6.1 Spatial Applications for Agriculture: Educational Case studies - Phase II
Investigators:
Dr. Thomas Mueller, Agronomy, mueller@uky.edu
Dr. Timothy Stombaugh, Biosystems and Agricultural Engineering, tss@uky.edu
Dr. Scott Shearer, Biosystems and Agricultural Engineering, shearer@bae.uky.edu
Dr. Haluk Cetin, Mid-America Remote Sensing Center, Murray State University, Haluk.Cetin@MurrayState.edu
Introduction:
Precision agriculture is about analyzing spatial data. For many research applications and some commercial applications in precision agriculture, ARC/View, ARC/INFO, or Arc/GIS software are used. For many commercial applications, programs specifically designed for precision agriculture are used. In the first phase of this proposal, we propose the development of educational modules for GIS applications for higher end users in GIS analysis. For the second phase of this proposal, we will use these funds to support a technical position that will assist in training for a wide variety of audiences requiring applied and more basic training in GIS for precision agriculture applications. Specifically, the person will provide support for the phase III proposal entitled “Outreach Education for Precision Agriculture”.
Objectives
The objectives of this proposal are as follows:
1) To develop a minimum of 5 new web-based GIS educational modules for precision agriculture applications.
2) To refine existing web based educational modules.
3) To assist training with the UK mobile precision agriculture computer training laboratory.
Background:
We will discuss the “Spatial Applications for Agriculture: Educational Case Studies”, a three year project funded in 2000 as part of phase II USDA precision agriculture funding at University of Kentucky . For the first year, we proposed the following modules: Coordinate Conversion and Datums - Boundary Mapping and Area, Yield Map Generation, Soil Sampling, Interpolation Techniques for Map Generation. In year 2, we proposed to develop educational modules in Land-Use Determination form Historical Yield Data, Profit Map Generation, Variable-Rate Fertilizer Recommendations, Variable-Rate Fertilizer Application, and Economics of Variable-Rate Fertilizer Application. In year 3, we proposed to develop modules for, Remote Sensing, Variable-Rate Seeding, Conducting On-Farm Investigations, Variable-Rate Nitrogen Application, Soil Conductivity Correlation with Landscape Features.
As we start the third year of this project, we are ahead of schedule. Most but not all of the modules have been completed: as can be seen in detail by visiting the class web site for BAE 599 - Topics in Agricultural Engineering: Precision Agriculture: http://www.bae.uky.edu/~precag/BAE599/Pages/BAE_599.htm. These modules will not only be used for the BAE 599 course, but at Murray State and Western Kentucky University as part of the Kentucky Precision Agriculture Consortium in a project funded with Phase III USDA precision agriculture funding for Kentucky. Dr. T.G. Mueller, one of the PI’s on both proposals, has developed modules as part of the Phase II funding and modules for PLS 468G, Soil Use and Management. Since most of the modules in this exercise will be accomplished by Dr. Mueller, we will discuss some of his past educational module development. All of these modules are step by step, in many cases keystroke by keystroke.
The education module, “Site Specific Soil Sampling” http://www.uky.edu/~mueller/SiteSpecificSoilSampling/) focuses on matching grid soil sampling data with publicly available data from the web (Fig. 1), to interpolate it (Fig. 1), and to evaluate its quality (Fig. 2).
Fig. 1.Soil phosphorus point measurements overlain on an aerial photograph (left) and interpolated (right).
Fig. 2. Predicted versus measured plots of soil phosphorous to help students to assess the quality of their interpolations.
Fig. 3. Soil surveys for spatial applications: Yield potential obtained from soil digital soil use maps (left) available from the web overlain on a digital USDA topographic map (DRG). A georeferenced and rectified soils map (right) overlain (black lines) set to be 65 transparent is overlain on an aerial photograph. Note that the yellow represents digitization in progress.
A module entitled “Landscape Spatial data on the Web” was developed (http://www.uky.edu/~mueller/pls468g/SoilsData_on_the_Web/) that teaches students to download soil survey data from the web and to make maps of NRCS - yield potential (Fig. 3 left).
Unfortunately, not all soil maps have been digitized in Kentucky so an exercise was developed for PLS 468G (http://www.uky.edu/~mueller/pls468g/home/; “Soil Use and Management”) to train students to digitize soil maps: The module is entitled: “Heads-Up Digitization of soil Surveys” (http://www.uky.edu/~mueller/pls468g/digit_soil_survey/). The students learn to register and rectify a scanned soil survey, to overlay it on a georeference aerial photograph available on the web for all of Kentucky (DOQQ), and to create a spatial data layer of the soils in that field (Fig. b). Students also learn to digitize field boundaries with DOQQ’s and calculate their areas in an exercise entitled “Field Boundaries and Areas” (http://www.uky.edu/~mueller/pls468g/bound/;).
Procedures
During the first year, we will develop 5 additional stand alone training modules. Dr. Mueller is primarily responsible for the first years work. During the second year, we will provide training either on campus at UK or with Dr. Stombaugh’s mobile training laboratory. The training will include modules developed with Phase II funding and Phase III funding. Dr. Stombaugh will be primarily responsible for the second year of the proposal. Dr. Mueller and Dr. Shearer will both provide support for the training efforts. The new proposed training modules are as follows:
An Introduction to GIS – This module will be a self study tutorial to teach students rudimentary aspects of GIS in a precision agriculture context specific to Kentucky. The goal of this assignment is to effectively introduce students enrolled in PLS 468G the fundamentals of GIS as a homework assignment rather than using valuable class time.
An Introduction to GPS – Most undergraduates in the school of agriculture have little or no hands on experience with GPS systems. We will develop a self study tutorial for students to learn the fundamentals of GPS and gain hands on experience using an IPAQ GPS system mapping system. Dr. Stombaugh is an expert in this area and we will use some of his previous publications and education modules developed from phase III funding USDA UK precision agriculture funding for the development of this module. The hands on component of this module will involve students checking out an IPAQ system – GPS system from Dr. Mueller’s office. Then they will map specific features on campus. This module will be used in other courses and for on campus training programs.
Calculation of Terrain Attributes – In this exercise, we will calculate terrain attributes from the DEMs developed in the previous elevation module and DEM’s down loaded from the internet. The DEM’s from the internet are not as accurate or intensive as the DEM’s we will create, but are available for every acre in Kentucky. Terrain attributes include slope, aspect, curvature, and a wetness index. We will compare these terrain attributes to crop yield and soil properties. This module will be used as an exercise in PLS 468G.
Electrical Conductivity (EC): Advanced Methods – Dr. Mueller has nearly completed an EC module for the precision agriculture course. Essentially for that exercise, the students will learn what EC is and how it relates to soil properties, how to collect it, interpolate it, and how to summarize EC measurements it by soil type. For the exercise we are proposing for this round of funding, the students will learn to calibrate EC readings with field measurements and soil sampling and analysis and geostatistical techniques for determining the appropriate sampling intensity. If the proposal entitled “Management Opportunity Maps” is funded in this same round of proposals. This module will be primarily for graduate and extension education.
Remote Sensing – Advanced Methods – Students will learn to manage remote sensed imagery with ARC/GIS. They will use the raster functions to calculate remote sensing indices such as NDVI and SAVI and relate these to yield maps variability and soil properties. Dr. Haluk Cetin from Murray State Mid America Center for Remote Sensing will be instrumental in developing this module.
Expected Benefits
These education modules will significantly improve graduate and undergraduate training in spatial technologies at the University of Kentucky. We also will provide training to farmers, extension agents, state government employees, and individuals in agribusiness. In summary, we will help develop a better-trained work force for precision agriculture in Kentucky.
Deliverables
We will develop a minimum of 6 web-based training modules for spatial applications agriculture. We will provide GIS training to citizens in Kentucky. These will also be available for students studying precision agriculture at Murray State and Western Kentucky University. We will provide training for faculty, staff, students, farmers, extension personal, and industry personal in Kentucky.