22.5.11.6.3 Orchards, Plantations, Trees as Crops

Chapter Contents (Back)
Orchards.
See also Rubber Trees, Plantations, Analysis.
See also Eucalypt Trees, Eucalyptus.
See also Olive Trees, Orchards, Diseases.
See also Citrus Trees, Orchards, Diseases.
See also Palm Trees, Oil Palms, Trees as Crops.

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Pearse, G.D.[Grant D.], Tan, A.Y.S.[Alan Y.S.], Watt, M.S.[Michael S.], Franz, M.O.[Matthias O.], Dash, J.P.[Jonathan P.],
Detecting and mapping tree seedlings in UAV imagery using convolutional neural networks and field-verified data,
PandRS(168), 2020, pp. 156-169.
Elsevier DOI 2009
Deep learning, Convolutional networks, Tree seedlings, Unmanned aerial vehicles, Forest establishment, Object detection BibRef

Tang, Z.X.[Zi-Xia], Li, M.M.[Meng-Meng], Wang, X.Q.[Xiao-Qin],
Mapping Tea Plantations from VHR Images Using OBIA and Convolutional Neural Networks,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
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Camarretta, N.[Nicolò], Harrison, P.A.[Peter A.], Lucieer, A.[Arko], Potts, B.M.[Brad M.], Davidson, N.[Neil], Hunt, M.[Mark],
From Drones to Phenotype: Using UAV-LiDAR to Detect Species and Provenance Variation in Tree Productivity and Structure,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010
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Gomez Selvaraj, M.[Michael], Vergara, A.[Alejandro], Montenegro, F.[Frank], Alonso Ruiz, H.[Henry], Safari, N.[Nancy], Raymaekers, D.[Dries], Ocimati, W.[Walter], Ntamwira, J.[Jules], Tits, L.[Laurent], Omondi, A.B.[Aman Bonaventure], Blomme, G.[Guy],
Detection of banana plants and their major diseases through aerial images and machine learning methods: A case study in DR Congo and Republic of Benin,
PandRS(169), 2020, pp. 110-124.
Elsevier DOI 2011
Artificial Intelligence, Banana detection, Deep learning, Disease detection, High-resolution satellite image, UAV images BibRef

López, R.S.[Rolando Salas], Fernández, D.G.[Darwin Gómez], López, J.O.S.[Jhonsy O. Silva], Briceño, N.B.R.[Nilton B. Rojas], Oliva, M.[Manuel], Murga, R.E.T.[Renzo E. Terrones], Trigoso, D.I.[Daniel Iliquín], Castillo, E.B.[Elgar Barboza], Gurbillón, M.Á.B.[Miguel Ángel Barrena],
Land Suitability for Coffee (Coffea arabica) Growing in Amazonas, Peru: Integrated Use of AHP, GIS and RS,
IJGI(9), No. 11, 2020, pp. xx-yy.
DOI Link 2012
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Tridawati, A.[Anggun], Wikantika, K.[Ketut], Susantoro, T.M.[Tri Muji], Harto, A.B.[Agung Budi], Darmawan, S.[Soni], Yayusman, L.F.[Lissa Fajri], Ghazali, M.F.[Mochamad Firman],
Mapping the Distribution of Coffee Plantations from Multi-Resolution, Multi-Temporal, and Multi-Sensor Data Using a Random Forest Algorithm,
RS(12), No. 23, 2020, pp. xx-yy.
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Numbisi, F.N.[Frederick N.], van Coillie, F.[Frieke],
Does Sentinel-1A Backscatter Capture the Spatial Variability in Canopy Gaps of Tropical Agroforests? A Proof-of-Concept in Cocoa Landscapes in Cameroon,
RS(12), No. 24, 2020, pp. xx-yy.
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Ellsäßer, F.[Florian], Röll, A.[Alexander], Ahongshangbam, J.[Joyson], Waite, P.A.[Pierre-André], Hendrayanto, Schuldt, B.[Bernhard], Hölscher, D.[Dirk],
Predicting Tree Sap Flux and Stomatal Conductance from Drone-Recorded Surface Temperatures in a Mixed Agroforestry System: A Machine Learning Approach,
RS(12), No. 24, 2020, pp. xx-yy.
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Das, A.C.[Animesh Chandra], Noguchi, R.[Ryozo], Ahamed, T.[Tofael],
Integrating an Expert System, GIS, and Satellite Remote Sensing to Evaluate Land Suitability for Sustainable Tea Production in Bangladesh,
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Hamrouni, Y.[Yousra], Paillassa, E.[Eric], Chéret, V.[Véronique], Monteil, C.[Claude], Sheeren, D.[David],
From local to global: A transfer learning-based approach for mapping poplar plantations at national scale using Sentinel-2,
PandRS(171), 2021, pp. 76-100.
Elsevier DOI 2012
Active learning, Domain adaptation, Poplar plantations, Spatial transfer, Large areas, Sentinel-2 BibRef

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Multi-Criteria Evaluation (MCE) Method for the Management of Woodland Plantations in Floodplain Areas,
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Detecting and Counting Orchard Trees on Unmanned Aerial Vehicle (uav)-based Images Using Entropy and Ndvi Features,
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Hamrouni, Y., Paillassa, É., Chéret, V., Monteil, C., Sheeren, D.,
Synergistic Use of Sentinel-1 and Sentinel-2 Time Series for Poplar Plantations Monitoring At Large Scale,
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DOI Link 2012
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Yandun, F., Silwal, A., Kantor, G.,
Visual 3D Reconstruction and Dynamic Simulation of Fruit Trees for Robotic Manipulation,
AgriVision20(238-247)
IEEE DOI 2008
Vegetation, Computational modeling, Robots, Solid modeling, Visualization, Heuristic algorithms BibRef

Adão, T., Pádua, L., Pinho, T.M., Hruška, J., Sousa, A., Sousa, J.J., Morais, R., Peres, E.,
Multi-purpose Chestnut Clusters Detection Using Deep Learning: A Preliminary Approach,
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Tubau Comas, A., Valente, J., Kooistra, L.,
Automatic Apple Tree Blossom Estimation From UAV Rgb Imagery,
UAV-g19(631-635).
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Zhang, C., Valente, J., Kooistra, L., Guo, L., Wang, W.,
Opportunities of UAVS in Orchard Management,
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Alves, H.M.R., Vieira, T.G.C., Volpato, M.M.L., Lacerda, M.P.C., Borém, F.M.,
Geotechnologies For The Characterization Of Specialty Coffee Environments Of Mantiqueira De Minas In Brazil,
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Alves, H.M.R., Volpato, M.M.L., Vieira, T.G.C., Maciel, D.A., Gonçalves, T.G., Dantas, M.F.,
Characterization And Spectral Monitoring Of Coffee Lands In Brazil,
ISPRS16(B8: 801-803).
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Nogueira, K.[Keiller], Schwartz, W.R.[William Robson], dos Santos, J.A.[Jefersson A.],
Coffee Crop Recognition Using Multi-scale Convolutional Neural Networks,
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Automatic Single Tree Detection in Plantations using UAV-based Photogrammetric Point clouds,
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Alves, H.M.R., Vieira, T.G.C., Souza, V.C.O., Bertoldo, M.A., Lacerda, M.P.C., Andrade, H., Bernardes, N.,
Monitoring the Relationships between Environment and Coffee Production in Agroecosytems of the State of Minas Gerais in Brazil,
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Vieira, T.G.C., Alves, H.M.R., Souza, V.C.O., Bernardes, T., Lacerda, M.P.C.,
Assessing and Mapping Changes, in Space and Time, of Coffee Lands of the State of Minas Gerais in Brazil,
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Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Olive Trees, Orchards, Diseases .


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