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Estimation of Actual Crop Coefficients Using Remotely Sensed Vegetation Indices and Soil Water Balance Modelled Data.

, , , , and . Remote Sensing, 7 (3): 2373-2400 (2015)

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Phenology parameter extraction from time-series of satellite vegetation index data using phenosat., , and . IGARSS, page 4926-4929. IEEE, (2012)Evaluation of satellite image segmentation using synthetic images., , and . IGARSS, page 2210-2213. IEEE, (2010)QPhenoMetrics: An open source software application to assess vegetation phenology metrics., , , , and . Comput. Electron. Agric., (2018)Hyperspectral-based predictive modelling of grapevine water status in the Portuguese Douro wine region., , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2017)Retrieval of Maize Leaf Area Index Using Hyperspectral and Multispectral Data., , and . Remote. Sens., 10 (12): 1942 (2018)Integrating Spectral and Textural Information for Monitoring the Growth of Pear Trees Using Optical Images from the UAV Platform., , , , , , , and . Remote. Sens., 13 (9): 1795 (2021)Estimation of Actual Crop Coefficients Using Remotely Sensed Vegetation Indices and Soil Water Balance Modelled Data., , , , and . Remote Sensing, 7 (3): 2373-2400 (2015)Estimation of Vineyard Productivity Map Considering a Cost-Effective LIDAR-Based Sensor., , , , , and . EPIA (1), volume 11804 of Lecture Notes in Computer Science, page 121-133. Springer, (2019)Evaluating the Single-Shot MultiBox Detector and YOLO Deep Learning Models for the Detection of Tomatoes in a Greenhouse., , , , , , and . Sensors, 21 (10): 3569 (2021)Tomato Detection Using Deep Learning for Robotics Application., , , , , and . EPIA, volume 12981 of Lecture Notes in Computer Science, page 27-38. Springer, (2021)