	
   from	
   an	
   UAV	
   plaoorm	
   and	
  
   the	
  Micro-­‐Hyperspec™	
  Imaging	
  Spectrometer	
  from	
  Headwall	
  
   Photonics.	
   Imagery	
   acquired	
   at	
   550	
   m	
   AGL	
   over	
   an	
   orange	
  
   orchard	
   where	
   stress	
   detecTon	
   experiments	
   are	
   conducted	
  
   by	
  QuantaLab	
  at	
  the	
  InsTtute	
  of	
  Sustainable	
  Agriculture	
  (IAS),	
  
   NaTonal	
  Research	
  Council	
  (CSIC),	
  Spain.	
  
Hyperspectral	
  Image	
  OrthorecQficaQon	
  




                                              AStude	
  data	
  acquired	
  with	
  an	
  AHRS	
  system	
  onboard	
  the	
  UAV	
  




Image	
   orthorecTficaTon	
   is	
   conducted	
   using	
   aqtude	
   data	
   acquired	
   with	
   an	
   AHRS	
   instrument	
  
synchronized	
  with	
  the	
  hyperspectral	
  imager.	
  Commercial	
  sojware	
  and	
  	
  IAS-­‐CSIC	
  algorithms	
  are	
  
applied	
  in	
  the	
  laboratory	
  ajer	
  each	
  flight	
  campaign.	
  
Image	
  CalibraQon	
  and	
  Atmospheric	
  CorrecQon	
  

                          Spectral	
   calibraTon	
   of	
   the	
   hyperspectral	
   instrument	
   is	
  
                          conducted	
   at	
   IAS-­‐CSIC	
   using	
   Hg-­‐Ar	
   calibraTon	
   lamps.	
  
                          Radiometric	
   calibraTon	
   coefficients	
   are	
   developed	
   in	
  
                          the	
  opTcs	
  laboratory	
  at	
  IAS-­‐CSIC	
  using	
  a	
  radiometrically	
  
                          calibrated	
   integraTng	
   sphere.	
   Image	
   calibraTon	
   and	
  
                          atmospheric	
   correcTon	
   to	
   obtain	
   surface	
   reflectance	
  
                          are	
   conducted	
   from	
   field-­‐measured	
   data	
   and	
   aerosol	
  
                          opTcal	
  depth	
  measured	
  at	
  the	
  Tme	
  of	
  flight.	
  Radiance	
  
                          and	
  reflectance	
  imagery	
  are	
  produced	
  ajer	
  calibraTon	
  
                          algorithms	
   are	
   applied	
   in	
   QuantaLab	
   IAS-­‐CSIC	
  
                          Laboratory.	
  




                                                                                             Imagery	
  acquired	
  
                                                                                             at	
  40	
  cm	
  
                                                                                             resoluTon,	
  260	
  
                                                                                             bands	
  in	
  the	
  	
  
                                                                                             400-­‐900	
  nm	
  region	
  
                                                                                             (5	
  nm	
  FWHM).	
  



Raw	
  data	
                                   Reflectance	
  data	
  
Hyperspectral	
  Image	
  SegmentaQon	
  of	
  the	
  crop	
  canopy	
  




                                                           Object	
  based	
  
                                                           image	
  analysis	
  for	
  
                                                           automaTc	
  tree	
  
                                                           crown	
  
                                                           idenTficaTon	
  and	
  
                                                           stress	
  detecTon	
  
                                                           using	
  spectral	
  
                                                           indices	
  

 Hyperspectral	
  reflectance	
  image	
                                                            Object	
  based	
  analysis	
  


Stress	
  map	
  (object-­‐based	
  analysis)	
  
                                                    Interpolated	
  themaTc	
  
                                                    maps	
  obtained	
  from	
  object	
  
                                                    based	
  analysis	
  conducted	
  
                                                    on	
  hyperspectral	
  indices	
  at	
  
                                                    the	
  tree	
  crown	
  level.	
  Stress	
  
                                                    maps	
  are	
  derived	
  based	
  on	
  
                                                    photosyntheTc	
  pigment	
  
                                                    concentraTon	
  and	
  canopy	
  
                                                    density	
  
Hyperspectral	
  Reflectance	
  from	
  a	
  water	
  body	
  




S p e c t r a l	
   r e fl e c t a n c e	
  
extracted	
   from	
   different	
  
areas	
  of	
  a	
  water	
  body	
  
Airborne	
  Hyperspectral	
  Imaging	
  for	
  
          Palm	
  Oil	
  Analysis	
  
IDENTIFICATION	
  OF	
  SELECTED	
  OIL	
  PALM	
  CHARACTERISICS	
  USING	
  
          DEVELOPED	
  SPECTRAL	
  SIGNATURE	
  LIBRARY	
  
User	
  Requirements	
  
•  Needs	
  to	
  increase	
  producTvity	
  by	
  planTng	
  more	
  (new	
  
   estate)	
  &	
  improve	
  producTvity	
  /	
  yields	
  
     –  SoluTon;	
  Maintain	
  good	
  tree	
  condiTons,	
  by	
  having	
  up	
  to	
  
        date	
  block	
  /	
  sectors	
  /	
  trees	
  informaTon	
  
     –  Healthiness	
  and	
  nutrient	
  status	
  
     –  Assets,	
  Land	
  use,	
  land	
  cover	
  (showing	
  assets	
  locaTon,	
  
        vegetaTon	
  and	
  water	
  body)	
  
•  Nutrient	
  checking	
  (leaves	
  &	
  soil)	
  –	
  up	
  to	
  individual	
  tree	
  
     –  SoluTon;	
  Soil	
  Nutrient	
  &	
  Foliar	
  Variability	
  Mapping	
  –	
  
        showing	
  the	
  availability	
  of	
  N,P,K,Mg,B(easier	
  for	
  detected	
  
        less	
  nutrient	
  area).	
  
User	
  Requirements	
  
•  Healthiness	
  oil	
  palm	
  trees	
  map	
  for	
  detecTng	
  
   stress	
  trees	
  and	
  for	
  esTmaTng	
  the	
  yield.	
  
    – SoluTon;	
  Digital	
  “stressed”	
  palms	
  map.	
  Maps	
  showing	
  
      healthy	
  trees,	
  “stressed”	
  and	
  dead	
  palms	
  and	
  
      development	
  of	
  spectral	
  signature	
  for	
  all	
  palms	
  
      condiTon.	
  
•  LocaTons	
  of	
  the	
  tree	
  with	
  un-­‐healthy	
  condiTon	
  	
  
    – SoluTon;	
  Tree	
  status.	
  Showing	
  tree	
  maturity	
  status
      (ageing)	
  
    – Individual	
  Oil	
  Palm	
  inventory	
  countswith	
  precise	
  GPS	
  
      locaTon	
  Map	
  (locaTon	
  each	
  tree)	
  
What	
  aerial	
  imagery	
  tells	
  
•    As	
  evaluaTon	
  tools	
  and	
  diagnosTc	
  kits,	
  
      –  PlantaTon	
  and	
  forestry	
  
      –  Inventory	
  
      –  Healthiness/Stressed/Disease	
  
      –  Dead	
  Trees	
  (Pest/Disease/Water	
  Stress,	
  waterlog,	
  burnt,	
  etc)	
  
      –  Species/community	
  types	
  
      –  Maturity	
  
•    Marine	
  and	
  environmental	
  features	
  
      –  Inventory	
  
      –  Community	
  types	
  
      –  Changes	
  detecTon	
  and	
  analysis	
  
      –  Coral/sea	
  weed	
  mapping	
  
      –  Water	
  quality	
  (salinity,	
  turbidity,	
  pH,	
  temperature,	
  etc)	
  
•    Physical	
  Features	
  
      –  Roads/footpath/track/rivers/streams/topo.	
  etc	
  
      –  Area	
  EsTmaTon=Gross	
  Area–Vacant	
  Area=Net	
  Area	
  
      –  Boundaries	
  
Overview	
  of	
  works	
  	
  proposal	
  –	
  design	
  and	
  develop	
  Unmanned	
  Aerial	
  Remote	
  Sensing	
  
 Facility	
  For	
  Agricultural,	
  Forestry	
  and	
  Palm	
  Oil	
  Analysis.	
  	
  




Preparing	
  	
  UAV	
  plaoorm	
                             IntegraTng	
  Micro	
  Hyperspec	
  Sensor	
  
for	
  user	
  unmanned	
  remote	
                                                                                           Image	
  capturing	
  and	
  image	
  
                                                              from	
  Honeywell	
  Photonic	
  (US)	
  advance	
              cube.	
  –	
  operate	
  by	
  Geo	
  
sensing	
  aerial	
  vehicle	
  plaoorm	
                     hyoperspec	
  	
  sensor	
  for	
  UAV	
  system.	
  Into	
  
(UAV).	
  Need	
  for	
  stable,	
  endurance	
                                                                               Sense	
  &	
  Quantalab,	
  Spain	
  
                                                              Geo	
  Sense	
  UAV	
  plaoorm.	
  
and	
  load	
  (min.	
  3	
  kg	
  load)	
  system	
          IntegraTon	
  work	
  is	
  collaboraTon	
  with	
  
Plaoorm	
  will	
  be	
  provided	
  by	
  Geo	
  Sense	
     QuantaLab,	
  Spain	
  and	
  Geo	
  Sense	
  




      Online	
  access	
  system	
  –	
                                 Design	
  &	
  develop	
  client	
  
      web	
  based	
  system	
  for	
                                   imaging	
  database	
  or	
  library	
  
      mulT	
  access	
  via	
  Internet	
  /	
                                                                                       Image	
  Analysis	
  –	
  
                                                                        system	
  for	
  review,	
  analysis	
  
      Intranet	
                                                                                                                     Quantalab,	
  Spain	
  
                                                                        and	
  decision	
  support	
  
      -­‐	
  Geo	
  Sense	
  &	
  partner	
                             -­‐	
  Quantalab	
  &	
  Geo	
  Sense	
  
Grant	
  Plan	
  
                     ExisTng	
                                                     Grant	
                                                      Spin	
  off	
  




          Hand	
  launch	
  glider	
  UAV	
                           Mid	
  range	
  UAV	
  System	
  	
                          Malaysian	
  IMU	
  system	
  
          Unmanned	
  aerial	
  mapping	
                             (20	
  kg,	
  payload	
  1.5kg)	
                            (autopilot	
  system)	
  
          Per	
  mission	
  30	
  min.	
  endurance,	
  	
            Per	
  mission	
  90	
  min	
  
          1.5	
  sq	
  km	
  per	
  mission	
                         Min.	
  3	
  sq	
  km	
  per	
  mission	
  
          6	
  	
  sq	
  km	
  (600	
  hectares)	
  per	
  day.	
     10	
  sq	
  km	
  (1000	
  hectares)	
  per	
  day	
  




                                                                                                                                     Remote	
  sensing	
  on	
  	
  
             RGB	
  compact	
  camera	
                                    Hyperspectral	
  Imaging	
                                demand	
  
                                                                           For	
  UAV	
  




             VisualizaTon	
                                                 Imaging	
  analysis	
                              Center	
  for	
  unmanned	
  remote	
  
                                                                                                                               Sensing	
  for	
  tropical	
  agri.	
  

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Geo Sense - UAV service, unmanned remote sensing

  • 1. Utilizing Hyperspectral Imaging System in unmanned aerial vehicle (UAV) for Agricultural/Palm Oil Analysis Geo  Sense  Sdn.  Bhd.   79A,  Jalan  Seri  Impian  1   T06-­‐03,  Jln  Centry  Square   Taman  Impian  Emas   Block  2320     81300  Johor  Bahru   63000  Cyberjaya     ismaili@geosense.com.my   www.geosense.com.my  
  • 2. Geo  Sense  Sdn.  Bhd.   Brief  Background   •  Establish  May  2006   •  MSC  Status  –  in  web  GIS  and  aerial  mapping   •  Pioneering  Civilian  UAV  applicaTons  /   Services   •  Skudai,  Johor  Bahru  Base  Company  &   Cyberjaya   •  CollaboraTon  with  UTM,  IMREC  and  Inst.   Sustainable  Agri  of  Cardoba  Spain   •  Since  2007  -­‐  R&D  in  unmanned  aerial   mapping  and  remote  sensing   •  Recepient  Anugerah  Perdana  Menteri  APICTA   ICT  eGov.  Catergory  in  2007   •  Vision,  to  become  leading  tech  company  in   civilian  UAV  applicaTon  
  • 3. Sources of Aerial Imagery Light Aircraft Imaging Altitude10k – 30k feet Satellite 500-800 km Cost RC AIrcarft / UAV Altitude 500 – 2000 ft •  erial Camera System A •  adiometric resolution R •  0 cm – 60 cm resolution 2 (avg 30 in resolution) Cloud Issues •  erial mapping survey A • PSAR (SAR) / LIDAR I •  atural color (RGB) N •  - 15 cm resolution 7 •  urveillance / Monitoring S 200 meter 90 km 3 km 300 meter 30 km 3 km
  • 5. Products  &  Services     Unmanned  Aerial     GIS  /       GPS  –  Geo  Tagging   Mapping   Web  GIS   Mobile  applicaTon  
  • 7. Technology  Brief   UAV  FOR  AERIAL  MAPPING  &   SURVEILLANCE  SERVICES  
  • 8. UAV  Aerial  Mapping  –  Process  Flow   UAV  Image  AcquisiTon   Flight   UAV   Transferring   Launching   Monitoring   Recovering   Planning   InstallaTon   Plan   Image  Processing   Raw   Overlaying   Mosaic  /  STtching   Tiling   Images   RegistraTon  
  • 9.
  • 10.
  • 11. 27  March  2010   22  July  2010  
  • 12. INTEGRATION  WITH  GIS  PLATFORM  
  • 14. Forest  Clearing  &     PlantaTon  Planning  
  • 16. Progress Monitoring  Rumah Rakyat IRDA June  2010   Oct  2010   Feb  2011  
  • 17. Potential Applications Work Auditing / Verification Feb  2010   June  2010  
  • 18. Case  Study  1  -­‐  UAV  Mapping  by  Geo  Sense    –  Semporna,  Sabah  (5  sq  km)   Visual  Using  UAV   PopulaTon:  ~  130K   Mail  Volume:  ~  200  per  day   PO:  Semporna  Post  Office   Mail  delivery:  limited     Address:  Using  kampung,  schools  &   PO  Box  (710  units)   Bank:  Maybank  &  BSN  
  • 19. House  Numbering  and  Address  Assignment  by  Pos  Malaysia   DigiTzing  using  GIS   KAMPUNG  BANGAU-­‐BANGAU   2,436  houses   ADDRESS  SAMPLE   Cikgu  Ahmad     No2,  KampungBangauBangau   PERKAMPUNGAN  AIR  1   91300  Semporna,  Sabah   659  houses   PERKAMPUNGAN  AIR  2   Lat  4.4883  N   Long  118.6050  E   3,313  houses   Approximately  6,000  new   delivery  points  idenTfied    
  • 20. Base Map Preparation – Using High Res Aerial Image from UAV High  resoluTon  UAV  Images   Image  digitalizing   Asset  Data  in  Base  Map   Base  Map  from  high  res  images  
  • 21. 3D  /  DTM  –  OrthoracTficaTon  Process   Sojware  upgrade  
  • 23. Project  Monitoring  and  CommunicaTon  (PMCS)  
  • 24. Scope  of  Work  &  Delivery   UAV  capturing  images   Image  process  &  digitalizing   The  big  mosaic  (sTtched)  image   Image  presentaTon  &  potenTal  uTlizaTon   Big  Poster   Tiles  for  quick  viewing   Online  Tles  visualizaTon   Image  registraTon  (GIS)   IntegraTon  with     -­‐  Project  GIS     Project  Management   -­‐  Project  monitoring  and   System   Online  visualizaTon   Quick  distribuTon  –  images   reporTng  system   -­‐  Structure  modeling   Online  archiving  system   store  in  DVD   -­‐  Decision  support   with  WBS   system  
  • 26.  Quanta  Lab    Geo  Sense   Geo  Sense,  is  Malaysian  MSC  Status  company,  that  is  using   unmanned  aerial  vehicle  (UAV)  for  aerial  mapping  and  remote   sensing.  Geo  Sense  is  collaboraTng  with  Dr.  Pablo  J.  Zarco  Tejada   the  Director  of  Laboratory  for  Research  in  QuanTtaTve  Remote   Sensing,  under  the  InsTtute  of  Sustainable  Agricultural  in  Cardoba,   Spain  in  uTlizing  UAV  for  advance  remote  sensing  for  agricultural     purposes.      Geo  Sense  
  • 27. CollaboraTon  of  experts  between  Quantalab  and  Geo  Sense  Sdn.  Bhd.    Profile    Pablo  J.  Zarco  has  been  Course  Director  and   Dr  Pablo  J.  Zarco  Tejada   Teaching  Assistant  within  the  Departments  of   Environmental  Science,  and  Earth  and  Space   Ph.D.  in  Earth  and  Space  Science,  York   Science  (  York  University  ,  Canada  ),  and  Land,  Air,   University  (Canada),  2000     and  Water  Resources  (LAWR),  University  of   M.Sc.  in  Remote  Sensing,  Image   California  Davis  ,  in  courses  related  to   Processing  and  ApplicaTons.  Dept.  of   Environmental  Science  and  Remote  Sensing.  He   Applied  Physics,  Electronic  and   has  also  collaborated  in  other  courses  at  University   Mechanical  Engineering  (APEME),   of  California  ,  Davis  in  Precision  Agriculture  and   University  of  Dundee  (Scotland  ,  UK),   Environmental  Remote  Sensing:     1997     Since  2008,  Dr  Pablo  has  been  uTlizing  UAV  for   B.S.  Agricultural  Engineering  (Cordoba  ,   agri.  remote  sensing.   Spain)      Geo  Sense  
  • 28. The  collaboraTon  will  offer  Malaysia  users  to  access  to  the  latest  technology  in   agricultural  monitoring  and  analysis  using  UAV  for  quicker  respond  at  lower  cost   compare  with  convenTonal  methods.   The  UAV  with  mulT  spectral  camera  enable  to  meet  any  on  demand  request  for   urgent  requirement  in  any  agricultural  respond  and  analysis,  eg  to  quickly  get  the   assessment  over  agri.  epidemics  in  paddy  field  and  mapping  DOA  IntegraTng  farming   area  without  the  need  to  wait  for  satellite  images  or  convenTonal  airplane.    Geo  Sense  
  • 29. Sample  of  analysis  from  UAV  hyperspec.  Sensor  operate  by  Quantalab  in  Spain.  
  • 30. ExisTng  Geo  Sense  UAV   Agricultural  /  Crop  Monitoring  /Precision  farming   Without  hyperspec  sensor  –  limited.   Infrared  Imagery   Crop  Analysis  
  • 31. Sample  of  large  agricultural  area  (track  record)     –  1000  hectares  olive  farm  in  Cardova,  Spain  .  
  • 32. Hyperspectral  imagery  acquired  with  an  UAV  plaOorm  over  orchard  crops   Imagery  acquired  at  40  cm  resoluTon  and  260  bands   in  the  400-­‐900  nm  region  @  5  nm  FWHM   Hyperspectral   imagery   acquired   from   an   UAV   plaoorm   and   the  Micro-­‐Hyperspec™  Imaging  Spectrometer  from  Headwall   Photonics.   Imagery   acquired   at   550   m   AGL   over   an   orange   orchard   where   stress   detecTon   experiments   are   conducted   by  QuantaLab  at  the  InsTtute  of  Sustainable  Agriculture  (IAS),   NaTonal  Research  Council  (CSIC),  Spain.  
  • 33. Hyperspectral  Image  OrthorecQficaQon   AStude  data  acquired  with  an  AHRS  system  onboard  the  UAV   Image   orthorecTficaTon   is   conducted   using   aqtude   data   acquired   with   an   AHRS   instrument   synchronized  with  the  hyperspectral  imager.  Commercial  sojware  and    IAS-­‐CSIC  algorithms  are   applied  in  the  laboratory  ajer  each  flight  campaign.  
  • 34. Image  CalibraQon  and  Atmospheric  CorrecQon   Spectral   calibraTon   of   the   hyperspectral   instrument   is   conducted   at   IAS-­‐CSIC   using   Hg-­‐Ar   calibraTon   lamps.   Radiometric   calibraTon   coefficients   are   developed   in   the  opTcs  laboratory  at  IAS-­‐CSIC  using  a  radiometrically   calibrated   integraTng   sphere.   Image   calibraTon   and   atmospheric   correcTon   to   obtain   surface   reflectance   are   conducted   from   field-­‐measured   data   and   aerosol   opTcal  depth  measured  at  the  Tme  of  flight.  Radiance   and  reflectance  imagery  are  produced  ajer  calibraTon   algorithms   are   applied   in   QuantaLab   IAS-­‐CSIC   Laboratory.   Imagery  acquired   at  40  cm   resoluTon,  260   bands  in  the     400-­‐900  nm  region   (5  nm  FWHM).   Raw  data   Reflectance  data  
  • 35. Hyperspectral  Image  SegmentaQon  of  the  crop  canopy   Object  based   image  analysis  for   automaTc  tree   crown   idenTficaTon  and   stress  detecTon   using  spectral   indices   Hyperspectral  reflectance  image   Object  based  analysis   Stress  map  (object-­‐based  analysis)   Interpolated  themaTc   maps  obtained  from  object   based  analysis  conducted   on  hyperspectral  indices  at   the  tree  crown  level.  Stress   maps  are  derived  based  on   photosyntheTc  pigment   concentraTon  and  canopy   density  
  • 36. Hyperspectral  Reflectance  from  a  water  body   S p e c t r a l   r e fl e c t a n c e   extracted   from   different   areas  of  a  water  body  
  • 37. Airborne  Hyperspectral  Imaging  for   Palm  Oil  Analysis  
  • 38. IDENTIFICATION  OF  SELECTED  OIL  PALM  CHARACTERISICS  USING   DEVELOPED  SPECTRAL  SIGNATURE  LIBRARY  
  • 39.
  • 40.
  • 41.
  • 42.
  • 43.
  • 44.
  • 45.
  • 46.
  • 47. User  Requirements   •  Needs  to  increase  producTvity  by  planTng  more  (new   estate)  &  improve  producTvity  /  yields   –  SoluTon;  Maintain  good  tree  condiTons,  by  having  up  to   date  block  /  sectors  /  trees  informaTon   –  Healthiness  and  nutrient  status   –  Assets,  Land  use,  land  cover  (showing  assets  locaTon,   vegetaTon  and  water  body)   •  Nutrient  checking  (leaves  &  soil)  –  up  to  individual  tree   –  SoluTon;  Soil  Nutrient  &  Foliar  Variability  Mapping  –   showing  the  availability  of  N,P,K,Mg,B(easier  for  detected   less  nutrient  area).  
  • 48. User  Requirements   •  Healthiness  oil  palm  trees  map  for  detecTng   stress  trees  and  for  esTmaTng  the  yield.   – SoluTon;  Digital  “stressed”  palms  map.  Maps  showing   healthy  trees,  “stressed”  and  dead  palms  and   development  of  spectral  signature  for  all  palms   condiTon.   •  LocaTons  of  the  tree  with  un-­‐healthy  condiTon     – SoluTon;  Tree  status.  Showing  tree  maturity  status (ageing)   – Individual  Oil  Palm  inventory  countswith  precise  GPS   locaTon  Map  (locaTon  each  tree)  
  • 49. What  aerial  imagery  tells   •  As  evaluaTon  tools  and  diagnosTc  kits,   –  PlantaTon  and  forestry   –  Inventory   –  Healthiness/Stressed/Disease   –  Dead  Trees  (Pest/Disease/Water  Stress,  waterlog,  burnt,  etc)   –  Species/community  types   –  Maturity   •  Marine  and  environmental  features   –  Inventory   –  Community  types   –  Changes  detecTon  and  analysis   –  Coral/sea  weed  mapping   –  Water  quality  (salinity,  turbidity,  pH,  temperature,  etc)   •  Physical  Features   –  Roads/footpath/track/rivers/streams/topo.  etc   –  Area  EsTmaTon=Gross  Area–Vacant  Area=Net  Area   –  Boundaries  
  • 50. Overview  of  works    proposal  –  design  and  develop  Unmanned  Aerial  Remote  Sensing   Facility  For  Agricultural,  Forestry  and  Palm  Oil  Analysis.     Preparing    UAV  plaoorm   IntegraTng  Micro  Hyperspec  Sensor   for  user  unmanned  remote   Image  capturing  and  image   from  Honeywell  Photonic  (US)  advance   cube.  –  operate  by  Geo   sensing  aerial  vehicle  plaoorm   hyoperspec    sensor  for  UAV  system.  Into   (UAV).  Need  for  stable,  endurance   Sense  &  Quantalab,  Spain   Geo  Sense  UAV  plaoorm.   and  load  (min.  3  kg  load)  system   IntegraTon  work  is  collaboraTon  with   Plaoorm  will  be  provided  by  Geo  Sense   QuantaLab,  Spain  and  Geo  Sense   Online  access  system  –   Design  &  develop  client   web  based  system  for   imaging  database  or  library   mulT  access  via  Internet  /   Image  Analysis  –   system  for  review,  analysis   Intranet   Quantalab,  Spain   and  decision  support   -­‐  Geo  Sense  &  partner   -­‐  Quantalab  &  Geo  Sense  
  • 51.
  • 52. Grant  Plan   ExisTng   Grant   Spin  off   Hand  launch  glider  UAV   Mid  range  UAV  System     Malaysian  IMU  system   Unmanned  aerial  mapping   (20  kg,  payload  1.5kg)   (autopilot  system)   Per  mission  30  min.  endurance,     Per  mission  90  min   1.5  sq  km  per  mission   Min.  3  sq  km  per  mission   6    sq  km  (600  hectares)  per  day.   10  sq  km  (1000  hectares)  per  day   Remote  sensing  on     RGB  compact  camera   Hyperspectral  Imaging   demand   For  UAV   VisualizaTon   Imaging  analysis   Center  for  unmanned  remote   Sensing  for  tropical  agri.