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Publicaciones

2024

  • Anderson, M. C., Kustas, W. P., Norman, J. M., Diak, G. T., Hain, C. R., Gao, F., Yang, Y., Knipper, K. R., Xue, J., Yang, Y., Crow, W. T., Holmes, T. R. H., Nieto, H., Guzinski, R., Otkin, J. A., Mecikalski, J. R., Cammalleri, C., Torres-Rua, A. T., Zhan, X., … Agam, N. (2024). A brief history of the thermal IR-based Two-Source Energy Balance (TSEB) model – diagnosing evapotranspiration from plant to global scales. Agricultural and Forest Meteorology, 350, 109951. doi.org/10.1016/j.agrformet.2024.109951
  • Belissent, N., Peña, J. M., Mesías-Ruiz, G. A., Shawe-Taylor, J., & Pérez-Ortiz, M. (2024). Transfer and zero-shot learning for scalable weed detection and classification in UAV images. Knowledge-Based Systems, 292, 111586. doi.org/10.1016/j.knosys.2024.111586
  • Blanchy, G., McLachlan, P., Mary, B., Censini, M., Boaga, J., & Cassiani, G. (2024). Comparison of multi-coil and multi-frequency frequency domain electromagnetic induction instruments. Frontiers in Soil Science, 4. doi.org/10.3389/fsoil.2024.1239497
  • Burchard-Levine, V., Borra-Serrano, I., Peña, J. M., Kustas, W. P., Guerra, J. G., Dorado, J., Mesías-Ruiz, G., Herrezuelo, M., Mary, B., McKee, L. M., de Castro, A. I., Sanchez-Élez, S., & Nieto, H. (2024). Evaluating the precise grapevine water stress detection using unmanned aerial vehicles and evapotranspiration-based metrics. Irrigation Science. doi.org/10.1007/s00271-024-00931-9
  • Burchard-Levine, V., Guerra, J. G., Borra-Serrano, I., Nieto, H., Mesías-Ruiz, G., Dorado, J., de Castro, A. I., Herrezuelo, M., Mary, B., Aguirre, E. P., & Peña, J. M. (2024). Evaluating the utility of combining high resolution thermal, multispectral and 3D imagery from unmanned aerial vehicles to monitor water stress in vineyards. Precision Agriculture. doi.org/10.1007/s11119-024-10179-0
  • Ghisi, T., Fischer, M., Nieto, H., Kowalska, N., Jocher, G., Homolová, L., Burchard-Levine, V., Žalud, Z., & Trnka, M. (2024). Evaluation of the METRIC and TSEB remote sensing evapotranspiration models in the floodplain area of the Thaya and Morava Rivers. Journal of Hydrology: Regional Studies, 53, 101785. doi.org/10.1016/j.ejrh.2024.101785
  • Gómez-Giráldez, P. J., Cristóbal, J., Nieto, H., García-Díaz, D., & Díaz-Delgado, R. (2024). Validation of Gross Primary Production Estimated by Remote Sensing for the Ecosystems of Doñana National Park through Improvements in Light Use Efficiency Estimation. Remote Sensing, 16(12), Article 12. doi.org/10.3390/rs16122170
  • Mesías-Ruiz, G. A., Borra-Serrano, I., Peña, J. M., de Castro, A. I., Fernández-Quintanilla, C., & Dorado, J. (2024). Weed species classification with UAV imagery and standard CNN models: Assessing the frontiers of training and inference phases. Crop Protection, 182, 106721. doi.org/10.1016/j.cropro.2024.106721
  • Mesías-Ruiz, G. A., Peña, J. M., de Castro, A. I., Borra-Serrano, I., & Dorado, J. (2024). Cognitive Computing Advancements: Improving Precision Crop Protection through UAV Imagery for Targeted Weed Monitoring. Remote Sensing, 16(16), Article 16. doi.org/10.3390/rs16163026
  • Pavoni, M., Boaga, J., Peruzzo, L., Barone, I., Mary, B., & Cassiani, G. (2024). Characterization of a Contaminated Site Using Hydro-Geophysical Methods: From Large-Scale ERT Surface Investigations to Detailed ERT and GPR Cross-Hole Monitoring. Water, 16(9), Article 9. doi.org/10.3390/w16091280
  • Pranga, J., Borra-Serrano, I., Quataert, P., De Swaef, T., Vanden Nest, T., Willekens, K., Ruysschaert, G., Janssens, I. A., Roldán-Ruiz, I., & Lootens, P. (2024). Quantification of species composition in grass-clover swards using RGB and multispectral UAV imagery and machine learning. Frontiers in Plant Science, 15. doi.org/10.3389/fpls.2024.1414181
  • Sánchez, J. M., Galve, J. M., Nieto, H., & Guzinski, R. (2024). Assessment of High-Resolution LST Derived From the Synergy of Sentinel-2 and Sentinel-3 in Agricultural Areas. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 916–928. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. doi.org/10.1109/JSTARS.2023.3335896
  • Unnisa, Z., Govind, A., Prikaziuk, E., Van der Tol, C., Lasserre, B., Burchard-Levine, V., & Marchetti, M. (2024). Assessing Evapotranspiration Models for Regional Implementation in the Mediterranean: A Comparative Analysis of STEPS, TSEB, and SCOPE with Global Datasets. Applied Sciences, 14(17), Article 17. doi.org/10.3390/app14177685
  • Vleugels, T., Saleem, A., Dubey, R., Muylle, H., Borra-Serrano, I., Lootens, P., De Swaef, T., & Roldán-Ruiz, I. (2024). Phenotypic characterization of drought responses in red clover (Trifolium pratense L.). Frontiers in Plant Science, 14. doi.org/10.3389/fpls.2023.1304411

2023

  • Gao, R., Torres-Rua, A.F., Nieto, H., Zahn, E., Hipps, L., Kustas, W.P., Alsina, M.M., Bambach, N., Castro, S.J., Prueger, J.H., Alfieri, J., McKee, L.G., White, W.A., Gao, F., McElrone, A.J., Anderson, M., Knipper, K., Coopmans, C., Gowing, I., Agam, N., Sanchez, L., Dokoozlian, N. (2023). ET Partitioning Assessment Using the TSEB Model and sUAS Information across California Central Valley Vineyards. Remote Sensing 15, 756. doi.org/10.3390/rs15030756
  • Garcia-Tejera O., Bonada M., Petrie P.R., Nieto H., Bellvert J., Sadras V.O. (2023) Viticulture adaptation to global warming: Modelling gas exchange, water status and leaf temperature to probe for practices manipulating water supply, canopy reflectance and radiation load. Agricultural and Forest Meteorology 331, 109351; doi.org/10.1016/j.agrformet.2023.109351
  • Ghisi, T., Fischer, M., Kowalska, N., Jocher, G., Orság, M., Bláhová, M., Nieto, H., Homolová, L., Žalud, Z., Trnka, M. (2023) Faster evapotranspiration recovery compared to canopy development post clearcutting in a floodplain forest. Forest Ecology and Management 532, 120828. doi.org/10.1016/j.foreco.2023.120828
  • Guzinski, R., Nieto, H., Ramo Sánchez, R., Sánchez, J.M., Jomaa, I., Zitouna-Chebbi, R., Roupsard, O., López-Urrea, R. (2023) Improving field-scale crop actual evapotranspiration monitoring with Sentinel-3, Sentinel-2, and Landsat data fusion. International Journal of Applied Earth Observation and Geoinformation 125, 103587. doi.org/10.1016/j.jag.2023.10358
  • Martín M.P., Ponce B., Echevarría P., Dorado J., Fernández-Quintanilla C. (2023) Early-season mapping of Johnsongrass (Sorghum halepense), Common Cocklebur (Xanthium strumarium) and Velvetleaf (Abutilon theophrasti) in corn fields using airborne hyperspectral imagery. Agronomy 13, 528; doi.org/10.3390/agronomy13020528
  • Mesías-Ruiz G.A., Pérez-Ortiz M., Dorado J., de Castro A.I., Peña J.M. (2023) Boosting precision crop protection towards agriculture 5.0 (Ag5.0) via machine learning and emerging technologies. Frontiers in Plant Science 14, 1143326; doi.org/10.3389/fpls.2023.1143326
  • Meza, K., Torres-Rua, A.F., Hipps, L., Kustas, W.P., Gao, R., Christiansen, L., Kopp, K., Nieto, H., Burchard-Levine, V., Martín, M.P., Coopmans, C., Gowing, I. (2023) Spatial estimation of actual evapotranspiration over irrigated turfgrass using sUAS thermal and multispectral imagery and TSEB model. Irrigation Science, in press. doi.org/10.1007/s00271-023-00899-y
  • Peng, J., Nieto, H., Neumann Andersen, M., Kørup, K., Larsen, R., Morel, J., Parsons, D., Zhou, Z., Manevski, K. (2023) Accurate estimates of land surface energy fluxes and irrigation requirements from UAV-based thermal and multispectral sensors. ISPRS Journal of Photogrammetry and Remote Sensing 198, 238–254. doi.org/10.1016/j.isprsjprs.2023.03.009

2022

  • Aboutalebi, M., Torres-Rua, A.F., McKee, M., Kustas, W.P., Nieto, H., Alsina, M.M., White, A., Prueger, J.H., McKee, L., Alfieri, J., Hipps, L., Coopmans, C., Sanchez, L., Dokoozlian, N. Downscaling UAV land surface temperature using a coupled wavelet-machine learning-optimization algorithm and its impact on evapotranspiration (2022) Irrigation Science, DOI: 10.1007/s00271-022-00801-2
  • Burchard-Levine, V., Nieto, H., Kustas, W.P., Gao, F., Alfieri, J.G., Prueger, J.H., Hipps, L.E., Bambach-Ortiz, N., McElrone, A.J., Castro, S.J., Alsina, M.M., McKee, L.G., Zahn, E., Bou-Zeid, E., Dokoozlian, N. Application of a remote-sensing three-source energy balance model to improve evapotranspiration partitioning in vineyards (2022) Irrigation Science, DOI: 10.1007/s00271-022-00787-x
  • Burchard-Levine, V., Nieto, H., Riaño, D., Kustas, W.P., Migliavacca, M., El-Madany, T.S., Nelson, J.A., Andreu, A., Carrara, A., Beringer, J., Baldocchi, D., Martín, M.P. A remote sensing-based three-source energy balance model to improve global estimations of evapotranspiration in semi-arid tree-grass ecosystems (2022) Global Change Biology, 28 (4), pp. 1493-1515. DOI: 10.1111/gcb.16002
  • Fernández-Quintanilla C., Dorado J., Andújar D., Peña J.M. (2022) Advanced detection technologies for weed scouting. In: Advances in Integrated Weed Management (P Kudsk, ed.), chapter 8, 24 pp., Burleigh Dodds Science Publishing Limited; ISBN-13: 9781786767455
  • Gao, R., Torres-Rua, A.F., Aboutalebi, M., White, W.A., Anderson, M., Kustas, W.P., Agam, N., Alsina, M.M., Alfieri, J., Hipps, L., Dokoozlian, N., Nieto, H., Gao, F., McKee, L.G., Prueger, J.H., Sanchez, L., Mcelrone, A.J., Bambach-Ortiz, N., Coopmans, C., Gowing, I. LAI estimation across California vineyards using sUAS multi-seasonal multi-spectral, thermal, and elevation information and machine learning (2022) Irrigation Science, DOI: 10.1007/s00271-022-00776-0
  • Guerra J.G., Cabello F., Fernández-Quintanilla C., Peña J.M., Dorado J. (2022) How weed management influence plant community composition, taxonomic diversity and crop yield: A long-term study in a Mediterranean vineyard. Agriculture, Ecosystems & Environment 326, 107816; https://doi.org/10.1016/j.agee.2021.107816
  • Guerra J.G., Cabello F., Fernández-Quintanilla C., Peña J.M., Dorado J. (2022) Plant functional diversity is affected by weed management through processes of trait convergence and divergence: A long-term study in vineyard weed communities. Frontiers in Plant Science; doi: 10.3389/fpls.2022.993051.
  • Guerra J.G., Cabello F., Fernández-Quintanilla C., Peña J.M., Dorado J. (2022) Use of under-vine living mulches to control noxious weeds in irrigated Mediterranean vineyards. Plants 2022, 11, 1921; doi:10.3390/plants11151921
  • Jofre-Cekalovic, C., Nieto, H., Girona, J., Pamies-Sans, M., Bellvert, J. Accounting for almond crop water use under different irrigation regimes with a two-source energy balance model and Copernicus-based inputs (2022) Remote Sensing, 14 (9), art. no. 2106, DOI: 10.3390/rs14092106
  • Kang, Y., Gao, F., Anderson, M., Kustas, W., Nieto, H., Knipper, K., Yang, Y., White, W., Alfieri, J., Torres-Rua, A., Alsina, M.M., Karnieli, A. Evaluation of satellite Leaf Area Index in California vineyards for improving water use estimation (2022) Irrigation Science, DOI: 10.1007/s00271-022-00798-8
  • Kustas, W.P., Nieto, H., Garcia-Tejera, O., Bambach, N., McElrone, A.J., Gao, F., Alfieri, J.G., Hipps, L.E., Prueger, J.H., Torres-Rua, A., Anderson, M.C., Knipper, K., Alsina, M.M., McKee, L.G., Zahn, E., Bou-Zeid, E., Dokoozlian, N. Impact of advection on two-source energy balance (TSEB) canopy transpiration parameterization for vineyards in the California Central Valley (2022) Irrigation Science, DOI: 10.1007/s00271-022-00778-y
  • Nieto, H., Alsina, M.M., Kustas, W.P., García-Tejera, O., Chen, F., Bambach, N., Gao, F., Alfieri, J.G., Hipps, L.E., Prueger, J.H., McKee, L.G., Zahn, E., Bou-Zeid, E., McElrone, A.J., Castro, S.J., Dokoozlian, N. Evaluating different metrics from the thermal-based two-source energy balance model for monitoring grapevine water stress (2022) Irrigation Science, DOI: 10.1007/s00271-022-00790-2
  • Nassar, A., Torres-Rua, A., Hipps, L., Kustas, W., McKee, M., Stevens, D., Nieto, H., Keller, D., Gowing, I., Coopmans, C. Using remote sensing to estimate scales of spatial heterogeneity to analyze evapotranspiration modeling in a natural ecosystem (2022) Remote Sensing, 14 (2), art. no. 372, DOI: 10.3390/rs14020372
  • Simpson, J.E., Holman, F.H., Nieto, H., El-Madany, T.S., Migliavacca, M., Martin, M.P., Burchard-Levine, V., Cararra, A., Blöcher, S., Fiener, P., Kaplan, J.O. UAS-based high resolution mapping of evapotranspiration in a Mediterranean tree-grass ecosystem (2022) Agricultural and Forest Meteorology, 321, art. no. 108981, DOI: 10.1016/j.agrformet.2022.108981
  • Tunca, E., Köksal, E.S., Torres-Rua, A., Kustas, W.P., Nieto, H. Estimation of bell pepper evapotranspiration using two-source energy balance model based on high-resolution thermal and visible imagery from unmanned aerial vehicles (2022) Journal of Applied Remote Sensing, 16 (2), art. no. 022204, DOI: 10.1117/1.JRS.16.022204

2021

  • Aguirre-García, S.D., Aranda-Barranco, S., Nieto, H., Serrano-Ortiz, P., Sánchez-Cañete, E.-P., Guerrero-Rascado, J.-L. Modelling actual evapotranspiration using a two source energy balance model with Sentinel imagery in herbaceous-free and herbaceous-cover Mediterranean olive orchards (2021) Agricultural and Forest Meteorology, 311, art. no. 108692, DOI: 10.1016/j.agrformet.2021.108692
  • Bellvert, J., Nieto, H., Pelechá, A., Jofre-Čekalović, C., Zazurca, L., Miarnau, X. Remote sensing energy balance model for the assessment of crop evapotranspiration and water status in an almond rootstock collection (2021) Frontiers in Plant Science, 12, art. no. 608967, DOI: 10.3389/fpls.2021.608967
  • Burchard-Levine, V., Nieto, H., Riaño, D., Migliavacca, M., El-Madany, T.S., Guzinski, R., Carrara, A., Martín, M.P. The effect of pixel heterogeneity for remote sensing based retrievals of evapotranspiration in a semi-arid tree-grass ecosystem (2021) Remote Sensing of Environment, 260, art. no. 112440, DOI: 10.1016/j.rse.2021.112440
  • de Castro A.I., Shi Y., Maja J.M., Peña, J.M. (2021) UAVs for vegetation monitoring: Overview and recent scientific contributions. Remote Sensing 2021, 13(11), 2139; https://doi.org/10.3390/rs13112139
  • Dorado J., Almendros G. (2021) Organo-mineral interactions involved in herbicide sorption on soil amended with peats of different maturity degree. Agronomy 2021, 11, 869; https://doi.org/10.3390/agronomy11050869
  • Guerra J.G., Cabello F., Fernández-Quintanilla C., Dorado J. (2021) A trait-based approach in a Mediterranean vineyard: Effects of agricultural management on the functional structure of plant communities. Agriculture, Ecosystems & Environment 316, 107465; https://doi.org/10.1016/j.agee.2021.107465
  • Guzinski, R., Nieto, H., Sanchez, J.M., Lopez-Urrea, R., Boujnah, D.M., Boulet, G. Utility of Copernicus-based inputs for actual evapotranspiration modeling in support of sustainable water use in agriculture (2021) IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, pp. 11466-11484. DOI: 10.1109/JSTARS.2021.3122573
  • Lati RN, Rasmussen J, Andújar D, Dorado J, Berge TW, Wellhausen C, Pflanz M, Nordmeyer H, Schirrmann M, Eizenberg H, Neve P, Jørgensen RN, Christensen S (2021) Site-specific weed management – constraints and opportunities for the weed research community. Weed Research 61(3), 147–153; https://doi.org/10.1111/wre.12469
  • Lima F., Blanco-Sepúlveda R., Gómez-Moreno M.L., Dorado J., Peña J.M. (2021) Mapping tillage direction and contour farming by object-based analysis of UAV images. Computers and Electronics in Agriculture 187, 106281; https://doi.org/10.1016/j.compag.2021.106281
  • Nassar, A., Torres-Rua, A., Kustas, W., Alfieri, J., Hipps, L., Prueger, J., Nieto, H., Alsina, M.M., White, W., McKee, L., Coopmans, C., Sanchez, L., Dokoozlian, N. Assessing daily evapotranspiration methodologies from one-time-of-day sUAS and EC information in the grapex project (2021) Remote Sensing, 13 (15), art. no. 2887, DOI: 10.3390/rs13152887
  • Simpson, J.E., Holman, F., Nieto, H., Voelksch, I., Mauder, M., Klatt, J., Fiener, P., Kaplan, J.O. High spatial and temporal resolution energy flux mapping of different land covers using an off-the-shelf unmanned aerial system (2021) Remote Sensing, 13 (7), art. no. 1286, DOI: 10.3390/rs13071286
  • Torres, P., Rodes-Blanco, M., Viana-Soto, A., Nieto, H., García, M. The role of remote sensing for the assessment and monitoring of forest health: A systematic evidence synthesis (2021) Forests, 12 (8), art. no. 1134, DOI: 10.3390/f12081134

2020

  • Aboutalebi, M., Torres-Rua, A.F., McKee, M., Kustas, W.P., Nieto, H., Alsina, M.M., White, A., Prueger, J.H., McKee, L., Alfieri, J., Hipps, L., Coopmans, C., Dokoozlian, N. Incorporation of Unmanned Aerial Vehicle (UAV) point cloud products into remote sensing evapotranspiration models
    (2020) Remote Sensing, 12 (1), art. no. 50, DOI: 10.3390/RS12010050
  • Bellvert, J., Jofre-Ĉekalović, C., Pelechá, A., Mata, M., Nieto, H. Feasibility of using the two-source energy balance model (TSEB) with Sentinel-2 and Sentinel-3 images to analyze the spatio-temporal variability of vine water status in a vineyard (2020) Remote Sensing, 12 (14), art. no. 2299, DOI: 10.3390/rs12142299
  • Burchard-Levine, V., Nieto, H., Riaño, D., Migliavacca, M., El-Madany, T.S., Perez-Priego, O., Carrara, A., Martín, M.P. Seasonal adaptation of the thermal-based two-source energy balance model for estimating evapotranspiration in a semiarid tree-grass ecosystem (2020) Remote Sensing, 12 (6), art. no. 904, DOI: 10.3390/rs12060904
  • de Castro AI, Peña JM, Torres-Sánchez J, Jiménez-Brenes FM, Valencia-Gredilla F, Recasens J, López-Granados F (2020) Mapping Cynodon dactylon infesting cover crops with an automatic decision tree-OBIA procedure and UAV imagery for precision viticulture. Remote Sensing 12, 56. https://doi.org/10.3390/rs12010056
  • Egea-Cobrero V, Bradley K, Calha I, Davis AS, Dorado J, Forcella F, Lindquist JL, Sprague CL, Gonzalez-Andujar JL (2020) Validation of predictive empirical weed emergence models of Abutilon theophrasti Medik Based on intercontinental data. Weed Research 60, 297–302. https://doi.org/10.1111/wre.12428
  • Fernández‐Quintanilla C, Barroso J (2020) Impacto del cambio climático sobre los sistemas de gestión de malas hierbas. ITEA 116: 396–404. https://doi.org/10.12706/itea.2020.034
  • Fernández-Quintanilla C, Dorado J, Andújar D, Peña JM (2020) Site-Specific Based Models. In: Decision Support Systems for Weed Management (GR Chantre, JL González-Andújar, ed.), pp. 143–157, Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-44402-0_7
  • Guzinski, R., Nieto, H., Sandholt, I., Karamitilios, G. Modelling high-resolution actual evapotranspiration through Sentinel-2 and Sentinel-3 data fusion (2020) Remote Sensing, 12 (9), art. no. 1433, DOI: 10.3390/RS12091433
  • Knipper, K.R., Kustas, W.P., Anderson, M.C., Nieto, H., Alfieri, J.G., Prueger, J.H., Hain, C.R., Gao, F., McKee, L.G., Alsina, M.M., Sanchez, L. Using high-spatiotemporal thermal satellite ET retrievals to monitor water use over California vineyards of different climate, vine variety and trellis design (2020) Agricultural Water Management, 241, art. no. 106361, DOI: 10.1016/j.agwat.2020.106361
  • Li, Y., Huang, C., Kustas, W.P., Nieto, H., Sun, L., Hou, J. Evapotranspiration partitioning at field scales using tseb and multi-satellite data fusion in the middle reaches of heihe river basin, Northwest China (2020) Remote Sensing, 12 (19), art. no. 3223, pp. 1-25, DOI: 10.3390/rs12193223
  • Luna IM, Fernández-Quintanilla C, Dorado J (2020) Is pasture cropping a valid weed management tool? Plants 9, 135. https://doi:10.3390/plants9020135
  • Messina G, Peña JM, Vizzari M, Modica G (2020) A comparison of UAV and satellites multispectral imagery in monitoring onion crop. An application in the ‘cipolla rossa di tropea’ (Italy). Remote Sensing 12, 3424. https://doi.org/10.3390/rs12203424
  • Nassar, A., Torres-Rua, A., Kustas, W., Nieto, H., McKee, M., Hipps, L., Stevens, D., Alfieri, J., Prueger, J., Alsina, M.M., McKee, L., Coopmans, C., Sanchez, L., Dokoozlian, N. Influence of model grid size on the estimation of surface fluxes using the two source energy balance model and sUAS imagery in vineyards (2020) Remote Sensing, 12 (3), art. no. 342, DOI: 10.3390/rs12030342
  • Peña JM, Orno-Badía C, Dorado J, de Castro AI, Recasens J (2020) Drones y digitalización para el manejo localizado en maíz. Agricultura 1044:40–45
  • Prats-Llinàs, M.T., Nieto, H., DeJong, T.M., Girona, J., Marsal, J. Using forced regrowth to manipulate Chardonnay grapevine (Vitis vinifera L.) development to evaluate phenological stage responses to temperature (2020) Scientia Horticulturae, 262, art. no. 109065, DOI: 10.1016/j.scienta.2019.109065
  • Song, L., Bian, Z., Kustas, W.P., Liu, S., Xiao, Q., Nieto, H., Xu, Z., Yang, Y., Xu, T., Han, X. Estimation of surface heat fluxes using multi-angular observations of radiative surface temperature (2020) Remote Sensing of Environment, 239, art. no. 111674, DOI: 10.1016/j.rse.2020.111674

2019

  • Aboutalebi, M., Torres-Rua, A.F., Kustas, W.P., Nieto, H., Coopmans, C., McKee, M. Assessment of different methods for shadow detection in high-resolution optical imagery and evaluation of shadow impact on calculation of NDVI, and evapotranspiration (2019) Irrigation Science, 37 (3), pp. 407-429. DOI: 10.1007/s00271-018-0613-9
  • Andreu, A., Dube, T., Nieto, H., Mudau, A.E., González-Dugo, M.P., Guzinski, R., Hülsmann, S. Remote sensing of water use and water stress in the African savanna ecosystem at local scale – Development and validation of a monitoring tool (2019) Physics and Chemistry of the Earth, 112, pp. 154-164, DOI: 10.1016/j.pce.2019.02.004
  • Alfieri, J.G., Kustas, W.P., Nieto, H., Prueger, J.H., Hipps, L.E., McKee, L.G., Gao, F., Los, S. Influence of wind direction on the surface roughness of vineyards (2019) Irrigation Science, 37 (3), pp. 359-373, DOI: 10.1007/s00271-018-0610-z
  • De Cal A, Fernández-Quintanilla C, Jaques JA (2019) Programas de I+D orientados específicamente a sistemas de gestión integrada de enfermedades, plagas y malas hierbas. In: Libro Blanco de la Sanidad Vegetal en España (RM Jiménez Díaz, MM López González, eds.), pp. 615–624, UCOPress. ISBN 978-84-9927-455-3.
  • de Castro AI, Peña JM (2019) Teledetección de malas hierbas y enfermedades en producción agraria. Tierras 275: 59–66
  • Castillejo-González IL, de Castro AI, Jurado-Expósito M, Peña JM, García-Ferrer A, López-Granados F (2019) Assessment of the persistence of Avena sterilis L patches in wheat fields for site-specific sustainable management. Agronomy 9, 30. https://doi.org/10.3390/agronomy9010030
  • Castillejo-Gonzalez IL, De Castro AI, Jurado-Exposito M, Peña-Barragán JM, García-Ferrer A, López-Granados F (2019) Predicen el crecimiento de una mala hierba del trigo para reducir el uso de herbicidas. Interempresas. http://www.interempresas.net/Grandes-cultivos/Articulos/242814-Predicen-el-crecimiento-de-una-mala-hierba-del-trigo-para-reducir-el-uso-de-herbicidas.html.
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