Skip to main content

Scientist in optical remote sensing of vegetation Forschungszentrum Jülich





Scientist in optical remote sensing of vegetation Forschungszentrum Jülich

The Plant Sciences Subinstitute of the Institute of Bio- and Geosciences (IBG) investigates the dynamics of plant processes and the interaction of plants with the environment. Plant science at Forschungszentrum Jülich plays a leading role at national and international level in the field of plant phenotyping, i.e. in the quantitative and non-invasive recording of structural and functional properties of plants important for agricultural and horticultural plant breeding. In this context, we are developing new sensors and measurement concepts and integrate them into semi- and fully automated systems. One focus of the subinstitute is the use of optical sensors to promote the automated measurement of plant traits under field conditions. Ground-based measurements are complemented by UAV, aircraft and satellite-based remote sensing approaches. Particular focus is on the development of novel non-invasive measurement approaches that include, multi- and hyperspectral imaging as well as different fluorescence retrieval techniques.
We are looking to recruit a
Scientist in optical remote sensing of vegetation
Your Job:
Focus of the research will be on exploiting hyper- and multispectral UAV data from cassava and other crops to derive structural and functional plant properties
Contribution to flight and campaign planning using rotary and fixed-wing unmanned platforms (UAVs) in Nigeria, Taiwan and Germany
Integration of multi- and hyperspectral sensors into existing UAV platforms
Measuring canopy traits in cassava plants in a project collaboration funded by the Bill and Melinda Gates Foundation
Development and refinement of algorithms for the preprocessing, atmospheric correction and georectification of spectrally resolved UAV data
Registration of optical reflectance data with experimental plot set-ups using GIS layers
Retrieval of canopy height models using custom based codes for data processing
Calculation of classical vegetation traits by exploiting the information content of the optical sensors
Radiative transfer inversion of leaf and canopy models to derive structural and functional vegetation traits from the combination of UAV based imaging data and other information sources, such as meteorological and ground based data
Interpretation of the results, correlation of remote sensing data with ground based plant traits and the integration within different synergistic projects
Presentation of the results at scientific conferences and within project reports
Writing of scientific papers in this field by taking advantage of the large body of research data that are available in the group
Contribution to project proposals in this research field
Contribution to supervision of Bachelor, Master and PhD students
Your Profile:
A university degree in Remote Sensing, Geophysics, Plant Biology, Agriculture or a natural scientific discipline with relevant and proven experience in the field of activity
Sound background in the use of UAVs and other unmanned aerial vehicles in research and agricultural practice
Experience in the processing of UAV image data using Agisoft Metashape or Pix4D
Sound background and proven expertise in processing and analyzing multispectral data
Profound knowledge in the field of atmospheric and geometric correction methods applied to ground-based, airborne and satellite data
Wide experience in interpretation and retrieval of vegetation traits from multispectral imagery
Special interest in retrieving and interpreting spectrally resolved UAV data from agricultural settings
Experience with programming languages and software that are used for multi-/hyperspectral image processing, e.g. ENVI/IDL, Python, R, Matlab etc.
Willingness and interest to work in Developing Countries
Ability to work in the field, partly also in remote locations outside of Germany, in specific in Nigeria and Taiwain
Driver license obligatory, already existing licenses to operate UAV platforms are a benefit
Our Offer:
Exciting working environment on an attractive research campus with excellent infrastructure, located between the cities of Cologne, Düsseldorf, and Aachen
Possibility to develop own scientific profile in the emerging topic of ‚remote sensing of vegetation traits using unmanned aerial vehicles'
Integration in a world-leading research group in this field with a stimulating scientific environment
Attendance of national and international conferences and workshops
Possibility for further scientific and technical training through international experts
Flexible working hours and various opportunities to reconcile work and private life
Position initially limited to three years, with the possibility of a longer-term perspective
The position can also be filled as a part-time position; flexible working time models between 50-100% are possible
Salary and social benefits in conformity with the provisions of the Collective Agreement for the Civil Service (TVöD)
Forschungszentrum Jülich promotes equal opportunities and diversity in its employment relations.
We also welcome applications from disabled persons.





Vineesh V
Assistant Professor of Geography,
Directorate of Education,
Government of Kerala.
https://g.page/vineeshvc
🌏🌎
🌐🌍

Comments

Post a Comment

Popular posts from this blog

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 ...
Post a Comment
Read more

Model GIS object attribute entity

These concepts explain different ways of organizing, storing, and representing geographic information in a Geographic Information System (GIS) . They include database design models (ER model), data structure models (Object and Attribute models), and spatio-temporal representations that integrate location, entities, and time . Together, they help GIS manage both spatial data (where things are) and descriptive information (what they are and how they change over time) . 1. Object-Based Model (Object-Oriented Data Model) The Object-Based Model treats geographic features as independent objects that combine spatial geometry and descriptive attributes within a single structure. Core Concept: Each geographic feature (such as a building, road, or river ) is represented as a self-contained object that stores both: Geometry – location and shape (point, line, polygon) Attributes – descriptive properties (name, type, length, capacity) Unlike older georelational models , which stored spatial ...
Post a Comment
Read more

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...
Post a Comment
Read more

Spatial data and Attribute data

Spatial Data Definition: Spatial data represents the geometric location of features on the Earth's surface. It defines the shape, size, and position of geographic entities. Key Concepts and Terminologies: Geometric Representation: Point Data: Represents a single location (e.g., a city center, weather station). Line Data: Represents linear features (e.g., roads, rivers). Polygon Data: Represents area-based features (e.g., administrative boundaries, lakes). Coordinate Systems & Projections: Geographic Coordinate System (GCS): Uses latitude and longitude (e.g., WGS 84). Projected Coordinate System (PCS): Converts curved surface data to a flat map (e.g., UTM, Mercator). Data Formats: Vector Data: Stores discrete features (points, lines, polygons). Raster Data: Stores continuous data in grid format (e.g., satellite imagery, elevation models). Examples of Spatial Data: A vector dataset of roads with line geometries stored in Shapefile (.shp) f...
Post a Comment
Read more

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...
Post a Comment
Read more