Skip to main content

Graduate Research Associate Positions: Remote Sensing and Data Analytics for Sustainable Agriculture The Ohio State University






Graduate Research Associate Positions: Remote Sensing and Data Analytics for Sustainable Agriculture The Ohio State University

The AgSensing Lab (ASL) in the Department of Food, Agricultural and Biological Engineering at the Ohio State University is recruiting 1 M.S. and 1 PhD students starting in Spring or Fall of 2021 to work in the areas of remote sensing and data analytics for sustainable agriculture.

The ASL focuses on understanding the implications of agricultural practices on ecosystem services (such as crop and soil health) at both field and landscape scales, using remote sensing (i.e., satellite and drone) technologies, ecosystem models and machine learning methods. Some of the current research projects include (1) crop yield assessment at a field scale; (2) mapping of cover crops and the impact on water quality and greenhouse gas emissions, (3) application of drone technologies for precision agriculture, and (4) satellite based monitoring of water quality. ASL also closely collaborates with other research groups, such as ReRout Lab, Lab for Environmental Modeling and Spatial Analysis, BSAL, and Digital Ag at the Ohio State University.

Selected graduate students will work on projects that involve interdisciplinary team of researchers from various disciplines, such as agricultural engineering, computer science and electrical engineering, horticulture and crop science, and entomology. The students will also have an opportunity to work with farmers, crop consultants, and precision agriculture industries. Graduate students are expected to publish research findings in international peer-reviewed journals, present research findings in conferences/meetings, and generate regular project update reports.

The ideal candidates should have the following qualifications and experiences:

· BS or MS degree in agricultural, mechanical, civil, or electrical engineering; environmental science; computer science; or other related disciplines.
· Demonstrated statistical and computer-programming (Python, R, OpenCV, MATLAB, Java, C++, etc.) skills.
· Experience in remote sensing, GIS, ecosystem modeling, precision agriculture technologies.
· Ability to learn/adopt skills and knowledge in solving "real-world" problems.
· Creative and independent research abilities with teamwork spirit.
· Strong oral and written communications skills.

Salary and Benefits: Starting salary/stipend will be competitive. The position will include full benefits as per OSU guidelines, including tuition and health care benefits.

Anticipated Starting Term: Spring 2020 (Open until filled). Applications will be reviewed as received.

No. of Positions: 2

How to Apply: Please email the following materials to Dr. Sami Khanal (khanal.3@osu.edu):

· Cover letter outlining (a) research experience, ideas and interest, (b) motivations to pursue a PhD, (c) and long-term career goals
· Detailed CV
· Academic transcripts (Unofficial copy at this point)
· Unofficial GRE and TOEFL (only for international students) test scores
· List of three references (name, position, institution, email address, and phone number).






Vineesh V
Assistant Professor of Geography,
Directorate of Education,
Government of Kerala.
https://www.facebook.com/Applied.Geography
http://geogisgeo.blogspot.com

Comments

Popular posts from this blog

Atmospheric Window

The atmospheric window in remote sensing refers to specific wavelength ranges within the electromagnetic spectrum that can pass through the Earth's atmosphere relatively unimpeded. These windows are crucial for remote sensing applications because they allow us to observe the Earth's surface and atmosphere without significant interference from the atmosphere's constituents. Key facts and concepts about atmospheric windows: Visible and Near-Infrared (VNIR) window: This window encompasses wavelengths from approximately 0. 4 to 1. 0 micrometers. It is ideal for observing vegetation, water bodies, and land cover types. Shortwave Infrared (SWIR) window: This window covers wavelengths from approximately 1. 0 to 3. 0 micrometers. It is particularly useful for detecting minerals, water content, and vegetation health. Mid-Infrared (MIR) window: This window spans wavelengths from approximately 3. 0 to 8. 0 micrometers. It is valuable for identifying various materials, incl...

Platforms in Remote Sensing

In remote sensing, a platform is the physical structure or vehicle that carries a sensor (camera, scanner, radar, etc.) to observe and collect information about the Earth's surface. Platforms are classified mainly by their altitude and mobility : Ground-Based Platforms Definition : Sensors mounted on the Earth's surface or very close to it. Examples : Tripods, towers, ground vehicles, handheld instruments. Applications : Calibration and validation of satellite data Detailed local studies (e.g., soil properties, vegetation health, air quality) Strength : High spatial detail but limited coverage. Airborne Platforms Definition : Sensors carried by aircraft, balloons, or drones (UAVs). Altitude : A few hundred meters to ~20 km. Examples : Airplanes with multispectral scanners UAVs with high-resolution cameras or LiDAR High-altitude balloons (stratospheric platforms) Applications : Local-to-regional mapping ...

History of GIS

1. 1832 - Early Spatial Analysis in Epidemiology:    - Charles Picquet creates a map in Paris detailing cholera deaths per 1,000 inhabitants.    - Utilizes halftone color gradients for visual representation. 2. 1854 - John Snow's Cholera Outbreak Analysis:    - Epidemiologist John Snow identifies cholera outbreak source in London using spatial analysis.    - Maps casualties' residences and nearby water sources to pinpoint the outbreak's origin. 3. Early 20th Century - Photozincography and Layered Mapping:    - Photozincography development allows maps to be split into layers for vegetation, water, etc.    - Introduction of layers, later a key feature in GIS, for separate printing plates. 4. Mid-20th Century - Computer Facilitation of Cartography:    - Waldo Tobler's 1959 publication details using computers for cartography.    - Computer hardware development, driven by nuclear weapon research, leads to broader mapping applications by early 1960s. 5. 1960 - Canada Geograph...

Scattering

Scattering 

History of GIS

The history of Geographic Information Systems (GIS) is rooted in early efforts to understand spatial relationships and patterns, long before the advent of digital computers. While modern GIS emerged in the mid-20th century with advances in computing, its conceptual foundations lie in cartography, spatial analysis, and thematic mapping. Early Roots of Spatial Analysis (Pre-1960s) One of the earliest documented applications of spatial analysis dates back to  1832 , when  Charles Picquet , a French geographer and cartographer, produced a cholera mortality map of Paris. In his report  Rapport sur la marche et les effets du cholĂ©ra dans Paris et le dĂ©partement de la Seine , Picquet used graduated color shading to represent cholera deaths per 1,000 inhabitants across 48 districts. This work is widely regarded as an early example of choropleth mapping and thematic cartography applied to epidemiology. A landmark moment in the history of spatial analysis occurred in  1854 , when  John Snow  inv...