Jan G. P. W. Clevers

Orcid: 0000-0002-0046-082X

Affiliations:
  • Wageningen University, Centre for Geo-Information, Netherlands


According to our database1, Jan G. P. W. Clevers authored at least 38 papers between 2007 and 2021.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
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PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2021
Assessing a Prototype Database for Comprehensive Global Aquatic Land Cover Mapping.
Remote. Sens., 2021

Diurnal variation of sun-induced chlorophyll fluorescence of agricultural crops observed from a point-based spectrometer on a UAV.
Int. J. Appl. Earth Obs. Geoinformation, 2021

2020
Assessment of Workflow Feature Selection on Forest LAI Prediction with Sentinel-2A MSI, Landsat 7 ETM+ and Landsat 8 OLI.
Remote. Sens., 2020

2018
Forest Cover and Vegetation Degradation Detection in the Kavango Zambezi Transfrontier Conservation Area Using BFAST Monitor.
Remote. Sens., 2018

Monitoring Forest Phenology and Leaf Area Index with the Autonomous, Low-Cost Transmittance Sensor PASTiS-57.
Remote. Sens., 2018

Improved estimation of leaf area index and leaf chlorophyll content of a potato crop using multi-angle spectral data - potential of unmanned aerial vehicle imagery.
Int. J. Appl. Earth Obs. Geoinformation, 2018

Hyperspectral Remote Sensing: Fundamentals and Practices, Ruiliang Pu, CRC Press, Boca Raton (2017). 466pp., Price: Hardback £ 155, Paperback £ 75. ISBN: 978-1-4987-3159-1 (Hardback), 978-1-1387-4717-3 (Paperback).
Int. J. Appl. Earth Obs. Geoinformation, 2018

Spatial Enhancement of Modis Leaf Area Index Using Regression Analysis with Landsat Vegetation Index.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017
Mapping Reflectance Anisotropy of a Potato Canopy Using Aerial Images Acquired with an Unmanned Aerial Vehicle.
Remote. Sens., 2017

Using Sentinel-2 Data for Retrieving LAI and Leaf and Canopy Chlorophyll Content of a Potato Crop.
Remote. Sens., 2017

2016
Hyperspectral Reflectance Anisotropy Measurements Using a Pushbroom Spectrometer on an Unmanned Aerial Vehicle - Results for Barley, Winter Wheat, and Potato.
Remote. Sens., 2016

Performance of vegetation indices from Landsat time series in deforestation monitoring.
Int. J. Appl. Earth Obs. Geoinformation, 2016

Fundamentals of Satellite Remote Sensing: An Environmental Approach, second edition, Emilio Chuvieco. CRC Press, Boca Raton (2016).
Int. J. Appl. Earth Obs. Geoinformation, 2016

2015
Estimation of Spruce Needle-Leaf Chlorophyll Content Based on DART and PARAS Canopy Reflectance Models.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2015

Microwave Radar and Radiometric Remote Sensing, F.T. Ulaby, D.G. Long. University of Michigan Press, Ann Arbor (2014).
Int. J. Appl. Earth Obs. Geoinformation, 2015

2014
Minimizing Measurement Uncertainties of Coniferous Needle-Leaf Optical Properties, Part I: Methodological Review.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014

Minimizing Measurement Uncertainties of Coniferous Needle-Leaf Optical Properties. Part II: Experimental Setup and Error Analysis.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014

2013
Assessing Water Stress of Desert Tamarugo Trees Using<i> in situ</i> Data and Very High Spatial Resolution Remote Sensing.
Remote. Sens., 2013

Estimating salinity stress in sugarcane fields with spaceborne hyperspectral vegetation indices.
Int. J. Appl. Earth Obs. Geoinformation, 2013

Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3.
Int. J. Appl. Earth Obs. Geoinformation, 2013

Modelling the spectral response of the desert tree Prosopis tamarugo to water stress.
Int. J. Appl. Earth Obs. Geoinformation, 2013

2012
Using Hyperspectral Remote Sensing Data for Retrieving Canopy Chlorophyll and Nitrogen Content.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2012

A Laboratory Goniometer System for Measuring Reflectance and Emittance Anisotropy.
Sensors, 2012

Mapping LAI and chlorophyll content from at-sensor APEX data using a Bayesian optimisation of a coupled canopy-atmosphere model.
Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012

2011
Multitemporal Unmixing of Medium-Spatial-Resolution Satellite Images: A Case Study Using MERIS Images for Land-Cover Mapping.
IEEE Trans. Geosci. Remote. Sens., 2011

A Dutch multi-date land use database: Identification of real and methodological changes.
Int. J. Appl. Earth Obs. Geoinformation, 2011

Using hyperspectral remote sensing data for retrieving total canopy chlorophyll and nitrogen content.
Proceedings of the 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2011

2010
Merging the Minnaert- k Parameter With Spectral Unmixing to Map Forest Heterogeneity With CHRIS/PROBA Data.
IEEE Trans. Geosci. Remote. Sens., 2010

Estimating canopy water content using hyperspectral remote sensing data.
Int. J. Appl. Earth Obs. Geoinformation, 2010

2009
Mapping of aggregated floodplain plant communities using image fusion of CASI and LiDAR data.
Int. J. Appl. Earth Obs. Geoinformation, 2009

Russell G. Congalton, Kass Green, Assessing the Accuracy of Remotely Sensed Data - Principles and Practices Second edition (2009) CRC Press, Taylor & Francis Group, Boca Raton, FL 978-1-4200-5512-2 183 pp., Price: $99.95.
Int. J. Appl. Earth Obs. Geoinformation, 2009

Fusing Minnaert-k parameter with spectral unmixing for forest heterogeneity mapping using CHRIS-PROBA data.
Proceedings of the First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009

Using hyperspectral remote sensing data for retrieving canopy water content.
Proceedings of the First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009

2008
Unmixing-Based Landsat TM and MERIS FR Data Fusion.
IEEE Geosci. Remote. Sens. Lett., 2008

Using spectral information from the NIR water absorption features for the retrieval of canopy water content.
Int. J. Appl. Earth Obs. Geoinformation, 2008

2007
Preface.
Int. J. Appl. Earth Obs. Geoinformation, 2007


Physically-based retrievals of Norway spruce canopy variables from very high spatial resolution hyperspectral data.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2007


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