Performing Department
BIOSYSTEMS AG EGR
Non Technical Summary
This project will engage undergraduate (UG) students (15/year) in smart agricultural technologies. The proposal primarily aims to introduce and impart an understanding of the latest high-resolution satellite-based microwave synthetic aperture radar (SAR) remote sensing observations for agricultural applications to the junior/senior-level undergraduates, particularly focusing on underprivileged, minority, and women in STEM. The project addresses the AFRI Farm Bill Priority Areas (4-5). The proposed REEU effort will enhance the undergraduate's know-how on the SAR applications for agricultural and will consequently make them high-skilled as compared to their peers. Such training will place them comfortably with attractive emolument is the increase market of SAR-based application for agriculture.In recent times, with the advent of microwave SAR, it is possible to monitor crop and farmland through cloud cover with day-night capabilities at high-resolution (<50 m). SAR observations carry information of crop characteristics and surface soil moisture. These attributes of SAR enable to differentiate among crops, track phenology, determine crop acreage, estimate water stress, and monitor drought. This advances the SAR-based application for improving productivity, sustainability, and agricultural intensification. Such knowledge of the current status of the crops is also strategically important for agronomist, agricultural scientist, agro-insurance companies, agro-food industries, and also federal institutions such as the USDA-NIFA) and USDA NASS. Therefore, we designed a structured and comprehensive coursework for the undergraduate trainees that includes classroom lectures, hands-on in-lab, and farm extension activities to make them proficient in applying SAR observations for agricultural sustainability, intensification, and extract current geo/biophysical status.
Animal Health Component
100%
Research Effort Categories
Basic
0%
Applied
100%
Developmental
0%
Goals / Objectives
The proposal primarily goal isto introduce and impart an understanding of latest high-resolution satellite-based microwave SAR remote sensing observations for agricultural applications to the junior/senior-level undergraduates, particularly focusing on underprivileged, minority, and women in STEM.To achieve the primary goal, the proposed REEU has the following specific objectives:Obj-1: Design an efficient onsite 6-week coursework and experimental learning that includes lectures, hands-on, field work, evaluation, and certification.Obj-2: Identify 15 potential junior/senior level UG students each year from across the nation with at least 60% students from the minority-serving universities, underprivileged communities, and women from STEM disciplines.Obj-3: Create an efficient logistical and comprehensive financial plan for the project.Obj-4: Develop a web-page to highlight the curriculum and increase the outreach throughout the country to attract prospective students to the program.Obj-5: Develop a follow-up plan to track and help all the trainees (UG students) beyond their participation in the program to demonstrate the impacts of the program on career choices and post-graduation employment and/or enrollment in higher education.?
Project Methods
Methods1. Student Recruitment, Selection, and Retention: The first task of the project is to develop a functional and efficient web-page for the program. It is key to publicize the program coursework and structure, duration, recruitment eligibility, the application process, remuneration, boarding and lodging, other logistical issues, details of instructors, and MSU available to the program. The applicant will apply for the program through the website. PD-Das and Co-PDs will reach out to Minority Serving Institutions and various university to get optimal number of applicants.After preliminary reviews, the project team will conduct interviews to prepare a final list of potential candidates based on their qualifications, motivation level, perspectives on research, and plans for higher studies. This process will identify 15/year junior-/senior-level UG students.The team will then work with the BAE department and the MSU Housing Services to facilitate the formal logistics of the program.2 Nature of Student Activities: The program coursework shown in Tables 1-2 is designed to make trainees proficient through comprehensive SAR data use for agricultural applications classes and in tandem field exercises.Classroom Lectures: The classroom lectures will be 40% of the overall course duration of 6 weeks (12 hours each week). The PD and Co-PDs will teach topics covering - introduction to remote sensing, microwave remote sensing by SAR, and application of SAR observations to agriculture.Table 1: Outline of the coursework, classroom lectures.S No.Description of the course topicDurationInstructor1.Introduction to Remote Sensing4 hoursPD Das2.Introduction to Microwave Remote Sensing4 hoursPD Das3.Current Practices of Satellite Data at Visible and Thermal frequencies for Agricultural Applications4 hoursCo-PD Ray4.Active Microwave Remote Sensing and SAR4 hoursPD Das5.Past, Current, and Future SAR Airborne and Satellite Missions4 hoursPD Das6.SAR Observations and Soil Moisture Retrievals4 hoursPD Das7Software Tools for SAR Data Processing and Analysis.3 hoursPD Das8.Introduction to Various Data Format used For SAR data3 hoursCo-PD Ray9.Demonstration of Various SAR Data (Sentinel-1A/B, ALOS PALSAR, and Upcoming NISAR Mission).3 HoursPD Das10.Demonstration of Various SAR Data (Sentinel-1A/B, ALOS PALSAR, and Upcoming NISAR Mission).3 HoursPD Das11.SAR Observations for Agricultural Applications-I3 hoursPD Das12.SAR Observations for Agricultural Applications-II3 hoursPD Das13.Calibration and Validation of SAR-based Products3 hoursCo-PD Ray14.Fusion of SAR data with Other Satellite Products for Enhanced Agricultural Applications3 hoursCo-PD Ray15.Class Project Discussion and Team Formation4 hoursPD Das and Co-PD Ray16.Leadership, Teamwork, Professional Dev. lectures4 hoursFrom MSU SROP Leaders17.Special topic presentations (Guest Lectures) from USDA, NASA, and Cornell University2 hoursCathleen Jones,Rowena LohmanMichael Cosh18.Lectures from industry experts from Applied Geosolutions (AG), Planet Watchers (PW), National Crop Insurance Services (NCIS)3 hoursNathan Torbick (AG), Dominic Edmunds (PW), Tom Zacharias (NCIS)Total61 hoursHands-on and Lab work: Along with the classroom lectures, the most important aspect of this training is the hands-on work. We will have at least 2 hours of hands-on every day of the program. As shown in Table 2, the plan will mirror the lessons during the coursework lectures to facilitate cognitive and hands-on tandem learning to enhance the retention of the skills acquired in the classroom and lab setup. The project team will provide each student with an electronic media (high-end thumb drive) comprising a day-specific hands-on exercise folder that includes GUI, downloaded SAR data (Sentinel-1A/B and if available NISAR data).Table 2: Outline of the hands-on exercise in the BAE computer lab to be instructed by the Project team.S No.Description of the topic covered in computing labDuration1.Introduction to Python GUI tools for SAR Processing,4 hours2.Download of current Satellite Data (Sentinel-1, PALSAR, and SMAP), know the data format and rendering4 hours3.Download of current Satellite Data (LandSat, MODIS), computing NDVI for agricultural application4 hours4.Work on downloaded SAR data from Sentinel, PALSAR, and NISAR (if available) to understand the data attributes4 hours5.Work on downloaded SAR data from Sentinel, PALSAR, and NISAR (if available) to understand the data attributes, and influence of soil roughness, vegetation4 hours6.Understanding SAR-based soil moisture retrievals and applying the soil moisture disaggregation algorithm to obtain high-resolution (100 m) over agricultural farms4 hours7.Using SAR-based vegetation attributes retrievals and over agricultural farms4 hours8.Using SAR-based vegetation attributes retrievals to detect crop water stress3 hours9.Using SAR-based vegetation attributes retrievals to detect water-demand and crop types3 hours10.Calibration and Validation of SAR-based Products using the in-situ soil moisture and vegetation data3 hours11.Comparing/fusing the SAR-based retrievals against/with the visible and thermal band vegetation retrievals to enhance the agricultural applications3 hours12.Python GUI introduction and data analysis3 hours13.Accessing free SAR data from NASA DAACs and Public Websites2 hours14.Project Presentation4 hoursTotal Lab Hours49 hoursHours for Project preparation and development24 hoursFieldwork and Extension Activities: Our project team plans to extend the comprehensive cal/val understanding and experience to the UG students. This will include, measurement of soil moisture, biomass, leaf-area-index (LAI), soil roughness, cropping density, etc. Standard measurement devices (such as Theta probes and Plant Canopy Analyzer) will be introduced to the students.Table 3: Field hands-on exercises at MSU Extension farms.1.Use the Delta-T Theta or Hydra Probe to measure top layer (~5 cm) soil moisture from various locations/sites within the field in a regular pattern to capture the field average and variability.2.Collect soil gravimetric sample, topsoil layer (0-5 cm depth) from at least one location in the field, collocating Theta Probe observation site.3.Measure LAI in various locations within the field using a device such as LAI?2200C Plant Canopy Analyzer.4.Collect crop biomass samples in each visit to determine crop vegetation-water-content (VWC).5.One-time measurement of crop planting density, row width, row directions.6.Weekly measurement of surface roughness through IPad Pro device.7.Take pictures during each visit to monitor the progression of crop development.8.Measure GPS locations of all the sites where Theta Probe and Canopy Imager are used, and corners of the field. The geophysical/biophysical samples collected during the three days per week visit will be analyzed and processed in the BAE lab on the remaining two days (Tuesday and Thursday) of the week. Co-PD Dong will take the lead and get the samples processed in the lab to obtain the gravimetric soil moisture values, and VWC from the biomass samples, and maintain the observations taken by the UG trainees in a computer log. These field observations will be used by the trainees for their assignments, in the computing lab activities to cal/val the SAR-based retrievals, understand the SAR backscatter observations, and coursework projects.