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
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.

Route programmed into the GPS
Disadvantages
 Significant experience required to fly the
UAV.
 Easily destructible.
LSU BAE
The UAV’s that have been used
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.
Actual track of the UAV flight
Control System Types
Manual Control
and destroyed
Aerial images
Agriculture
Aquaculture
Use of FMA-Copilot
Satellite Imagery for Remote Sensing

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.
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.
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.

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 .

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
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.