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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. Route programmed into the GPS.

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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

Route programmed into the GPS

The UAV’s that have been used

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.