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

Popular posts from this blog

Optical Sensors in Remote Sensing

1. What Are Optical Sensors? Optical sensors are remote sensing instruments that detect solar radiation reflected or emitted from the Earth's surface in specific portions of the electromagnetic spectrum (EMS) . They mainly work in: Visible region (0.4–0.7 µm) Near-Infrared – NIR (0.7–1.3 µm) Shortwave Infrared – SWIR (1.3–3.0 µm) Thermal Infrared – TIR (8–14 µm) — emitted energy, not reflected Optical sensors capture spectral signatures of surface features. Each object reflects/absorbs energy differently, creating a unique spectral response pattern . a) Electromagnetic Spectrum (EMS) The continuous range of wavelengths. Optical sensing uses solar reflective bands and sometimes thermal bands . b) Spectral Signature The unique pattern of reflectance or absorbance of an object across wavelengths. Example: Vegetation reflects strongly in NIR Water absorbs strongly in NIR and SWIR (appears dark) c) Radiance and Reflectance Radi...

Radar Sensors in Remote Sensing

Radar sensors are active remote sensing instruments that use microwave radiation to detect and measure Earth's surface features. They transmit their own energy (radio waves) toward the Earth and record the backscattered signal that returns to the sensor. Since they do not depend on sunlight, radar systems can collect data: day or night through clouds, fog, smoke, and rain in all weather conditions This makes radar extremely useful for Earth observation. 1. Active Sensor A radar sensor produces and transmits its own microwaves. This is different from optical and thermal sensors, which depend on sunlight or emitted heat. 2. Microwave Region Radar operates in the microwave region of the electromagnetic spectrum , typically from 1 mm to 1 m wavelength. Common radar frequency bands: P-band (70 cm) L-band (23 cm) S-band (9 cm) C-band (5.6 cm) X-band (3 cm) Each band penetrates and interacts with surfaces differently: Lo...

Thermal Sensors in Remote Sensing

Thermal sensors are remote sensing instruments that detect naturally emitted thermal infrared (TIR) radiation from the Earth's surface. Unlike optical sensors (which detect reflected sunlight), thermal sensors measure heat energy emitted by objects because of their temperature. They work mainly in the Thermal Infrared region (8–14 µm) of the electromagnetic spectrum. 1. Thermal Infrared Radiation All objects above 0 Kelvin (absolute zero) emit electromagnetic radiation. This is explained by Planck's Radiation Law . For Earth's surface temperature range (about 250–330 K), the peak emitted radiation occurs in the 8–14 µm thermal window . Thus, thermal sensors detect emitted energy , not reflected sunlight. 2. Emissivity Emissivity is the efficiency with which a material emits thermal radiation. Values range from 0 to 1 : Water, vegetation → high emissivity (0.95–0.99) Bare soil → medium (0.85–0.95) Metals → low (0.1–0.3) E...

Geometric Correction

When satellite or aerial images are captured, they often contain distortions (errors in shape, scale, or position) caused by many factors — like Earth's curvature, satellite motion, terrain height (relief), or the Earth's rotation . These distortions make the image not properly aligned with real-world coordinates (latitude and longitude). 👉 Geometric correction is the process of removing these distortions so that every pixel in the image correctly represents its location on the Earth's surface. After geometric correction, the image becomes geographically referenced and can be used with maps and GIS data. Types  1. Systematic Correction Systematic errors are predictable and can be modeled mathematically. They occur due to the geometry and movement of the satellite sensor or the Earth. Common systematic distortions: Scan skew – due to the motion of the sensor as it scans the Earth. Mirror velocity variation – scanning mirror moves at a va...

LiDAR in Remote Sensing

LiDAR (Light Detection and Ranging) is an active remote sensing technology that uses laser pulses to measure distances to the Earth's surface and create high-resolution 3D maps . LiDAR sensors emit short pulses of laser light (usually in the near-infrared range) and measure the time it takes for the pulse to return after hitting an object. Because LiDAR measures distance very precisely, it is excellent for mapping: terrain vegetation height buildings forests coastlines flood plains ✅ 1. Active Sensor LiDAR sends its own laser energy, unlike passive sensors that rely on sunlight. ✅ 2. Laser Pulse LiDAR emits thousands of pulses per second (even millions). Wavelengths commonly used: Near-Infrared (NIR) → land and vegetation mapping Green (532 nm) → water/ bathymetry (penetrates shallow water) ✅ 3. Time of Flight (TOF) The sensor measures the time taken for the laser to travel: from the sensor → to the sur...