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Laurent Tits
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2020 – today
- 2023
- [j18]Koen De Vos
, Benjamin Campforts, Laurent Tits, Kristof Van Tricht, Kasper Bonte, Gerard Govers
Potential and limitations of crowdsourced data for high-resolution rice mapping in Madagascar: The importance of representation. Int. J. Appl. Earth Obs. Geoinformation 117: 103204 (2023) - [j17]Stephanie Delalieux
Red Palm Weevil Detection in Date Palm Using Temporal UAV Imagery. Remote. Sens. 15(5): 1380 (2023) - 2021
- [c13]Kasper Bonte, Mehrdad Moshtaghi, Kristof Van Tricht, Laurent Tits:
Automated Crop Harvest Detection Algorithm Based on Synergistic Use of Optical and Radar Satellite Imagery. IGARSS 2021: 5981-5984
2010 – 2019
- 2019
- [j16]Yasmin Vanbrabant, Laurent Tits
Multitemporal Chlorophyll Mapping in Pome Fruit Orchards from Remotely Piloted Aircraft Systems. Remote. Sens. 11(12): 1468 (2019) - 2018
- [c12]Stefan Livens, Stephanie Delalieux
Improved Coregistration of Multidate and Multisensor Orchard Imagery. WHISPERS 2018: 1-5 - 2017
- [j15]Wanda De Keersmaecker, Stefaan Lhermitte
Assessment of Regional Vegetation Response to Climate Anomalies: A Case Study for Australia Using GIMMS NDVI Time Series between 1982 and 2006. Remote. Sens. 9(1): 34 (2017) - 2016
- [j14]Jonathan Van Beek
Viewing Geometry Sensitivity of Commonly Used Vegetation Indices towards the Estimation of Biophysical Variables in Orchards. J. Imaging 2(2): 15 (2016) - [c11]Steven Puttemans
Automated visual fruit detection for harvest estimation and robotic harvesting. IPTA 2016: 1-6 - 2015
- [j13]Jonathan Van Beek
Reducing background effects in orchards through spectral vegetation index correction. Int. J. Appl. Earth Obs. Geoinformation 34: 167-177 (2015) - [j12]Raymond Struthers, Anna Ivanova, Laurent Tits
Thermal infrared imaging of the temporal variability in stomatal conductance for fruit trees. Int. J. Appl. Earth Obs. Geoinformation 39: 9-17 (2015) - [j11]Laurent Tits
A Geometric Unmixing Concept for the Selection of Optimal Binary Endmember Combinations. IEEE Geosci. Remote. Sens. Lett. 12(1): 82-86 (2015) - [j10]Jonathan Van Beek
Temporal Dependency of Yield and Quality Estimation through Spectral Vegetation Indices in Pear Orchards. Remote. Sens. 7(8): 9886-9903 (2015) - [j9]Anne Clasen, Ben Somers
Spectral Unmixing of Forest Crown Components at Close Range, Airborne and Simulated Sentinel-2 and EnMAP Spectral Imaging Scale. Remote. Sens. 7(11): 15361-15387 (2015) - [c10]Wanda De Keersmaecker, Stefaan Lhermitte, Laurent Tits
Towards the large-scale assessment of vegetation biomass production stability. MultiTemp 2015: 1-4 - 2014
- [j8]Jonathan Van Beek, Laurent Tits
Correction: Van Beek, J. et al. Stem Water Potential Monitoring in Pear Orchards through WorldView-2 Multispectral Imagery. Remote Sens, 2013, 5, 6647-6666. Remote. Sens. 6(2): 1760-1761 (2014) - [j7]Nicolas Dobigeon
A Comparison of Nonlinear Mixing Models for Vegetated Areas Using Simulated and Real Hyperspectral Data. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(6): 1869-1878 (2014) - [j6]Ben Somers
Quantifying Nonlinear Spectral Mixing in Vegetated Areas: Computer Simulation Model Validation and First Results. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(6): 1956-1965 (2014) - [j5]Marian-Daniel Iordache
A Dynamic Unmixing Framework for Plant Production System Monitoring. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(6): 2016-2034 (2014) - [j4]Stephanie Delalieux
Unmixing-Based Fusion of Hyperspatial and Hyperspectral Airborne Imagery for Early Detection of Vegetation Stress. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(6): 2571-2582 (2014) - [j3]Laurent Tits
Site-Specific Plant Condition Monitoring Through Hyperspectral Alternating Least Squares Unmixing. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(8): 3606-3618 (2014) - [c9]Wanda De Keersmaecker, Stefaan Lhermitte, Laurent Tits
Linking NDVI and climate-based ecosystem stability with land cover in Europe. IGARSS 2014: 3938-3940 - [c8]Nicolas Dobigeon, Laurent Tits
Nonlinear unmixing of vegetated areas: A model comparison based on simulated and real hyperspectral data. WHISPERS 2014: 1-4 - [c7]Laurent Tits
Validating nonlinear mixing models: Benchmark datasets from vegetated areas. WHISPERS 2014: 1-4 - 2013
- [j2]Jonathan Van Beek
Stem Water Potential Monitoring in Pear Orchards through WorldView-2 Multispectral Imagery. Remote. Sens. 5(12): 6647-6666 (2013) - [c6]Marian-Daniel Iordache
Improved signal unmixing of vegetation using sparse group selection. IGARSS 2013: 3018-3021 - [c5]Marian-Daniel Iordache
Plant production system monitoring via multiple signal classification and sparse regression. WHISPERS 2013: 1-4 - 2012
- [j1]Laurent Tits
The Potential and Limitations of a Clustering Approach for the Improved Efficiency of Multiple Endmember Spectral Mixture Analysis in Plant Production System Monitoring. IEEE Trans. Geosci. Remote. Sens. 50(6): 2273-2286 (2012) - [c4]Laurent Tits
First results of quantifying nonlinear mixing effects in heterogeneous forests: A modeling approach. IGARSS 2012: 7185-7188 - [c3]Laurent Tits
Shape-based unmixing for vegetation mapping. WHISPERS 2012: 1-4 - 2010
- [c2]Ben Somers
Soil reflectance modeling & hyperspectral mixture analysis: Towards vegetation spectra minimizing the soil background contamination. WHISPERS 2010: 1-4
2000 – 2009
- 2009
- [c1]Ben Somers
A Solution for the Mixture Problem in Agricultural Remote Sensing. IGARSS (5) 2009: 344-347
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