Postdoc in remote sensing and ecosystem modelling Swiss Federal Institute for Forest, Snow and Landscape Research

Swiss Federal Institute for Forest, Snow and Landscape Research WSL

The Swiss Federal Institute for Forest, Snow and Landscape Research WSL is part of the ETH Domain. Approximately 600 people work on the sustainable use and protection of the environment and on the handling of natural hazards.

The Research Unit Forest Dynamics assesses the effects of changing environmental conditions on forest ecosystem functioning. We are offering for 7 months a position as

Postdoc in remote sensing and ecosystem modelling

You will investigate ecosystem photosynthesis and impacts of extreme cold temperature events in the early season. The challenge is to identify causes, understand mechanisms, and to quantify effects at the continental scale. To achieve this, you will work with ecosystem eddy covariance flux measurements from a large number of sites, develop model parametrisations to resolve apparent model bias, and investigate links between flux measurements and multispectral remote sensing data. You will be part of a diverse group with complimentary expertise, relevant for this project and with a strong collaborative philosophy. You will benefit from a world-leading academic environment at WSL and ETH Zürich (through co-supervision) and the excellent quality of life in Switzerland. The funding for this project is seven months and opens the door for upcoming opportunities within the groups of project collaborators at WSL and ETH Zürich. Your working place will be at WSL in Birmensdorf (approx. 20 min outside of Zurich). For further information about the project please visit the website https://stineb.github.io/project/photocold/

You hold a PhD in ecology or environmental sciences with a particular focus in remote sensing or environmental modelling. This position requires independent and creative thinking to formulate hypotheses; familiarity with plant ecophysiology, remote sensing and eddy covariance data; a robust skill set for methods in environmental data science (analysis of large datasets and mechanistic ecosystem modelling modelling); and the curiosity and intrinsic motivation to address an important research challenge for a better understanding of global environmental change and climate impacts.

Please send your complete application to Stefania Pe, Human Resources WSL, by uploading the requested documents through our webpage. Applications via email will not be considered. Questions regarding the position can be directed by email or phone to project collaborators Prof. A. Gessler (arthur.gessler@wsl.ch, +41 44 739 28 18), Prof. B. Stocker (bestocke@ethz.ch, +41 44 632 48 90), Dr. Petra D'Odorico (petra.dodorico@wsl.ch, +41 44 739 20 46), or Dr. Christian Ginzler (christian.ginzler@wsl.ch, +41 44 739 25 51). The WSL strives to increase the proportion of women in its employment, which is why qualified women are particularly called upon to apply for this position.

Apply now

Apply with xeebo

Zürcherstrasse 111, CH-8903 Birmensdorf

Company-Video

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

Comments

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 ...

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...

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...

Resolution of Sensors in Remote Sensing

Spatial Resolution 🗺️ Definition : The smallest size of an object on the ground that a sensor can detect. Measured as : The size of a pixel on the ground (in meters). Example : Landsat → 30 m (each pixel = 30 × 30 m on Earth). WorldView-3 → 0.31 m (very detailed, you can see cars). Fact : Higher spatial resolution = finer details, but smaller coverage. Spectral Resolution 🌈 Definition : The ability of a sensor to capture information in different parts (bands) of the electromagnetic spectrum . Measured as : The number and width of spectral bands. Types : Panchromatic (1 broad band, e.g., black & white image). Multispectral (several broad bands, e.g., Landsat with 7–13 bands). Hyperspectral (hundreds of very narrow bands, e.g., AVIRIS). Fact : Higher spectral resolution = better identification of materials (e.g., minerals, vegetation types). Radiometric Resolution 📊 Definition : The ability of a sensor to ...

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...

Vineesh V, Geography

Search This Blog