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        TITLE = "GYMEE: A Global Field-Scale Crop Yield and ET Mapper in Google Earth
Engine Based on Landsat, Weather, and Soil Data",
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@article{bb295302,
        AUTHOR = "Adams, T. and Bruton, R. and Ruiz, H. and Barrios Perez, I. and Selvaraj, M.G. and Hays, D.B.",
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        BIBSOURCE = "http://www.visionbib.com/bibliography/cartog927cr1.html#TT289933"}

@article{bb295303,
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        TITLE = "Improving Strawberry Yield Prediction by Integrating Ground-Based
Canopy Images in Modeling Approaches",
        JOURNAL = IJGI,
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        NUMBER = "4",
        PAGES = "xx-yy",
        BIBSOURCE = "http://www.visionbib.com/bibliography/cartog927cr1.html#TT289934"}

@article{bb295304,
        AUTHOR = "Varela, S. and Pederson, T. and Bernacchi, C.J. and Leakey, A.D.B.",
        TITLE = "Understanding Growth Dynamics and Yield Prediction of Sorghum Using
High Temporal Resolution UAV Imagery Time Series and Machine Learning",
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        NUMBER = "9",
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        BIBSOURCE = "http://www.visionbib.com/bibliography/cartog927cr1.html#TT289935"}

@article{bb295305,
        AUTHOR = "Kwak, G.H. and Park, C.W. and Lee, K.D. and Na, S.I. and Ahn, H.Y. and Park, N.W.",
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        NUMBER = "9",
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        BIBSOURCE = "http://www.visionbib.com/bibliography/cartog927cr1.html#TT289936"}

@article{bb295306,
        AUTHOR = "Abdelbaki, A. and Schlerf, M. and Retzlaff, R. and Machwitz, M. and Verrelst, J. and Udelhoven, T.",
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Hyperspectral Imaging",
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        NUMBER = "9",
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        BIBSOURCE = "http://www.visionbib.com/bibliography/cartog927cr1.html#TT289937"}

@article{bb295307,
        AUTHOR = "Janousek, J. and Jambor, V. and Marcon, P. and Dohnal, P. and Synkova, H. and Fiala, P.",
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Vegetation Indices and Chemical Analysis of Agricultural Crops",
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        NUMBER = "10",
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        BIBSOURCE = "http://www.visionbib.com/bibliography/cartog927cr1.html#TT289938"}

@article{bb295308,
        AUTHOR = "Zhu, X.F. and Guo, R. and Liu, T.T. and Xu, K.",
        TITLE = "Crop Yield Prediction Based on Agrometeorological Indexes and Remote
Sensing Data",
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        BIBSOURCE = "http://www.visionbib.com/bibliography/cartog927cr1.html#TT289939"}

@article{bb295309,
        AUTHOR = "Chancia, R. and van Aardt, J. and Pethybridge, S. and Cross, D. and Henderson, J.",
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@article{bb295310,
        AUTHOR = "Saif, M.S. and Chancia, R. and Pethybridge, S. and Murphy, S.P. and Hassanzadeh, A. and van Aardt, J.",
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Features from Hyperspectral UAS Imagery",
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@article{bb295311,
        AUTHOR = "Quemada, C. and Perez Escudero, J.M. and Gonzalo, R. and Ederra, I. and Santesteban, L.G. and Torres, N. and Iriarte, J.C.",
        TITLE = "Remote Sensing for Plant Water Content Monitoring: A Review",
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@article{bb295312,
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Modified YOLOv3",
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@article{bb295313,
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Gap-Filling of Landsat NDVI",
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@article{bb295314,
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        TITLE = "Mapping the Location and Extent of 2019 Prevent Planting Acres in
South Dakota Using Remote Sensing Techniques",
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@article{bb295315,
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Multi-Spectral Remote Sensing and Deep Learning",
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@article{bb295316,
        AUTHOR = "Fang, P. and Yan, N. and Wei, P.P. and Zhao, Y.F. and Zhang, X.",
        TITLE = "Aboveground Biomass Mapping of Crops Supported by Improved CASA Model
and Sentinel-2 Multispectral Imagery",
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@article{bb295317,
        AUTHOR = "KC, K. and Zhao, K. and Romanko, M. and Khanal, S.",
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Remote Sensing",
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@article{bb295318,
        AUTHOR = "Padial Iglesias, M. and Serra, P. and Ninyerola, M. and Pons, X.",
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Higher Accuracy in Land Cover Maps",
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@article{bb295319,
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@article{bb295320,
        AUTHOR = "Zhao, H.W. and Duan, S. and Liu, J. and Sun, L. and Reymondin, L.",
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@article{bb295321,
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Leaf Area Index",
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@article{bb295322,
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@article{bb295323,
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        TITLE = "Predicting Days to Maturity, Plant Height, and Grain Yield in
Soybean: A Machine and Deep Learning Approach Using Multispectral
Data",
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@article{bb295324,
        AUTHOR = "Fan, J.L. and Defourny, P. and Zhang, X.Y. and Dong, Q.H. and Wang, L.M. and Qin, Z.H. and de Vroey, M. and Zhao, C.L.",
        TITLE = "Crop Mapping with Combined Use of European and Chinese Satellite Data",
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@article{bb295325,
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from Satellite Time Series",
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@article{bb295326,
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        TITLE = "USA Crop Yield Estimation with MODIS NDVI: Are Remotely Sensed Models
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@article{bb295327,
        AUTHOR = "Aneece, I. and Thenkabail, P.S.",
        TITLE = "Classifying Crop Types Using Two Generations of Hyperspectral Sensors
(Hyperion and DESIS) with Machine Learning on the Cloud",
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@article{bb295328,
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        TITLE = "Evaluating the Farmland Use Intensity and Its Patterns in a Farming:
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        NUMBER = "21",
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        BIBSOURCE = "http://www.visionbib.com/bibliography/cartog927cr1.html#TT289959"}

@article{bb295329,
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        TITLE = "Domain-Guided Machine Learning for Remotely Sensed In-Season Crop
Growth Estimation",
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        BIBSOURCE = "http://www.visionbib.com/bibliography/cartog927cr1.html#TT289960"}

@article{bb295330,
        AUTHOR = "Azzari, G. and Jain, S. and Jeffries, G. and Kilic, T. and Murray, S.",
        TITLE = "Understanding the Requirements for Surveys to Support Satellite-Based
Crop Type Mapping: Evidence from Sub-Saharan Africa",
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@article{bb295331,
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A Pilot Study Using Simulated Canopies and Field Measurement Testbeds",
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@article{bb295332,
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a Mechanistic Photosynthetic Model",
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@article{bb295333,
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        BIBSOURCE = "http://www.visionbib.com/bibliography/cartog927cr1.html#TT289964"}

@article{bb295334,
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precise crop classification based on UAV-borne H2 imagery",
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@article{bb295335,
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Variability on Irrigated and Rainfed Fields Applying Linear Models
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@article{bb295336,
        AUTHOR = "Li, M.Y. and Zhang, R. and Luo, H.X. and Gu, S.W. and Qin, Z.L.",
        TITLE = "Crop Mapping in the Sanjiang Plain Using an Improved Object-Oriented
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@article{bb295337,
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@article{bb295338,
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        NUMBER = "5",
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@article{bb295339,
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@article{bb295340,
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Detecting Submerged Kelp Canopy",
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@article{bb295341,
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@article{bb295342,
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@article{bb295343,
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@article{bb295344,
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@article{bb295345,
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Learning Classifiers Based on Spectral, Textural and Environmental
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@article{bb295346,
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UAV-Manned Hyperspectral Imagery",
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@article{bb295347,
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UAV-Manned Hyperspectral Imagery",
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@article{bb295348,
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@article{bb295351,
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Multispectral Images and Vegetation Indices",
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@article{bb295352,
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@article{bb295353,
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        TITLE = "A Meta-Analysis of Remote Sensing Technologies and Methodologies for
Crop Characterization",
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@article{bb295354,
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@article{bb295355,
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@article{bb295356,
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@article{bb295357,
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@article{bb295358,
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@article{bb295359,
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Functional Characteristics of Vegetation Canopy",
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@article{bb295361,
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Polarization Extension",
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@article{bb295362,
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@article{bb295363,
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Map-Reference Cover Type Transition Probabilities",
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@article{bb295365,
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@article{bb295366,
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        TITLE = "Remote Sensing Crop Recognition by Coupling Phenological Features and
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@article{bb295367,
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@article{bb295368,
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@article{bb295369,
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@article{bb295370,
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@article{bb295371,
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@article{bb295375,
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@article{bb295376,
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@article{bb295377,
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@article{bb295378,
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@article{bb295381,
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Vegetation Indices from Pleiades Imagery for Yield Estimation",
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Assimilating Remote Sensing Data: Implications for Small-Scale
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@article{bb295384,
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@article{bb295385,
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crop foliar nutrients in cranberries",
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@article{bb295386,
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Textural Indexes Considering Spatial Heterogeneity",
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@article{bb295389,
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