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Manoj Karkee Agricultural Automation and Robotics Lab

Precision Agriculture Technologies

BSysE 551: Advanced Topics on Precision Agriculture Technologies – FALL 2014

Instructor: Manoj Karkee (manoj.karkee@wsu.edu)

Goals and Objective:

Understanding the principles and applications of various tools and technologies used in precision agriculture including Global Navigation Satellite Systems (GNSS), Remote Sensing, Geographic Information System and Science (GIS), Variable Rate Technologies (VRT), and Yield Monitoring.

 

Text:

The Precision-Farming Guide for Agriculturists, Morgan and Ess, Deere & Company, 2010 Edition.
Software

GRASS or ArcGIS (or any other Remote Sensing/ GIS Package)

 

References:

  • Geographic Information Systems: An Introduction, Jeffrey Star and John Estes
  • Hermann J. Heege, Editor; Precision in Crop Farming: Site Specific Concepts and Sensing Methods: Applications and Results

 

Syllabus and Schedule

Week 1 and 2 (August 25 to Sep 7)

Introduction to Precision Agriculture

Sensing, GIS and GPS technologies, Prescription Maps, Yield Monitoring, Variable rate technology

Introduction to GIS

Essential Elements of GIS; Vector Vs Raster Data Structures; Data Structure Conversion; Rectification, and Registration including map projection and Coordinate Systems; Interpolation and Coordinate transformation                

 

Week 3 and 4 (Sep 8 to Sep 21)

Additional Topics in GIS

Reclassification and Aggregation; Geometric Operation on Special Data; GIS-based modeling; Statistical Analysis including descriptive statistics and histograms

 

Week 5 and 6 (Sep 22 to Oct 5)

Global Navigation Satellite Systems (GNSS)

Fundamental principles of GNSS; Understanding GPS including satellites, constellation, sensors and applications; DGPS and RTK GPS; Position and altitude Accuracies with different types of GPS sensors

 

Week 7 and 8 (Oct 6 to Oct 19)

Remote Sensing

Introduction of Remote Sensing; Fundamental principles including spectral signature of landcover classes; Applications of remote sensing; Remote Sensing and GIS

 

Platforms: Satellites, Manned Aircrafts, UASs, ground vehicles, fixed platforms

Active and Passive Sensors: Cameras, Stereo-vision, Laser, RADAR, SAR, Thermal, Spectroscopy, Multi- and Hyper-Spectral Imagers

 

Week 9 and 10 (Oct 20 to Nov 2)

Remote Sensing Image Interpretation

Clustering; Classification; Crop Stress Sensing; DEM, DTM and TIN; DEM Processing including slope and aspect

 

Week 11 and 12 (Nov 3 to No 16)

Auto-steering and automatic implement control systems

Understanding of System Components, How the system works, what are the applications?

Variable Rate Technologies;

Understanding of System Components, How the system works, what are the applications?

 

Week 13 and 14 (Nov 17 to Dec 7; includes thanksgiving break):

Yield Monitoring

Yield monitoring systems for row/grain crops; research and development in yield monitoring in specialty crops; yield mapping; application/use of yield data/maps in precision agriculture including variable rate input application

 

Week 15 and 16 (Dec 8 to Dec 19; includes finals week): Project Completion; Presentation; Final Report

 

Homework/Lab Exercises

 

Lab 1: Collect/acquire or derive soil, elevation, slope, aspect, rainfall and irrigation system maps of Benton Country, WA; and use GIS-based modeling to develop apple planting suitability map.

 

Report – due by Sep 30th

 

Lab 2: Collect location data with a RTK GPS system in a cherry orchard (a GPS mounted vehicle to collect 3D position of 5 rows of trees)

 

Report – due by Oct 30th

 

Lab 3: Identify 10 different public or commercial platforms (including satellites and Aerial platforms) and report their attributes including altitude, sensor type, Field of View and Instantaneous Field of View, temporal, spatial and spectral resolution, cost per unit area covered, and availability of elevation data.

 

Report – due by Nov 26th

 

Lab 4: Obtain a remote sensing image of Benton County and develop a NDVI map. Collect 2 data points for each class as ground truth data and use that to develop a landcover map using a supervised classification method. Four classes are necessary; vegetation (including agriculture, forest, lawn etc.) barren land, water bodies and built up area.

 

Report – due by Dec 19th

 

Deliverables and Grading

  • Four bi-weekly laboratory reports (data collection can be done together; reports should be submitted individually) – 40%;
  • A group project proposal due on 30th Sep – 20%
  • Final project presentation; Dec 15 – 20%
  • A final project report; Dec 19 – 20%

 

A few quick links to GRASS

http://grass.osgeo.org/news/37/60/GRASS-GIS-7-0-0-beta3/

http://grass.osgeo.org/documentation/tutorials/

http://grass.osgeo.org/documentation/first-time-users/

http://grass.osgeo.org/grass64/manuals/imageryintro.html

 

A few other helpful links:

http://www.agmachinery.okstate.edu/PrecisionAgTech

http://catalog.iastate.edu/collegeofagricultureandlifesciences/systemstechnology/systemstechnology.pdf

 

Special Note:

Students are encouraged to provide feedbacks to the class by Sep 30th and again by Dec 19th on the following five categories. Two to three bullet points for each question would be appreciated!!!

  1. What did you expect to learn in the class?
  2. Did the course content meet your expectation?
  3. Course demand (Circle one): Low, Below Average, Average, Above Average, High
  4. Positive aspects of the overall class
  5. Aspects that needs could be improved/modified