Skip to main content

GRADUATE RESEARCH ASSISTANTSHIP IN SPATIAL VARIABILITY – CROP YIELD RELATIONSHIPS - University of Nebraska-Lincoln

GRADUATE RESEARCH ASSISTANTSHIP IN SPATIAL VARIABILITY – CROP YIELD RELATIONSHIPS - University of Nebraska-Lincoln

The University of Nebraska-Lincoln (UNL) invites applications for an MS or PhD graduate research assistantship. The candidate in this assistantship will support work to improve an understanding of spatial variability underlying crop yields and associated producer profitability. Specifically the student will investigate the relationship of the National Commodity Crop Productivity Index (NCCPI), an index in the SSURGO database, to crop yields in Nebraska. These efforts will provide a research-based assessment of the ability of the NCCPI to predict crop  yields in Nebraska. The selected candidate will join a collaborative research team involving faculty in Spatial Sciences (Dr. Yi Qi; https://www.qispatial.com/), Cropping Systems (Dr. Andrea Basche; https://agronomy.unl.edu/basche-research), and Applied Wildlife Ecology (Dr. Andrew Little; https://wildlifeecologylab.unl.edu/).

Responsibilities for the student will include:
·                      Data collection, organization, and analysis of relevant field-scale yield data
·                      Evaluate the spatial relationship of crop yields to the National Commodity Crop Productivity Index (NCCPI)
·                      Conduct spatial analysis and quantitative data analysis to identify hotspots of marginal or less productive regions and mapping their relationship to the NCCPI
·                      Develop map products to allow for visualization and interpretation of results

Qualifications: Applicants must have completed a minimum of a Bachelor of Science degree in a field related Geographical Information Systems, Remote Sensing, and Data Analytics. Applicants should have a GPA ≥3.0. Applicants also should have strong quantitative skills (e.g., correlation analysis, regression analysis) and organizational skills, attention to detail, and excellent oral and written communication skills. Preference will be given to applicants with prior experience or training with GIS (e.g., Esri ArcGIS develop and ArcGIS online), Remote Sensing (e.g., ENVI) or similar software.

GRA Stipend: Starting salary $22,000 for M.S. or $24,000 for Ph.D.
Tuition Waiver: A tuition waiver of up to 12 credit hours per semester and 6-12 credit hours during summer sessions (depending on previous enrollment) is provided with the GRA.
Health Insurance: Students on assistantships are provided health insurance at a reduced rate. 
GRA Availability: Summer or Fall 2020

Application: To be considered for this position, please send a cover letter outlining your interests, research background, and career aspirations as they pertain to this position; a resume or curriculum vitae; copies of transcripts (unofficial); unofficial copies of GRE scores; and contact information for 3 professional references (name, email, phone, address) combined in a single PDF file with the file name formatted as lastname_firstname to Dr. Yi Qi (yi.qi@unl.edu). Review of applications will begin immediately and the position will remain open until filled.

Comments

Popular posts from this blog

Types of Remote Sensing

Remote Sensing means collecting information about the Earth's surface without touching it , usually using satellites, aircraft, or drones . There are different types of remote sensing based on the energy source and the wavelength region used. 🛰️ 1. Active Remote Sensing 📘 Concept: In active remote sensing , the sensor sends out its own energy (like a signal or pulse) to the Earth's surface. The sensor then records the reflected or backscattered energy that comes back from the surface. ⚙️ Key Terminology: Transmitter: sends energy (like a radar pulse or laser beam). Receiver: detects the energy that bounces back. Backscatter: energy that is reflected back to the sensor. 📊 Examples of Active Sensors: RADAR (Radio Detection and Ranging): Uses microwave signals to detect surface roughness, soil moisture, or ocean waves. LiDAR (Light Detection and Ranging): Uses laser light (near-infrared) to measure elevation, vegetation...

geostationary and sun-synchronous

Orbital characteristics of Remote sensing satellite geostationary and sun-synchronous  Orbits in Remote Sensing Orbit = the path a satellite follows around the Earth. The orbit determines what part of Earth the satellite can see , how often it revisits , and what applications it is good for . Remote sensing satellites mainly use two standard orbits : Geostationary Orbit (GEO) Sun-Synchronous Orbit (SSO)  Geostationary Satellites (GEO) Characteristics Altitude : ~35,786 km above the equator. Period : 24 hours → same as Earth's rotation. Orbit type : Circular, directly above the equator . Appears "stationary" over one fixed point on Earth. Concepts & Terminologies Geosynchronous = orbit period matches Earth's rotation (24h). Geostationary = special type of geosynchronous orbit directly above equator → looks fixed. Continuous coverage : Can monitor the same area all the time. Applications Weather...

India remote sensing

1. Foundational Phase (Early 1970s – Early 1980s) Objective: To explore the potential of space-based observation for national development. 1972: The Space Applications Programme (SAP) was initiated by the Indian Space Research Organisation (ISRO), focusing on applying space technology for societal benefits. 1975: The Department of Space (DoS) was established, providing an institutional base for space applications, including remote sensing. 1977: India began aerial and balloon-borne experiments to study Earth resources and assess how remote sensing data could aid in agriculture, forestry, and hydrology. 1978 (June 7): Bhaskara-I launched by the Soviet Union — India's first experimental Earth Observation satellite . Payloads: TV cameras (for land and ocean surface observation) and a Microwave Radiometer. Significance: Proved that satellite-based Earth observation was feasible for India's needs. 1981 (November 20): Bhaskara-II launche...

Natural Disasters

A natural disaster is a catastrophic event caused by natural processes of the Earth that results in significant loss of life, property, and environmental resources. It occurs when a hazard (potentially damaging physical event) interacts with a vulnerable population and leads to disruption of normal life . Key terms: Hazard → A potential natural event (e.g., cyclone, earthquake). Disaster → When the hazard causes widespread damage due to vulnerability. Risk → Probability of harmful consequences from interaction of hazard and vulnerability. Vulnerability → Degree to which a community or system is exposed and unable to cope with the hazard. Resilience → Ability of a system or society to recover from the disaster impact. 👉 Example: An earthquake in an uninhabited desert is a hazard , but not a disaster unless people or infrastructure are affected. Types Natural disasters can be classified into geophysical, hydrological, meteorological, clim...

Man-Made Disasters

  A man-made disaster (also called a technological disaster or anthropogenic disaster ) is a catastrophic event caused directly or indirectly by human actions , rather than natural processes. These disasters arise due to negligence, error, industrial activity, conflict, or misuse of technology , and often result in loss of life, property damage, and environmental degradation . Terminology: Anthropogenic = originating from human activity. Technological hazard = hazard caused by failure or misuse of technology or industry. 🔹 Conceptual Understanding Man-made disasters are part of the Disaster Management Cycle , which includes: Prevention – avoiding unsafe practices. Mitigation – reducing disaster impact (e.g., safety regulations). Preparedness – training and planning. Response – emergency actions after the disaster. Recovery – long-term rebuilding and policy correction. These disasters are predictable and preventable through strong...