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2023
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2023
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Sugarcane yields prediction at the row level using a novel cross-validation approach to multi-year multispectral images
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2022
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Quantifying Hail Damage in Crops Using Sentinel-2 Imagery
Remote Sensing,
2022
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A new sugarcane yield model using the SiPAR model
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2022
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Remote Sensing,
2022
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2022 IEEE International Conference on Cybernetics and Computational Intelligence (CyberneticsCom),
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Empirical model for forecasting sugarcane yield on a local scale in Brazil using Landsat imagery and random forest algorithm
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2021
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Sugarcane Yield Mapping Using High-Resolution Imagery Data and Machine Learning Technique
Remote Sensing,
2021
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High Accuracy Pre-Harvest Sugarcane Yield Forecasting Model Utilizing Drone Image Analysis, Data Mining, and Reverse Design Method
Agriculture,
2021
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Assessing the Potential of Sentinel-2 Derived Vegetation Indices to Retrieve Phenological Stages of Mango in Ghana
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2021
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Relationship of vegetation indices and SPAD meter readings with sugarcane leaf nitrogen under Pampanga Mill District, Philippines condition
IOP Conference Series: Earth and Environmental Science,
2020
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A Satellite-Based Methodology for Harvest Date Detection and Yield Prediction in Sugarcane
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium,
2020
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Prediction of Antioxidant Activity of Cherry Fruits from UAS Multispectral Imagery Using Machine Learning
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2020
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Integrating Landsat-8 and Sentinel-2 Time Series Data for Yield Prediction of Sugarcane Crops at the Block Level
Remote Sensing,
2020
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Remote Sensing-Based Yield Forecasting for Sugarcane (Saccharum officinarum L.) Crop in India
Journal of the Indian Society of Remote Sensing,
2018
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Exploring the Potential of High Resolution WorldView-3 Imagery for Estimating Yield of Mango
Remote Sensing,
2018
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Using Worldview Satellite Imagery to Map Yield in Avocado (Persea americana): A Case Study in Bundaberg, Australia
Remote Sensing,
2017
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Using GeoEye-1 Imagery for Multi-Temporal Object-Based Detection of Canegrub Damage in Sugarcane Fields in Queensland, Australia
GIScience & Remote Sensing,
2017
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