GRADUATE RESEARCH ASSISTANTSHIP IN SPATIAL VARIABILITY – CROP YIELD RELATIONSHIPS

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

KSHEC Scholarship 2024-25

KSHEC Scholarship 2024-25 Alert! First-Year UG Students Only, Don't Miss This Golden Opportunity! 💡✨ Are you a first-year undergraduate student studying in a Government or Aided College in Kerala? Do you need financial assistance to continue your education without stress? The Kerala State Higher Education Council (KSHEC) Scholarship is here to support YOU! This scholarship is a lifeline for deserving students, helping them focus on their studies without worrying about financial burdens. If you meet the criteria, APPLY NOW and take a step towards a brighter future! 🌟 ✅ Simple Online Application – Quick & easy process! 📌 Who Can Apply? ✔️ First-year UG students ONLY ✔️ Must be studying in an Arts & Science Government or Aided college in Kerala ✔️ Professional Course students are not eligible 🔹 Scholarship Amounts Per Year: 📌 1st Year FYUGP – ₹12,000 📌 2nd Year FYUGP – ₹18,000 📌 3rd Year FYUGP – ₹24,000 📌 4th Year FYUGP – ₹40,000 📌 5th Year PG – ₹60,000 Great News...

Disaster Management

1. Disaster Risk Analysis → Disaster Risk Reduction → Disaster Management Cycle Disaster Risk Analysis is the first step in managing disasters. It involves assessing potential hazards, identifying vulnerable populations, and estimating possible impacts. Once risks are identified, Disaster Risk Reduction (DRR) strategies come into play. DRR aims to reduce risk and enhance resilience through planning, infrastructure development, and policy enforcement. The Disaster Management Cycle then ensures a structured approach by dividing actions into pre-disaster, during-disaster, and post-disaster phases . Example Connection: Imagine a coastal city prone to cyclones: Risk Analysis identifies low-lying areas and weak infrastructure. Risk Reduction includes building seawalls, enforcing strict building codes, and training residents for emergency situations. The Disaster Management Cycle ensures ongoing preparedness, immediate response during a cyclone, and long-term recovery afterw...

Pre During and Post Disaster

Disaster management is a structured approach aimed at reducing risks, responding effectively, and ensuring a swift recovery from disasters. It consists of three main phases: Pre-Disaster (Mitigation & Preparedness), During Disaster (Response), and Post-Disaster (Recovery). These phases involve various strategies, policies, and actions to protect lives, property, and the environment. Below is a breakdown of each phase with key concepts, terminologies, and examples. 1. Pre-Disaster Phase (Mitigation and Preparedness) Mitigation: This phase focuses on reducing the severity of a disaster by minimizing risks and vulnerabilities. It involves structural and non-structural measures. Hazard Identification: Recognizing potential natural and human-made hazards (e.g., earthquakes, floods, industrial accidents). Risk Assessment: Evaluating the probability and consequences of disasters using GIS, remote sensing, and historical data. Vulnerability Analysis: Identifying areas and p...

Mapping Process

The mapping process involves several systematic steps to transform real-world spatial information into a readable, accurate, and useful representation. Below is a structured explanation of each step in the mapping process, with key concepts, terminologies, and examples. 1. Defining the Purpose of the Map Before creating a map, it is essential to determine its purpose and audience . Different maps serve different objectives, such as navigation, analysis, or communication. Types of Maps Based on Purpose: Thematic Maps: Focus on specific subjects (e.g., climate maps, population density maps). Topographic Maps: Show natural and human-made features (e.g., contour maps, landform maps). Tourist Maps: Highlight attractions, roads, and landmarks for travelers. Cadastral Maps: Used in land ownership and property boundaries. Navigational Maps: Used in GPS systems for wayfinding. Example: A disaster risk map for floods will highlight flood-prone areas, emergency shelters, and ...

GIS Concepts

S patial Data Components Location or Position This defines where a spatial object exists on the Earth's surface. It is represented using coordinate systems , such as: Geographic Coordinate System (GCS) – Uses latitude and longitude (e.g., WGS84). Projected Coordinate System (PCS) – Converts Earth's curved surface into a flat map using projections (e.g., UTM, Mercator). Example: The Eiffel Tower is located at 48.8584° N, 2.2945° E in the WGS84 coordinate system. Attribute Data (Descriptive Information About Location) Describes characteristics of spatial features and is stored in attribute tables . Types of attribute data: Nominal Data – Categories without a numerical value (e.g., land use type: residential, commercial). Ordinal Data – Ranked categories (e.g., soil quality: poor, moderate, good). Interval Data – Numeric values without a true zero (e.g., temperature in °C). Ratio Data – Numeric values with a true zero (e.g., population count, rainfall amoun...

Vineesh V, Geography

Search This Blog