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  • 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;
  • 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;
  • 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;


  • 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;
  • 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


  • 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;
  • 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;
  • 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;
  • 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;
  • 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;
  • 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


  • 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.
  • 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.
  • Fernández‐Quintanilla C, Barroso J (2020) Impacto del cambio climático sobre los sistemas de gestión de malas hierbas. ITEA 116: 396–404.
  • 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.
  • 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.
  • 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


  • 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.
  • 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.
  • Fernández-Quintanilla C, González-Andújar JL (2019) Sobre la multifuncionalidad de las llamadas ‘malas hierbas’. Phytoma España 306: 1–4.
  • Freeman D, Gupta S, Smith DH, Maja JM, Robbins J, Owen JS, Peña JM, de Castro AI (2019) Watson on the farm: using cloud-based artificial intelligence to identify early indicators of water stress. Remote Sensing 11, 2645.
  • Guzinski, R., Nieto, H. Evaluating the feasibility of using Sentinel-2 and Sentinel-3 satellites for high-resolution evapotranspiration estimations
    (2019) Remote Sensing of Environment, 221, pp. 157-172, DOI: 10.1016/j.rse.2018.11.019
  • Jiménez-Brenes FM, López-Granados F, Torres-Sánchez J, Peña JM, Ramírez P, Castillejo-González IL, de Castro AI (2019) Automatic UAV-based detection of Cynodon dactylon for site-specific vineyard management. PLOS ONE 14, e0218132. https://doi:10.1371/journal.pone.0218132
  • Knipper, K.R., Kustas, W.P., Anderson, M.C., Alfieri, J.G., Prueger, J.H., Hain, C.R., Gao, F., Yang, Y., McKee, L.G., Nieto, H., Hipps, L.E., Alsina, M.M., Sanchez, L. Evapotranspiration estimates derived using thermal-based satellite remote sensing and data fusion for irrigation management in California vineyards (2019) Irrigation Science, 37 (3), pp. 431-449, DOI: 10.1007/s00271-018-0591-y
  • Kustas, W.P., Alfieri, J.G., Nieto, H., Wilson, T.G., Gao, F., Anderson, M.C. Utility of the two-source energy balance (TSEB) model in vine and interrow flux partitioning over the growing season (2019) Irrigation Science, 37 (3), pp. 375-388, DOI: 10.1007/s00271-018-0586-8
  • Li, Y., Kustas, W.P., Huang, C., Nieto, H., Haghighi, E., Anderson, M.C., Domingo, F., Garcia, M., Scott, R.L. Evaluating soil resistance formulations in thermal-based two-source energy balance (TSEB) model: Implications for heterogeneous semiarid and arid regions (2019) Water Resources Research, DOI: 10.1029/2018WR022981
  • Loddo D, Bozic D, Calha I, Dorado J, Izquierdo J, Šćepanović M, Barić K, Carlesi S, Leskovsek R, Peterson D, Vasileiadis V, Veres A, Vrbničanin S & Masin R (2019) Variability in seedling emergence for European and North American populations of Abutilon theophrasti. Weed Research 59, 15–27.
  • López Moya JJ, Melgarejo P, De Cal A, Jacas J, Fernández-Quintanilla C (2019) Debilidades y fortalezas de la I+D+i en Sanidad Vegetal en el sistema español. In: Libro Blanco de la Sanidad Vegetal en España (RM Jiménez Díaz, MM López González, eds.), pp. 635–650, UCOPress. ISBN 978-84-9927-455-3.
  • Nieto, H., Kustas, W.P., Alfieri, J.G., Gao, F., Hipps, L.E., Los, S., Prueger, J.H., McKee, L.G., Anderson, M.C. Impact of different within-canopy wind attenuation formulations on modelling sensible heat flux using TSEB (2019) Irrigation Science, 37 (3), pp. 315-331, DOI: 10.1007/s00271-018-0611-y
  • Nieto, H., Kustas, W.P., Torres-Rúa, A., Alfieri, J.G., Gao, F., Anderson, M.C., White, W.A., Song, L., Alsina, M.M., Prueger, J.H., McKee, M., Elarab, M., McKee, L.G. Evaluation of TSEB turbulent fluxes using different methods for the retrieval of soil and canopy component temperatures from UAV thermal and multispectral imagery (2019) Irrigation Science, 37 (3), pp. 389-406, DOI: 10.1007/s00271-018-0585-9
  • Ostos Garrido FJ, de Castro AI, Pistón F, Torres-Sánchez J, Peña JM (2019) High-throughput phenotyping of bioethanol potential in cereals by using multi-temporal UAV-based imagery. Frontiers in Plant Science 10, 948. https://doi:10.3389/fpls.2019.00948
  • Parry, C.K., Nieto, H., Guillevic, P., Agam, N., Kustas, W.P., Alfieri, J., McKee, L., McElrone, A.J. An intercomparison of radiation partitioning models in vineyard canopies (2019) Irrigation Science, 37 (3), pp. 239-252, DOI: 10.1007/s00271-019-00621-x
  • Peña JM (2019) La revolución tecnológica está llegando al sector agrícola para quedarse. Interempresas.
  • Peña JM, Ostos-Garrido FJ, Torres-Sánchez J, Pistón F, de Castro AI (2019) A UAV-based system for monitoring crop growth in wheat, barley and triticale phenotyping field trials. In: Precision Agriculture’2019 (J.V. Stafford, ed.), pp. 397–403, Wageningen Academic Publisher, The Netherlands. ISBN: 978-90-8686-337-2.
  • Prueger, J.H., Parry, C.K., Kustas, W.P., Alfieri, J.G., Alsina, M.M., Nieto, H., Wilson, T.G., Hipps, L.E., Anderson, M.C., Hatfield, J.L., Gao, F., McKee, L.G., McElrone, A., Agam, N., Los, S.A. Crop Water Stress Index of an irrigated vineyard in the Central Valley of California (2019) Irrigation Science, 37 (3), pp. 297-313, DOI: 10.1007/s00271-018-0598-4
  • Rueda-Ayala, V P, Peña, J M, Höglind, M, Bengochea-Guevara, J M, & Andújar, D (2019) Comparing UAV-based technologies and RGB-D reconstruction methods for plant height and biomass monitoring on Grass Ley. Sensors 19, 535. https://doi:10.3390/s19030535
  • White, W.A., Alsina, M.M., Nieto, H., McKee, L.G., Gao, F., Kustas, W.P. Determining a robust indirect measurement of leaf area index in California vineyards for validating remote sensing-based retrievals (2019) Irrigation Science, 37 (3), pp. 269–280, DOI: 10.1007/s00271-018-0614-8


  • Andújar D, Calle M, Fernández-Quintanilla C, Ribeiro A & Dorado J (2018) Three-dimensional modeling of weed plants using low-cost photogrammetry. Sensors 18, 1077. https://doi:10.3390/s18041077
  • de Castro AI, Jiménez-Brenes FM, Torres-Sánchez J, Peña JM, Borra-Serrano I, López-Granados F (2018) 3-D characterization of vineyards using a novel UAV imagery-based OBIA procedure for precision viticulture applications. Remote Sensing 10, 584.
  • de Castro AI, Six J, Plant RE, Peña JM (2018) Mapping crop calendar events and phenology-related metrics at the parcel level by Object-Based Image Analysis (OBIA) of MODIS-NDVI time-series: A case study in Central California. Remote Sensing 10, 1745. https://doi:10.3390/rs10111745
  • de Castro AI, Torres-Sánchez J, Peña JM, Jiménez-Brenes FM, Csillik O, López-Granados F (2018) An automatic Random Forest-OBIA algorithm for early weed mapping between and within crop rows using UAV imagery. Remote Sensing 10, 285.
  • El-Madany, T.S., Reichstein, M., Perez-Priego, O., Carrara, A., Moreno, G., Pilar Martín, M., Pacheco-Labrador, J., Wohlfahrt, G., Nieto, H., Weber, U., Kolle, O., Luo, Y.-P., Carvalhais, N., Migliavacca, M. Drivers of spatio-temporal variability of carbon dioxide and energy fluxes in a Mediterranean savanna ecosystem (2018) Agricultural and Forest Meteorology, 262, pp. 258-278, DOI: 10.1016/j.agrformet.2018.07.010
  • Fernández‐Quintanilla C, Peña JM, Andújar D, Dorado J, Ribeiro A, López‐Granados F (2018) Is the current state of the art of weed monitoring suitable for site-specific weed management in arable crops? Weed Research 58, 259–272. https://doi:10.1111/wre.12307
  • Fernández‐Quintanilla C, Peña JM, Andújar D, Dorado J, Ribeiro A, López‐Granados F (2018) Últimos avances en tecnologías para la gestión localizada de las malas hierbas. Phytoma España 303: 40–45.
  • Jiménez Brenes FM, de Castro AI, Torres Sánchez J, Peña JM, López Granados F (2018) Detección temprana de malas hierbas dentro y fuera de la línea de cultivo utilizando imágenes UAV y procedimientos automatizados de análisis. Tierras 264: 22–27.
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