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

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...

Logical Data Model in GIS

In GIS, a logical data model defines how data is structured and interrelated—independent of how it is physically stored or implemented. It serves as a blueprint for designing databases, focusing on the organization of entities, their attributes, and relationships, without tying them to a specific database technology. Key Features Abstraction : The logical model operates at an abstract level, emphasizing the conceptual structure of data rather than the technical details of storage or implementation. Entity-Attribute Relationships : It identifies key entities (objects or concepts) and their attributes (properties), as well as the logical relationships between them. Business Rules : Business logic is embedded in the model to enforce rules, constraints, and conditions that ensure data consistency and accuracy. Technology Independence : The logical model is platform-agnostic—it is not tied to any specific database system or storage format. Visual Representat...

Approaches of Surface Water Management: Watershed-Based Approaches

Surface water management refers to the strategies used to regulate and optimize the availability, distribution, and quality of surface water resources such as rivers, lakes, and reservoirs. One of the most effective strategies is the watershed-based approach , which considers the entire watershed or drainage basin as a unit for water resource management, ensuring sustainability and minimizing conflicts between upstream and downstream users. 1. Watershed-Based Approaches Watershed A watershed (or drainage basin) is a geographical area where all precipitation and surface runoff flow into a common outlet such as a river, lake, or ocean. Example : The Ganga River Basin is a watershed that drains into the Bay of Bengal. Hydrological Cycle and Watershed Management Watershed-based approaches work by managing the hydrological cycle , which involves precipitation, infiltration, runoff, evapotranspiration, and groundwater recharge. Precipitation : Rainfall or snowfall within a...

Raster Data Structure

Raster Data Raster data is like a digital photo made up of small squares called cells or pixels . Each cell shows something about that spot — like how high it is (elevation), how hot it is (temperature), or what kind of land it is (forest, water, etc.). Think of it like a graph paper where each box is colored to show what's there. Key Points What's in the cell? Each cell stores information — for example, "water" or "forest." Where is the cell? The cell's location comes from its place in the grid (like row 3, column 5). We don't need to store its exact coordinates. How Do We Decide a Cell's Value? Sometimes, one cell covers more than one thing (like part forest and part water). To choose one value , we can: Center Point: Use whatever feature is in the middle. Most Area: Use the feature that takes up the most space in the cell. Most Important: Use the most important feature (like a road or well), even if it...

Disaster Management international framework

The international landscape for disaster management relies on frameworks that emphasize reducing risk, improving preparedness, and fostering resilience to protect lives, economies, and ecosystems from the impacts of natural and human-made hazards. Here's a more detailed examination of key international frameworks, with a focus on terminologies, facts, and concepts, as well as the role of the United Nations Office for Disaster Risk Reduction (UNDRR): 1. Sendai Framework for Disaster Risk Reduction 2015-2030 Adopted at the Third UN World Conference on Disaster Risk Reduction in Sendai, Japan, and endorsed by the UN General Assembly in 2015, the Sendai Framework represents a paradigm shift from disaster response to proactive disaster risk management. It applies across natural, technological, and biological hazards. Core Priorities: Understanding Disaster Risk: This includes awareness of disaster risk factors and strengthening risk assessments based on geographic, social, and econo...

Vineesh V, Geography

Search This Blog