Unmanned Aerial Vehicle System for Remote Sensing Applications

1
Unmanned Aerial Vehicle System for Remote Sensing
Applications in Agriculture and Aquaculture

• Dr. Randy. R. Price, Goutam . J. Nistala, Dr.
  Steven G. Hall
• Department of Biological and Agricultural
  Engineering
• Louisiana State University, AgCenter

LSU BAE
The UAVs that have been used
Route programmed into the GPS

• Remote Sensing in Agriculture and Aquaculture
• Determination of a quantity by detecting it
• from a distance.
• A common application of remote sensing is the
• use of satellite-borne instruments to determine
• the location and amount of resources on the
• surface of the Earth.
• Management of agricultural crops and
• aquacultural products is important.
• Yield of crops is based on many factors like
• inputs, weather, irrigation conditions, quality
  of pesticides and several other factors.
• Optimization of inputs, yield and quality is
  very important.
• Other methods like self diagnostics, crop
  scouting and pest reduction are inefficient and
  
• result in redundant application of resources.
• Remote Sensing is looked upon as the
  alternative.
• Piloted aircraft and satellites are the primary
• sources used to obtain RS images.

• Disadvantages
• Significant experience required to fly the
• UAV.
• Easily destructible.

• Objectives
• To explore the use of an UAV for acquiring
  remotely sensed imagery and data in a cost
  efficient manner
• To construct an UAV and its control system with
  stable flight characteristics
• To make the UAV autonomous with an automatic
  guidance system
• To equip the UAV with an image acquisition system.

and destroyed
Actual track of the UAV flight

Control System Types Manual Control
Aerial images
Agriculture Aquaculture
Use of FMA-Copilot

• Satellite Imagery for Remote Sensing
• Advantages
• The system is reliable.
• The farmer need not have special skills to
• obtain and use the data .
• Disadvantages
• The quality and resolution of data and
• imagery obtained may not be sufficient for
  
• accurate diagnostics.
• Data obtained can be easily affected by bad
• weather conditions like clouds or rain.
• Non availability of data when and where
• required .The data can be obtained only at
• regular intervals .
• Very expensive.

• The co-pilot uses four infrared temperature
  sensors to monitor the aircrafts relationship to
  earths horizon.
• In the infrared spectrum ,the earth is warm below
  the horizon and the sky is cold above the
  horizon.
• The copilot senses the aircrafts position
  relative to horizon during a flight and sends
  corrective signals to the aileron and elevator
  servos.

• Conclusions
• UAVs provide possibilities for
• Image capture at low altitude, reducing cloud
  problems
• Interaction with pests including birds on
  aquaculture ponds
• Automated or semi-automated operation, reducing
  labor
• Repeatable performance
• Cost effective use of technology
• Further testing is underway

• Automated Flight Control

• Calculation of NDVI
• The Normalized Difference Vegetative
• Index (NDVI,) is a calculation, based on
• several spectral bands, of the photosynthetic
• output in a pixel in an image.
• It measures the amount of green vegetation
• in an area.
• Actively growing green plants strongly
• absorb radiation in the visible region of the
  
• spectrum (Photo synthetically.
• Active Radiation) while strongly reflecting
• radiation in the Near Infrared region.
• The UAV obtained images are used to
• calculate NDVI values of the entire field .

Selected references

• Continuous Georeferencing for video based remote
  sensing on agricultural
• aircraft - S.J.Thomson, J.E.Hanks, and
  G.F.Sassenrath-Cole. Published in the
  transactions of ASAE Vol 45(4)1177-1189.
• Airborne Multispectral Imagery for mapping
  variable growing conditions and yields of cotton,
  grain sorghum and corn - C.Yang, J.M. Bradford,
  C.L.
• Wiegand
• The Development of Remote Sensing System using
  Unmanned Helicopter
• Ryo SUGIURA, Noboru NOGUCHI, Kazunobu
  ISHII, Hideo TERAO.
• Proceedings of the July 26-27, 2002
  Conference (Chicago, Illinois, USA)
• 701P0502.
• A Hyperspectral Imaging System for Agriculture
  Applications Chenghai
• Yang, James H. Everitt, Chengye Mao.
  Written for presentation at the 2001
• ASAE Annual International Meeting,
  sponsored by ASAE Sacramento
• Convention Center.

• Unmanned Aerial Vehicle
• Advantages
• 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.