1 / 1

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

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.

emory
Download Presentation

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

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  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 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.

More Related