Lauwers, M.; De Cauwer, B.; Nuyttens, D.; Maes, W.H.; Pieters, J.G. (2024) Multispectral UAV image classification of jimson weed (Datura stramonium L.) in common bean (Phaseolus vulgaris L.). Remote Sensing, 16, 3538. [ link]
Mngadi, M.; Germishuizen, I.; Onisimo, M.; Naicker, R.; Maes, W.H.; Odebiri, O.; Schroder, M. (2024) A systematic review of the application of remote sensing technologies in mapping forest insect pests and diseases at a tree level. Remote Sensing Applications: Society and Environment, 36, 101341. [ link]
Wang, J.J., Lou, Y., Wang, W.T.; Liu, S.Y.; Zhang, H.H.; Hui, X.; Wang, Y.L.; Yan, H.J., Maes, W.H. A robust model for diagnosing water stress of winter wheat by combining UAV multispectral and thermal remote sensing. Agricultural water management 291:108616, 2024. [ link]
Wieme, J.; Leroux, S.; Cool, S.R.; Pieters, J.G.; Van Beek, J.; Maes, W.H. Ultra-high resolution UAV imaging and supervised deep learning for accurate detection of Alternaria solani in Potato fields. Frontiers in Plant Science 15: 1206998, 2024. [ link]
Heim, R.; Okole, N.; Steppe, K.; van Labeke, M-C.; Geedicke, I.; Maes, W.H. An applied framework to unlocking multi-angular UAV reflectance data: A case study for classification of plant parameters in maize (Zea mays). Precision Agriculture, 2024. [ link]
Missarov, A.; Sosnovsky, Y.; Rydlo, K.; Brovkina, O.; Maes, W.H.; Kral, K.; Krucek, M.; Krasylenko, Y. Vertical botany: airborne remote sensing as an emerging tool for mistletoe research. Botany, 2023. [ link]
Daniels, L.; Eeckhout, E.; Wieme, J.; Dejaegher, Y.; Audenaert, K.; Maes, W.H. Identifying the optimal radiometric calibration method for UAV-based multispectral imaging. Remote Sens. 2023, 15, 2909. [ link]
Vlaminck, M.; Diels, L.; Philips, W.; Maes, W.; Heim, R.; Wit, B.D.; Luong, H. A Multisensor UAV Payload and Processing Pipeline for Generating Multispectral Point Clouds. Remote Sens. 2023, 15, 1524. [ link]
Van de Vijver, R.; Mertens, K.; Heungens, K.; Nuyttens, D.; Wieme, J.; Maes, W.H.; Van Beek, J.; Somers, B.; Saeys, W. (2023). Ultra-high-resolution UAV-based detection of Alternaria solani infections in potato fields. Remote Sens. 2022, 24, 6232 [ link]
Vlaminck, M.; Heidbuchel, R.; Philips, W.; Luong, H. (2022). Region-Based CNN for Anomaly Detection in PV Power Plants Using Aerial Imagery. Deep Learning Methods for Aerial Imagery, special issue of Sensors 22(3), 1244. [ link]
Vivero, S.; Hendrickx, H.; Frankl, A.; Delaloye, R.; Lambiel, C. (2022). Kinematics and geomorphological changes of a destabilising rock glacier captured from close-range sensing techniques (Tsarmine rock glacier, Western Swiss Alps). FRONTIERS IN EARTH SCIENCE, 10. [ link]
Hendrickx, H.; Le Roy, G.; Helmstetter, A.; Pointner, E.; Larose, E.; Braillard, L.;Frankl, A. (2022). Timing, volume and precursory indicators of rock- and cliff fall on a permafrost mountain ridge (Mattertal, Switzerland). EARTH SURFACE PROCESSES AND LANDFORMS, 47, 1532–1549. [ link]
Luzardo, G.; Vlaminck, M.;Lefkaditis, D.;Philips, W.;Luong, H. (2021). GPS-Assisted Feature Matching in Aerial Images with Highly Repetitive Patterns. IEEE International Symposium on Geoscience and Remote Sensing (IGARSS). [ link]
De Swaef, T.; Maes, W.H.; Aper, J.; Baert, J.; Cougnon, M.; Reheul, D.; Steppe, K.; Roldán-Ruiz, I.; Lootens, P. (2021). Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses. Remote Sens., 13, 147. [ link]
Diaz, J.J.V.; Vlaminck, M.; Lefkaditis, D.; Vargas, S.A.O.; Luong, H. (2020). Solar panel detection within complex backgrounds using thermal images acquired by UAVs, UAV Imagery for Engineering Applications Using Artificial Intelligence Techniques (UAV-AI), special issue of Sensors 20(21), 6219. [ link]
Maes, W.H; Pagán, B.; Li, X.; Xiao, J.; Miralles, D. (2020). Sun-induced fluorescence closely linked to ecosystem transpiration as evidenced by satellite data and radiative transfer models. Remote Sensing of Environment. [ link]
Maes, W.H.; Steppe, K. (2019). Perspectives for remote sensing with Unmanned Aerial Vehicles in precision agriculture. Trends in Plant Science, 24 : 45. [ link]
Hendrickx, H.; De Sloover, L.; Stal, C.; Delaloye, R.; Nyssen, J.; & Frankl, A. (2020). Talus slope geomorphology investigated at multiple time scales from high-resolution topographic surveys and historical aerial photographs (Sanetsch Pass, Switzerland). EARTH SURFACE PROCESSES AND LANDFORMS, 45(14), 3653–3669. [ link]
Maes, W.H.; Huete, A.R.; Avino, M.; Boer, M.M.; Dehaan, R.; Pendall, E.; Griebel, A.; Steppe, K. (2018). Can UAV-based infrared thermography be used to study plant-parasite interactions between mistletoe and eucalypt trees? Remote Sensing, 12 : 2062 [ link]
Hendrickx, H.; Vivero, S.; De Cock, L.; De Wit, B.; De Maeyer, P.; Lambiel, C.; Frankl, A. (2019). The reproducibility of SfM algorithms to produce detailed Digital Surface Models : the example of PhotoScan applied to a high-alpine rock glacier. REMOTE SENSING LETTERS, 10(1), 11–20. [ link]
Maes, W.H.; Huete, A.R.; Steppe, K. (2017). Optimizing the processing of UAV-based thermal imagery. Remote Sensing, 9 : 476. [ link]
Cleverly, J.; Eamus, D.; Restrepo Coupe, N.; Chen, C.; Maes, W. H.; Li, L.; Faux, R.; Santini, N.S.; Rumman, R.; Yu, Q.; Huete, A.R. (2016). Soil moisture controls on phenology and productivity in semi-arid critical zone. Science of the Total Environment, 568 : 1227-1237. [ link]