World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
42
Citations
7480
World Ranking
7363
National Ranking
4

Overview

Martin Schlerf is affiliated with the Luxembourg Institute of Science and Technology in Luxembourg. Their research primarily focuses on environmental science, with extensive contributions across several interconnected subfields.

The main fields of study for Schlerf include:

  • Environmental Science

Their work spans numerous subfields, such as:

  • Ecology
  • Environmental Engineering
  • Global and Planetary Change
  • Plant Science
  • Atmospheric Science

Schlerf's research topics emphasize aspects related to remote sensing applications in environmental and agricultural contexts. The primary topics covered include:

  • Remote Sensing in Agriculture
  • Plant Water Relations and Carbon Dynamics
  • Urban Heat Island Mitigation
  • Remote Sensing and LiDAR Applications
  • Leaf Properties and Growth Measurement
  • Species Distribution and Climate Change
  • Tree-ring Climate Responses

Their frequent co-authors throughout multiple publications are:

  • Miriam Machwitz
  • Kaniska Mallick
  • Katja Berger
  • Jochem Verrelst
  • Anne J. Hoek van Dijke

Schlerf has published multiple papers in a variety of publication venues, with repeated contributions to:

  • Remote Sensing of Environment
  • International Journal of Applied Earth Observation and Geoinformation
  • Biogeosciences
  • Precision Agriculture
  • Nature Geoscience

Notable recent papers authored or co-authored by Martin Schlerf include:

  • "Shifts in regional water availability due to global tree restoration," 2022, Nature Geoscience
  • "Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review," 2022, Remote Sensing of Environment
  • "Thermal infrared remote sensing of vegetation: Current status and perspectives," 2021, International Journal of Applied Earth Observation and Geoinformation
  • "Examining the link between vegetation leaf area and land-atmosphere exchange of water, energy, and carbon fluxes using FLUXNET data," 2020, Biogeosciences
  • "Comparison of Crop Trait Retrieval Strategies Using UAV-Based VNIR Hyperspectral Imaging," 2021, Remote Sensing

Best Publications

  • Inversion of a radiative transfer model for estimating vegetation LAI and chlorophyll in a heterogeneous grassland

    Roshanak Darvishzadeh;Andrew Skidmore;Martin Schlerf;Clement Atzberger

  • LAI and chlorophyll estimation for a heterogeneous grassland using hyperspectral measurements

    Roshanak Darvishzadeh;Andrew Skidmore;Martin Schlerf;Clement Atzberger

  • Remote sensing of forest biophysical variables using HyMap imaging spectrometer data

    Martin Schlerf;Clement Atzberger;Joachim Hill

  • Shifts in regional water availability due to global tree restoration

    Unknown

  • Inversion of a forest reflectance model to estimate structural canopy variables from hyperspectral remote sensing data

    Martin Schlerf;Clement Atzberger

  • Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review

    Unknown

  • Challenges and Future Perspectives of Multi-/Hyperspectral Thermal Infrared Remote Sensing for Crop Water-Stress Detection: A Review

    Max Gerhards;Martin Schlerf;Kaniska Mallick;Thomas Udelhoven

  • Mapping grassland leaf area index with airborne hyperspectral imagery : a comparison study of statistical approaches and inversion of radiative transfer models

    Roshanak Darvishzadeh;Clement Atzberger;Andrew Skidmore;Martin Schlerf

  • The fourth phase of the radiative transfer model intercomparison (RAMI) exercise: Actual canopy scenarios and conformity testing

    Jean Luc Widlowski;Corrado Mio;Mathias Disney;Jennifer Adams

  • Regional estimation of savanna grass nitrogen using the red-edge band of the spaceborne RapidEye sensor

    Abel Ramoelo;Abel Ramoelo;Andrew K. Skidmore;Moses Azong Cho;Martin Schlerf

  • Retrieval of chlorophyll and nitrogen in Norway spruce (Picea abies L. Karst.) using imaging spectroscopy

    Martin Schlerf;Clement Atzberger;Joachim Hill;Henning Buddenbaum

  • Comparative analysis of different retrieval methods for mapping grassland leaf area index using airborne imaging spectroscopy

    Clement Atzberger;Roshanak Darvishzadeh;Markus Immitzer;Martin Schlerf

  • Classification of coniferous tree species and age classes using hyperspectral data and geostatistical methods

    H. Buddenbaum;M. Schlerf;J. Hill

  • Mapping spatio-temporal variation of grassland quantity and quality using MERIS data and the PROSAIL model

    Yali Si;Yali Si;Martin Schlerf;Raul Zurita-Milla;Andrew Skidmore

  • The fourth radiation transfer model intercomparison (RAMI-IV): Proficiency testing of canopy reflectance models with ISO-13528

    J. L. Widlowski;B. Pinty;M. Lopatka;C. Atzberger

  • Simple and robust methods for remote sensing of canopy chlorophyll content: a comparative analysis of hyperspectral data for different types of vegetation.

    Yoshio Inoue;Martine Guérif;Frédéric Baret;Andrew Skidmore

  • Water stress detection in potato plants using leaf temperature, emissivity, and reflectance

    Max Gerhards;Gilles Rock;Martin Schlerf;Thomas Udelhoven

  • Identifying plant species using mid-wave infrared (2.5–6μm) and thermal infrared (8–14μm) emissivity spectra

    Saleem Ullah;Saleem Ullah;Martin Schlerf;Andrew K. Skidmore;Christoph Hecker

  • Water-removed spectra increase the retrieval accuracy when estimating savanna grass nitrogen and phosphorus concentrations

    Abel Ramoelo;Abel Ramoelo;Andrew K. Skidmore;Martin Schlerf;Renaud Mathieu

  • Non-linear partial least square regression increases the estimation accuracy of grass nitrogen and phosphorus using in situ hyperspectral and environmental data

    Abel Ramoelo;Abel Ramoelo;AK Skidmore;Moses A Cho;Renaud Sa Mathieu

  • Hyperspectral analysis of mangrove foliar chemistry using PLSR and support vector regression

    Christoffer Axelsson;AndrewK. Skidmore;Martin Schlerf;Anas Fauzi

  • Estimation of grassland biomass and nitrogen using MERIS data

    Saleem Ullah;Yali Si;Martin Schlerf;Andrew K. Skidmore

Frequent Co-Authors

Andrew K. Skidmore
Andrew K. Skidmore University of Twente
Clement Atzberger
Clement Atzberger BOKU University
Roshanak Darvishzadeh
Roshanak Darvishzadeh University of Twente
Joachim Hill
Joachim Hill University of Trier
Moses Azong Cho
Moses Azong Cho Council for Scientific and Industrial Research
Renaud Mathieu
Renaud Mathieu International Rice Research Institute
Tiejun Wang
Tiejun Wang University of Twente
Martin Herold
Martin Herold Wageningen University & Research
Ignas M. A. Heitkönig
Ignas M. A. Heitkönig Wageningen University & Research
Lucien Hoffmann
Lucien Hoffmann Luxembourg Institute of Science and Technology

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