24.4.13.7 Orchards, Plantations, Trees as Crops

Geng, J., Chen, J.M., Fan, W., Tu, L., Tian, Q., Yang, R., Yang, Y., Wang, L., Lv, C., Wu, S.,
GOFP: A Geometric-Optical Model for Forest Plantations,
GeoRS(55), No. 9, September 2017, pp. 5230-5241.
IEEE DOI 1709
vegetation, vegetation mapping, 3-D canopy visualization technique, Moderate Resolution Imaging Spectroradiometer surface reflectance, Neyman model, Poisson model, bidirectional reflectance distribution function, bidirectional reflectance factor, forest plantations, hypergeometric model, natural forest canopies, BibRef

Robson, A.[Andrew], Rahman, M.M.[Muhammad Moshiur], Muir, J.[Jasmine],
Using Worldview Satellite Imagery to Map Yield in Avocado (Persea americana): A Case Study in Bundaberg, Australia,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802
BibRef

Salgadoe, A.S.A.[Arachchige Surantha Ashan], Robson, A.J.[Andrew James], Lamb, D.W.[David William], Dann, E.K.[Elizabeth Kathryn], Searle, C.[Christopher],
Quantifying the Severity of Phytophthora Root Rot Disease in Avocado Trees Using Image Analysis,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Johansen, K.[Kasper], Raharjo, T.[Tri], McCabe, M.F.[Matthew F.],
Using Multi-Spectral UAV Imagery to Extract Tree Crop Structural Properties and Assess Pruning Effects,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Yang, Z.Q.[Zhi-Qi], Dong, J.W.[Jin-Wei], Qin, Y.W.[Yuan-Wei], Ni, W.J.[Wen-Jian], Zhao, G.S.[Guo-Song], Chen, W.[Wei], Chen, B.Q.[Bang-Qian], Kou, W.L.[Wei-Li], Wang, J.[Jie], Xiao, X.M.[Xiang-Ming],
Integrated Analyses of PALSAR and Landsat Imagery Reveal More Agroforests in a Typical Agricultural Production Region, North China Plain,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810
BibRef

Iizuka, K.[Kotaro], Watanabe, K.[Kazuo], Kato, T.[Tsuyoshi], Putri, N.A.[Niken Andika], Silsigia, S.[Sisva], Kameoka, T.[Taishin], Kozan, O.[Osamu],
Visualizing the Spatiotemporal Trends of Thermal Characteristics in a Peatland Plantation Forest in Indonesia: Pilot Test Using Unmanned Aerial Systems (UASs),
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810
BibRef

Sarron, J.[Julien], Malézieux, É.[Éric], Sané, C.A.B.[Cheikh Amet Bassirou], Faye, É.[Émile],
Mango Yield Mapping at the Orchard Scale Based on Tree Structure and Land Cover Assessed by UAV,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Rahman, M.M.[Muhammad Moshiur], Robson, A.[Andrew], Bristow, M.[Mila],
Exploring the Potential of High Resolution WorldView-3 Imagery for Estimating Yield of Mango,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
BibRef

She, Y.[Ying], Ehsani, R.[Reza], Robbins, J.[James], Leiva, J.N.[Josué Nahún], Owen, J.[Jim],
Applications of High-Resolution Imaging for Open Field Container Nursery Counting,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Salgadoe, A.S.A.[Arachchige Surantha Ashan], Robson, A.J.[Andrew James], Lamb, D.W.[David William], Schneider, D.[Derek],
A Non-Reference Temperature Histogram Method for Determining Tc from Ground-Based Thermal Imagery of Orchard Tree Canopies,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Aubard, V.[Valentine], Paulo, J.A.[Joana Amaral], Silva, J.M.N.[João M. N.],
Long-Term Monitoring of Cork and Holm Oak Stands Productivity in Portugal with Landsat Imagery,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link 1903
BibRef

de Luca, G.[Giandomenico], Silva, J.M.N.[João M. N.], Cerasoli, S.[Sofia], Araújo, J.[João], Campos, J.[José], di Fazio, S.[Salvatore], Modica, G.[Giuseppe],
Object-Based Land Cover Classification of Cork Oak Woodlands using UAV Imagery and Orfeo ToolBox,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Poortinga, A.[Ate], Tenneson, K.[Karis], Shapiro, A.[Aurélie], Nquyen, Q.[Quyen], Aung, K.S.[Khun San], Chishtie, F.[Farrukh], Saah, D.[David],
Mapping Plantations in Myanmar by Fusing Landsat-8, Sentinel-2 and Sentinel-1 Data along with Systematic Error Quantification,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904
BibRef

Romero-Trigueros, C.[Cristina], Gambín, J.M.B.[José María Bayona], Tortosa, P.A.N.[Pedro Antonio Nortes], Cabañero, J.J.A.[Juan José Alarcón], Nicolás, E.N.[Emilio Nicolás],
Determination of Crop Water Stress Index by Infrared Thermometry in Grapefruit Trees Irrigated with Saline Reclaimed Water Combined with Deficit Irrigation,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904
BibRef

Marques, P.[Pedro], Pádua, L.[Luís], Adão, T.[Telmo], Hruška, J.[Jonáš], Peres, E.[Emanuel], Sousa, A.[António], Sousa, J.J.[Joaquim J.],
UAV-Based Automatic Detection and Monitoring of Chestnut Trees,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904
BibRef

Pádua, L.[Luís], Marques, P.[Pedro], Martins, L.[Luís], Sousa, A.[António], Peres, E.[Emanuel], Sousa, J.J.[Joaquim J.],
Monitoring of Chestnut Trees Using Machine Learning Techniques Applied to UAV-Based Multispectral Data,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Pique, G.[Gaétan], Fieuzal, R.[Rémy], Debaeke, P.[Philippe], Al Bitar, A.[Ahmad], Tallec, T.[Tiphaine], Ceschia, E.[Eric],
Combining High-Resolution Remote Sensing Products with a Crop Model to Estimate Carbon and Water Budget Components: Application to Sunflower,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Numbisi, F.N.[Frederick N.], van Coillie, F.M.B.[Frieke M. B.], de Wulf, R.[Robert],
Delineation of Cocoa Agroforests Using Multiseason Sentinel-1 SAR Images: A Low Grey Level Range Reduces Uncertainties in GLCM Texture-Based Mapping,
IJGI(8), No. 4, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Bai, T.C.[Tie-Cheng], Zhang, N.N.[Nan-Nan], Mercatoris, B.[Benoit], Chen, Y.Q.[You-Qi],
Improving Jujube Fruit Tree Yield Estimation at the Field Scale by Assimilating a Single Landsat Remotely-Sensed LAI into the WOFOST Model,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Fuentes-Pacheco, J.[Jorge], Torres-Olivares, J.[Juan], Roman-Rangel, E.[Edgar], Cervantes, S.[Salvador], Juarez-Lopez, P.[Porfirio], Hermosillo-Valadez, J.[Jorge], Rendón-Mancha, J.M.[Juan Manuel],
Fig Plant Segmentation from Aerial Images Using a Deep Convolutional Encoder-Decoder Network,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Iizuka, K.[Kotaro], Kato, T.[Tsuyoshi], Silsigia, S.[Sisva], Soufiningrum, A.Y.[Alifia Yuni], Kozan, O.[Osamu],
Estimating and Examining the Sensitivity of Different Vegetation Indices to Fractions of Vegetation Cover at Different Scaling Grids for Early Stage Acacia Plantation Forests Using a Fixed-Wing UAS,
RS(11), No. 15, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Hariharan, J.[Jeanette], Fuller, J.[John], Ampatzidis, Y.F.[Yi-Fannis], Abdulridha, J.[Jaafar], Lerwill, A.[Andrew],
Finite Difference Analysis and Bivariate Correlation of Hyperspectral Data for Detecting Laurel Wilt Disease and Nutritional Deficiency in Avocado,
RS(11), No. 15, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Marchetti, F.[Francesca], Waske, B.[Björn], Arbelo, M.[Manuel], Moreno-Ruíz, J.A.[Jose A.], Alonso-Benito, A.[Alfonso],
Mapping Chestnut Stands Using Bi-Temporal VHR Data,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link 1911
BibRef

Navarro, A.[Ana], Catalao, J.[Joao], Calvao, J.[Joao],
Assessing the Use of Sentinel-2 Time Series Data for Monitoring Cork Oak Decline in Portugal,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link 1911
BibRef

Salgadoe, A.S.A.[Arachchige Surantha Ashan], Robson, A.J.[Andrew James], Lamb, D.W.[David William], Dann, E.K.[Elizabeth Kathryn],
Assessment of Canopy Porosity in Avocado Trees as a Surrogate for Restricted Transpiration Emanating from Phytophthora Root Rot,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Lottering, R.T.[Romano Trent], Govender, M.[Mackyla], Peerbhay, K.[Kabir], Lottering, S.[Shenelle],
Comparing partial least squares (PLS) discriminant analysis and sparse PLS discriminant analysis in detecting and mapping Solanum mauritianum in commercial forest plantations using image texture,
PandRS(159), 2020, pp. 271-280.
Elsevier DOI 1912
Image texture, PLS-DA, SPLS-DA BibRef

Dong, X.Y.[Xin-Yu], Zhang, Z.C.[Zhi-Chao], Yu, R.Y.[Rui-Yang], Tian, Q.J.[Qing-Jiu], Zhu, X.[Xicun],
Extraction of Information about Individual Trees from High-Spatial-Resolution UAV-Acquired Images of an Orchard,
RS(12), No. 1, 2020, pp. xx-yy.
DOI Link 2001
BibRef

Abbasi, M.[Mozhgan], Verrelst, J.[Jochem], Mirzaei, M.[Mohsen], Marofi, S.[Safar], Bakhtiari, H.R.R.[Hamid Reza Riyahi],
Optimal Spectral Wavelengths for Discriminating Orchard Species Using Multivariate Statistical Techniques,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link 2001
BibRef

de Lima Santos, I.C.[Isabel Carolina], dos Santos, A.[Alexandre], Oumar, Z.[Zakariyyaa], Soares, M.A.[Marcus Alvarenga], Cerqueira Silva, J.C.[Július César], Zanetti, R.[Ronald], Zanuncio, J.C.[José Cola],
Remote Sensing to Detect Nests of the Leaf-Cutting Ant Atta sexdens (Hymenoptera: Formicidae) in Teak Plantations,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Jia, X.W.[Xiao-Wei], Khandelwal, A.[Ankush], Carlson, K.M.[Kimberly M.], Gerber, J.S.[James S.], West, P.C.[Paul C.], Samberg, L.H.[Leah H.], Kumar, V.[Vipin],
Automated Plantation Mapping in Southeast Asia Using MODIS Data and Imperfect Visual Annotations,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Cheng, Z.Z.[Zhen-Zhen], Qi, L.J.[Li-Jun], Cheng, Y.F.[Yi-Fan], Wu, Y.[Yalei], Zhang, H.[Hao],
Interlacing Orchard Canopy Separation and Assessment using UAV Images,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Ye, H.C.[Hui-Chun], Huang, W.J.[Wen-Jiang], Huang, S.Y.[Shan-Yu], Cui, B.[Bei], Dong, Y.Y.[Ying-Ying], Guo, A.[Anting], Ren, Y.[Yu], Jin, Y.[Yu],
Recognition of Banana Fusarium Wilt Based on UAV Remote Sensing,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Yrttimaa, T.[Tuomas], Saarinen, N.[Ninni], Kankare, V.[Ville], Viljanen, N.[Niko], Hynynen, J.[Jari], Huuskonen, S.[Saija], Holopainen, M.[Markus], Hyyppä, J.[Juha], Honkavaara, E.[Eija], Vastaranta, M.[Mikko],
Multisensorial Close-Range Sensing Generates Benefits for Characterization of Managed Scots Pine (Pinus sylvestris L.) Stands,
IJGI(9), No. 5, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Wu, D.[Dan], Johansen, K.[Kasper], Phinn, S.[Stuart], Robson, A.[Andrew],
Suitability of Airborne and Terrestrial Laser Scanning for Mapping Tree Crop Structural Metrics for Improved Orchard Management,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Johansen, K.[Kasper], Duan, Q.B.[Qi-Bin], Tu, Y.H.[Yu-Hsuan], Searle, C.[Chris], Wu, D.[Dan], Phinn, S.[Stuart], Robson, A.[Andrew], McCabe, M.F.[Matthew F.],
Mapping the condition of macadamia tree crops using multi-spectral UAV and WorldView-3 imagery,
PandRS(165), 2020, pp. 28-40.
Elsevier DOI 2006
UAV, WorldView-3, High spatial resolution, Macadamia, Tree condition, Random forest BibRef

Brinkhoff, J.[James], Robson, A.J.[Andrew J.],
Macadamia Orchard Planting Year and Area Estimation at a National Scale,
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link 2007
BibRef

Alonso, L.[Laura], Picos, J.[Juan], Bastos, G.[Guillermo], Armesto, J.[Julia],
Detection of Very Small Tree Plantations and Tree-Level Characterization Using Open-Access Remote-Sensing Databases,
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link 2007
BibRef

Blanco, V.[Víctor], Blaya-Ros, P.J.[Pedro José], Castillo, C.[Cristina], Soto-Vallés, F.[Fulgencio], Torres-Sánchez, R.[Roque], Domingo, R.[Rafael],
Potential of UAS-Based Remote Sensing for Estimating Tree Water Status and Yield in Sweet Cherry Trees,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link 2008
BibRef

o Sinha, P.[Priyakant], Robson, A.[Andrew], Schneider, D.[Derek], Kilic, T.[Talip], Mugera, H.K.[Harriet Kasidi], Ilukor, J.[John], Tindamanyire, J.M.[Jimmy Moses],
The potential of in-situ hyperspectral remote sensing for differentiating 12 banana genotypes grown in Uganda,
PandRS(167), 2020, pp. 85-103.
Elsevier DOI 2008
Banana, Hyperspectral remote sensing, Prediction modelling, Agriculture productivity, Survey design BibRef

Sarabia, R.[Ricardo], Aquino, A.[Arturo], Ponce, J.M.[Juan Manuel], López, G.[Gilberto], Andújar, J.M.[José Manuel],
Automated Identification of Crop Tree Crowns from UAV Multispectral Imagery by Means of Morphological Image Analysis,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link 2003
BibRef

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

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
BibRef

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

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.
DOI Link 2012
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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.
DOI Link 2012
BibRef

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

Tzioutzios, C.[Christos], Kastridis, A.[Aristeidis],
Multi-Criteria Evaluation (MCE) Method for the Management of Woodland Plantations in Floodplain Areas,
IJGI(9), No. 12, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Mahajan, G.R.[Gopal Ramdas], Das, B.[Bappa], Murgaokar, D.[Dayesh], Herrmann, I.[Ittai], Berger, K.[Katja], Sahoo, R.N.[Rabi N.], Patel, K.[Kiran], Desai, A.[Ashwini], Morajkar, S.[Shaiesh], Kulkarni, R.M.[Rahul M.],
Monitoring the Foliar Nutrients Status of Mango Using Spectroscopy-Based Spectral Indices and PLSR-Combined Machine Learning Models,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Liu, M.X.[Ming-Xing], Liu, J.H.[Jian-Hong], Atzberger, C.[Clement], Jiang, Y.[Ya], Ma, M.[Minfei], Wang, X.M.[Xun-Mei],
Zanthoxylum bungeanum Maxim mapping with multi-temporal Sentinel-2 images: The importance of different features and consistency of results,
PandRS(174), 2021, pp. 68-86.
Elsevier DOI 2103
Random forest classifier, Sentinel-2, Vegetation indices, Topographic variables, Importance analysis BibRef

Wang, J.[Jie], Shi, X.J.[Xiao-Jun], Xu, Y.C.[Yang-Chun], Dong, C.X.[Cai-Xia],
Nitrogen Management Based on Visible/Near Infrared Spectroscopy in Pear Orchards,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Guo, Y.H.[Ya-Hui], Chen, S. .Z.[Shou- Zhi], Wu, Z.F.[Zhao-Fei], Wang, S.X.[Shu-Xin], Bryant, C.R.[Christopher Robin], Senthilnath, J.[Jayavelu], Cunha, M.[Mario], Fu, Y.H.[Yongshuo H.],
Integrating Spectral and Textural Information for Monitoring the Growth of Pear Trees Using Optical Images from the UAV Platform,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Jabs-Sobocinska, Z.[Zofia], Affek, A.N.[Andrzej N.], Ewiak, I.[Ireneusz], Nita, M.D.[Mihai Daniel],
Mapping Mature Post-Agricultural Forests in the Polish Eastern Carpathians with Archival Remote Sensing Data,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Yang, Z.Q.[Zhi-Qi], Dong, J.[Jinwei], Kou, W.L.[Wei-Li], Qin, Y.W.[Yuan-Wei], Xiao, X.M.[Xiang-Ming],
Mapping Panax Notoginseng Plantations by Using an Integrated Pixel- and Object-Based (IPOB) Approach and ZY-3 Imagery,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Aeberli, A.[Aaron], Johansen, K.[Kasper], Robson, A.[Andrew], Lamb, D.W.[David W.], Phinn, S.[Stuart],
Detection of Banana Plants Using Multi-Temporal Multispectral UAV Imagery,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Aeberli, A.[Aaron], Phinn, S.[Stuart], Johansen, K.[Kasper], Robson, A.[Andrew], Lamb, D.W.[David W.],
Characterisation of Banana Plant Growth Using High-Spatiotemporal-Resolution Multispectral UAV Imagery,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Gorgoso-Varela, J.J.[J. Javier], Ponce, R.A.[Rafael Alonso], Rodríguez-Puerta, F.[Francisco],
Modeling Diameter Distributions with Six Probability Density Functions in Pinus halepensis Mill. Plantations Using Low-Density Airborne Laser Scanning Data in Aragón (Northeast Spain),
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Park, S.Y.[Su-Young], Ryu, D.[Dongryeol], Fuentes, S.[Sigfredo], Chung, H.[Hoam], O'Connell, M.[Mark], Kim, J.C.[Jun-Chul],
Dependence of CWSI-Based Plant Water Stress Estimation with Diurnal Acquisition Times in a Nectarine Orchard,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Lian, Y.N.[Yi-Ning], Feng, Z.K.[Zhong-Ke], Huai, Y.J.[Yong-Jian], Lu, H.[Hao], Chen, S.L.[Shi-Lin], Li, N.[Niwen],
Terrestrial Videogrammetry for Deriving Key Forest Inventory Data: A Case Study in Plantation,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Malhi, R.K.M.[Ramandeep Kaur M.], Kiran, G.S.[G. Sandhya], Shah, M.N.[Mangala N.], Mistry, N.V.[Nirav V.], Bhavsar, V.H.[Viral H.], Singh, C.P.[Chandra Prakash], Bhattarcharya, B.K.[Bimal Kumar], Townsend, P.A.[Philip A.], Mohan, S.[Shiv],
Applicability of Smoothing Techniques in Generation of Phenological Metrics of Tectona grandis L. Using NDVI Time Series Data,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
Teak trees. BibRef

Esteban, J.[Jessica], Fernández-Landa, A.[Alfredo], Tomé, J.L.[José Luis], Gómez, C.[Cristina], Marchamalo, M.[Miguel],
Identification of Silvicultural Practices in Mediterranean Forests Integrating Landsat Time Series and a Single Coverage of ALS Data,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Mo, J.W.[Jia-Wei], Lan, Y.[Yubin], Yang, D.Z.[Dong-Zi], Wen, F.[Fei], Qiu, H.B.[Hong-Bin], Chen, X.[Xin], Deng, X.L.[Xiao-Ling],
Deep Learning-Based Instance Segmentation Method of Litchi Canopy from UAV-Acquired Images,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Guo, X.Z.[Xu-Zhan], Liu, Q.W.[Qing-Wang], Sharma, R.P.[Ram P.], Chen, Q.[Qiao], Ye, Q.L.[Qiao-Lin], Tang, S.Z.[Shou-Zheng], Fu, L.Y.[Li-Yong],
Tree Recognition on the Plantation Using UAV Images with Ultrahigh Spatial Resolution in a Complex Environment,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Kilwenge, R.[Regina], Adewopo, J.[Julius], Sun, Z.L.[Zhan-Li], Schut, M.[Marc],
UAV-Based Mapping of Banana Land Area for Village-Level Decision-Support in Rwanda,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Chung, C.H.[Chih-Hsin], Wang, J.[Jonathan], Deng, S.L.[Shu-Lin], Huang, C.Y.[Cho-Ying],
Analysis of Canopy Gaps of Coastal Broadleaf Forest Plantations in Northeast Taiwan Using UAV Lidar and the Weibull Distribution,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Yin, S.Y.[Shi-Yun], Zhou, K.[Kai], Cao, L.[Lin], Shen, X.[Xin],
Estimating the Horizontal and Vertical Distributions of Pigments in Canopies of Ginkgo Plantation Based on UAV-Borne LiDAR, Hyperspectral Data by Coupling PROSAIL Model,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Meng, Y.Y.[Yuan-Yuan], Wei, C.Y.[Cai-Yong], Guo, Y.P.[Yan-Pei], Tang, Z.Y.[Zhi-Yao],
A Planted Forest Mapping Method Based on Long-Term Change Trend Features Derived from Dense Landsat Time Series in an Ecological Restoration Region,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Zhang, Y.M.[You-Ming], Ta, N.[Na], Guo, S.[Song], Chen, Q.[Qian], Zhao, L.C.[Long-Cai], Li, F.L.[Fen-Ling], Chang, Q.R.[Qing-Rui],
Combining Spectral and Textural Information from UAV RGB Images for Leaf Area Index Monitoring in Kiwifruit Orchard,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Zhang, S.M.[Shi-Min], Li, X.H.[Xiu-Hua], Ba, Y.X.[Yu-Xuan], Lyu, X.G.[Xue-Gang], Zhang, M.Q.[Mu-Qing], Li, M.Z.[Min-Zan],
Banana Fusarium Wilt Disease Detection by Supervised and Unsupervised Methods from UAV-Based Multispectral Imagery,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

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Parcel-Level Mapping of Horticultural Crop Orchards in Complex Mountain Areas Using VHR and Time-Series Images,
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An Integration of Linear Model and 'Random Forest' Techniques for Prediction of Norway Spruce Vitality: A Case Study of the Hemiboreal Forest, Latvia,
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Comparing Different Light Use Efficiency Models to Estimate the Gross Primary Productivity of a Cork Oak Plantation in Northern China,
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Remote Sensing Imaging as a Tool to Support Mulberry Cultivation for Silk Production,
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A Novel Technique Using Planar Area and Ground Shadows Calculated from UAV RGB Imagery to Estimate Pistachio Tree (Pistacia vera L.) Canopy Volume,
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Accuracy Evaluation and Branch Detection Method of 3D Modeling Using Backpack 3D Lidar SLAM and UAV-SfM for Peach Trees during the Pruning Period in Winter,
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Geometrical Characterization of Hazelnut Trees in an Intensive Orchard by an Unmanned Aerial Vehicle (UAV) for Precision Agriculture Applications,
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Zhu, S.[Shidan], Cui, N.[Ningbo], Zhou, J.[Ji], Xue, J.Y.[Jing-Yuan], Wang, Z.H.[Zhi-Hui], Wu, Z.[Zongjun], Wang, M.J.[Ming-Jun], Deng, Q.L.[Qing-Ling],
Digital Mapping of Root-Zone Soil Moisture Using UAV-Based Multispectral Data in a Kiwifruit Orchard of Northwest China,
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How Sensitive Is Thermal Image-Based Orchard Water Status Estimation to Canopy Extraction Quality?,
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Raman, M.G.[Mugilan Govindasamy], Marzougui, A.[Afef], Teh, S.L.[Soon Li], York, Z.B.[Zara B.], Evans, K.M.[Kate M.], Sankaran, S.[Sindhuja],
Rapid Assessment of Architectural Traits in Pear Rootstock Breeding Program Using Remote Sensing Techniques,
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Lara-Gómez, M.Á.[Miguel Ángel], Navarro-Cerrillo, R.M.[Rafael M.], Rumbao, I.C.[Inmaculada Clavero], Palacios-Rodríguez, G.[Guillermo],
Comparison of Errors Produced by ABA and ITC Methods for the Estimation of Forest Inventory Attributes at Stand and Tree Level in Pinus radiata Plantations in Chile,
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Peng, Y.[Yan], He, G.J.[Guo-Jin], Wang, G.Z.[Gui-Zhou], Zhang, Z.M.[Zhao-Ming],
Large-Scale Populus euphratica Distribution Mapping Using Time-Series Sentinel-1/2 Data in Google Earth Engine,
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Wu, C.X.[Chun-Xiao], Jia, W.[Wei], Yang, J.Y.[Jian-Yu], Zhang, T.T.[Ting-Ting], Dai, A.[Anjin], Zhou, H.[Han],
Economic Fruit Forest Classification Based on Improved U-Net Model in UAV Multispectral Imagery,
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DOI Link 2306
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Yin, Y.[Yihan], Liu, G.[Gang], Li, S.[Shanle], Zheng, Z.Y.[Zhi-Yuan], Si, Y.S.[Yong-Sheng], Wang, Y.[Yang],
A Method for Predicting Canopy Light Distribution in Cherry Trees Based on Fused Point Cloud Data,
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Hapuarachchi, N.S.[Nimanie S.], Trueman, S.J.[Stephen J.], Kämper, W.[Wiebke], Farrar, M.B.[Michael B.], Wallace, H.M.[Helen M.], Nichols, J.[Joel], Bai, S.H.[Shahla Hosseini],
Hyperspectral Imaging of Adaxial and Abaxial Leaf Surfaces for Rapid Assessment of Foliar Nutrient Concentrations in Hass Avocado,
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Torgbor, B.A.[Benjamin Adjah], Rahman, M.M.[Muhammad Moshiur], Brinkhoff, J.[James], Sinha, P.[Priyakant], Robson, A.[Andrew],
Integrating Remote Sensing and Weather Variables for Mango Yield Prediction Using a Machine Learning Approach,
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Sun, Z.B.[Zhi-Bin], Jiang, X.Y.[Xin-Yue], Tang, X.H.[Xue-Hai], Yan, L.P.[Li-Peng], Kuang, F.[Fan], Li, X.Z.[Xiao-Zhou], Dou, M.[Min], Wang, B.[Bin], Gao, X.[Xiang],
Identifying Core Wavelengths of Oil Tree's Hyperspectral Data by Taylor Expansion,
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Amantai, N.[Nigenare], Meng, Y.Y.[Yuan-Yuan], Song, S.S.[Shan-Shan], Li, Z.[Zihui], Hou, B.[Bowen], Tang, Z.Y.[Zhi-Yao],
Spatial-Temporal Patterns of Interannual Variability in Planted Forests: NPP Time-Series Analysis on the Loess Plateau,
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DOI Link 2307
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Singh, K.[Kanika], Fuentes, I.[Ignacio], Al-Shammari, D.[Dhahi], Fidelis, C.[Chris], Butubu, J.[James], Yinil, D.[David], Sharififar, A.[Amin], Minasny, B.[Budiman], Guest, D.I.[David I], Field, D.J.[Damien J],
E-Agriculture Planning Tool for Supporting Smallholder Cocoa Intensification Using Remotely Sensed Data,
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DOI Link 2307
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Wu, X.[Xuehui], Luo, Z.W.[Zhi-Wei], Xu, H.[Huanliang],
Recognition of pear leaf disease under complex background based on DBPNet and modified mobilenetV2,
IET-IPR(17), No. 10, 2023, pp. 3055-3067.
DOI Link 2308
agricultural engineering, agricultural products, image recognition, image segmentation BibRef

Xiong, Z.J.[Zhang-Jun], Wang, L.[Lele], Zhao, Y.J.[Ying-Jie], Lan, Y.[Yubin],
Precision Detection of Dense Litchi Fruit in UAV Images Based on Improved YOLOv5 Model,
RS(15), No. 16, 2023, pp. 4017.
DOI Link 2309
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Sun, Y.F.[Yi-Fei], Hao, Z.B.[Zhen-Bang], Guo, Z.[Zhanbao], Liu, Z.[Zhenhu], Huang, J.X.[Jia-Xing],
Detection and Mapping of Chestnut Using Deep Learning from High-Resolution UAV-Based RGB Imagery,
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DOI Link 2310
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Li, Y.J.[Ya-Jing], Yan, E.[Enping], Jiang, J.W.[Jia-Wei], Cao, D.[Dan], Mo, D.[Dengkui],
Investigating the Identification and Spatial Distribution Characteristics of Camellia oleifera Plantations Using High-Resolution Imagery,
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DOI Link 2311
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Tsao, A.[Angela], Nzewi, I.[Ikenna], Jayeoba, A.[Ayodeji], Ayogu, U.[Uzoma], Lobell, D.B.[David B.],
Canopy Height Mapping for Plantations in Nigeria Using GEDI, Landsat, and Sentinel-2,
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DOI Link 2311
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Hashimoto, A.[Asahi], Chiu, C.W.[Chen-Wei], Onda, Y.[Yuichi], Tateishi, M.[Makiko], Tsuruta, K.[Kenji], Gomi, T.[Takashi],
Satellite remote sensing model for estimating canopy transpiration in cypress plantation using in situ sap flow observations and forest inventory,
PandRS(206), 2023, pp. 258-272.
Elsevier DOI 2312
Transpiration, Forest inventory, Remote sensing, Sap flow, Decoupling index BibRef

Xie, J.X.[Jia-Xing], Wang, J.X.[Jia-Xin], Chen, Y.F.[Yu-Feng], Gao, P.[Peng], Yin, H.[Huili], Chen, S.[Shiyun], Sun, D.Z.[Dao-Zong], Wang, W.X.[Wei-Xing], Mo, H.[Handong], Shen, J.Y.[Ji-Yuan], Li, J.[Jun],
Estimating the SPAD of Litchi in the Growth Period and Autumn Shoot Period Based on UAV Multi-Spectrum,
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DOI Link 2401
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Moraiti, N.[Nikoletta], Mullissa, A.[Adugna], Rahn, E.[Eric], Sassen, M.[Marieke], Reiche, J.[Johannes],
Critical Assessment of Cocoa Classification with Limited Reference Data: A Study in Cote d'Ivoire and Ghana Using Sentinel-2 and Random Forest Model,
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DOI Link 2402
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Chakhar, A.[Amal], Hernández-López, D.[David], Ballesteros, R.[Rocío], Moreno, M.A.[Miguel A.],
Irrigation Detection Using Sentinel-1 and Sentinel-2 Time Series on Fruit Tree Orchards,
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DOI Link 2402
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Heidarlou, H.B.[Hadi Beygi], Oprea-Sorescu, O.[Octavian], Marcu, M.V.[Marina Viorela], Borz, S.A.[Stelian Alexandru],
Mapping Small-Scale Willow Crops and Their Health Status Using Sentinel-2 Images in Complex Agricultural Areas,
RS(16), No. 3, 2024, pp. 595.
DOI Link 2402
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Rehman, A.U.[Arif Ur], Zhang, L.[Lifu], Sajjad, M.M.[Meer Muhammad], Raziq, A.[Abdur],
Multi-Temporal Sentinel-1 and Sentinel-2 Data for Orchards Discrimination in Khairpur District, Pakistan Using Spectral Separability Analysis and Machine Learning Classification,
RS(16), No. 4, 2024, pp. 686.
DOI Link 2402
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Lodato, F.[Francesco], Pennazza, G.[Giorgio], Santonico, M.[Marco], Vollero, L.[Luca], Grasso, S.[Simone], Pollino, M.[Maurizio],
In-Depth Analysis and Characterization of a Hazelnut Agro-Industrial Context through the Integration of Multi-Source Satellite Data: A Case Study in the Province of Viterbo, Italy,
RS(16), No. 7, 2024, pp. 1227.
DOI Link 2404
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Tawalbeh, Z.M.[Zada M.], Bawazir, A.S.[A. Salim], Fernald, A.[Alexander], Sabie, R.[Robert], Heerema, R.J.[Richard J.],
Assessing Satellite-Derived OpenET Platform Evapotranspiration of Mature Pecan Orchard in the Mesilla Valley, New Mexico,
RS(16), No. 8, 2024, pp. 1429.
DOI Link 2405
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Dixit, J.[Jitendra], Bhardwaj, A.K.[Ashok Kumar], Gupta, S.K.[Saurabh Kumar], Singh, S.K.[Suraj Kumar], Meraj, G.[Gowhar], Kumar, P.[Pankaj], Kanga, S.[Shruti], Singh, S.[Saurabh], Sajan, B.[Bhartendu],
Potential of Lightweight Drones and Object-Oriented Image Segmentation in Forest Plantation Assessment,
RS(16), No. 9, 2024, pp. 1554.
DOI Link 2405
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Zhang, W.L.[Wen-Li], Peng, X.Y.[Xin-Yu], Bai, T.T.[Ting-Ting], Wang, H.Z.[Hao-Zhou], Takata, D.[Daisuke], Guo, W.[Wei],
A UAV-Based Single-Lens Stereoscopic Photography Method for Phenotyping the Architecture Traits of Orchard Trees,
RS(16), No. 9, 2024, pp. 1570.
DOI Link 2405
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Kumar, S.S.[S. Sathish], Sigappi, A.N., Thomas, G.A.S.[G. Arun Sampaul], Robinson, Y.H.[Y. Harold], Raja, S.P.,
Classification and Analysis of Pistachio Species Through Neural Embedding-Based Feature Extraction and Small-Scale Machine Learning Techniques,
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Pan, Q.M.[Qing-Mei], Cheng, X.F.[Xiang-Fen], Hu, M.J.[Mei-Jun], Liu, L.Q.[Lin-Qi], Wang, X.[Xin], Zhang, J.S.[Jin-Song], Li, Z.P.[Zhi-Peng], Yuan, W.W.[Wen-Wen], Gao, X.[Xiang],
The Afternoon/Morning Ratio of Tower-Based Solar-Induced Chlorophyll Fluorescence Can Be Used to Monitor Drought in a Chinese Cork Oak Plantation,
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DOI Link 2406
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Guimarães, N.[Nathalie], Sousa, J.J.[Joaquim J.], Couto, P.[Pedro], Bento, A.[Albino], Pádua, L.[Luís],
Combining UAV-Based Multispectral and Thermal Infrared Data with Regression Modeling and SHAP Analysis for Predicting Stomatal Conductance in Almond Orchards,
RS(16), No. 13, 2024, pp. 2467.
DOI Link 2407
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Afsar, M.M.[Muhammad Munir], Bakhshi, A.D.[Asim Dilawar], Iqbal, M.S.[Muhammad Shahid], Hussain, E.[Ejaz], Iqbal, J.[Javed],
High-Precision Mango Orchard Mapping Using a Deep Learning Pipeline Leveraging Object Detection and Segmentation,
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Jin, J.[Jia], Wang, Q.[Quan], Zhuang, J.[Jie],
Coupling Light Intensity and Hyperspectral Reflectance Improve Estimations of the Actual Electron Transport Rate of Mango Leaves (Mangifera indica L.),
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DOI Link 2410
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Rouault, P.[Pierre], Courault, D.[Dominique], Pouget, G.[Guillaume], Flamain, F.[Fabrice], Diop, P.K.[Papa-Khaly], Desfonds, V.[Véronique], Doussan, C.[Claude], Chanzy, A.[André], Debolini, M.[Marta], McCabe, M.[Matthew], Lopez-Lozano, R.[Raul],
Phenological and Biophysical Mediterranean Orchard Assessment Using Ground-Based Methods and Sentinel 2 Data,
RS(16), No. 18, 2024, pp. 3393.
DOI Link 2410
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Xu, W.M.[Wei-Meng], Li, Z.H.[Zhen-Hong], Lin, H.[Hate], Shao, G.[Guowen], Zhao, F.[Fa], Wang, H.[Han], Cheng, J.P.[Jin-Peng], Lei, L.[Lei], Chen, R.Q.[Ri-Qiang], Han, S.Y.[Shao-Yu], Yang, H.[Hao],
Mapping Fruit-Tree Plantation Using Sentinel-1/2 Time Series Images with Multi-Index Entropy Weighting Dynamic Time Warping Method,
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Gutiérrez-Hernández, O.[Oliver], García, L.V.[Luis V.],
Robust Trend Analysis in Environmental Remote Sensing: A Case Study of Cork Oak Forest Decline,
RS(16), No. 20, 2024, pp. 3886.
DOI Link 2411
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Liu, H.[Hui], Xu, J.[Jie], Chen, W.H.[Wen-Hua], Shen, Y.[Yue], Kai, J.[Jinru],
Efficient Semantic Segmentation for Large-Scale Agricultural Nursery Managements via Point Cloud-Based Neural Network,
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Alemayehu, B.[Bireda], Suarez-Minguez, J.[Juan], Rosette, J.[Jacqueline],
The Implications of Plantation Forest-Driven Land Use/Land Cover Changes for Ecosystem Service Values in the Northwestern Highlands of Ethiopia,
RS(16), No. 22, 2024, pp. 4159.
DOI Link 2412
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Ibrahim, M.[Muhammad], Wang, H.[Haitian], Iqbal, I.A.[Irfan A.], Miao, Y.[Yumeng], Albaqami, H.[Hezam], Blom, H.[Hans], Mian, A.[Ajmal],
Forest Stem Extraction and Modeling (FoSEM): A LiDAR-Based Framework for Accurate Tree Stem Extraction and Modeling in Radiata Pine Plantations,
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DOI Link 2502
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Afsar, M.M.[Muhammad Munir], Iqbal, M.S.[Muhammad Shahid], Bakhshi, A.D.[Asim Dilawar], Hussain, E.[Ejaz], Iqbal, J.[Javed],
MangiSpectra: A Multivariate Phenological Analysis Framework Leveraging UAV Imagery and LSTM for Tree Health and Yield Estimation in Mango Orchards,
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Exploration of Data Augmentation Techniques for Bush Detection in Blueberry Orchards,
Precognition24(5674-5683)
IEEE DOI 2410
Smart agriculture, Technological innovation, Navigation, Focusing, Object detection, Data augmentation, Robustness, bush detection BibRef

Filipovic, V.[Vladan], Stefanovic, D.[Dimitrije], Pajevic, N.[Nina], Grbovic, Ž.[Željana], Djuric, N.[Nemanja], Panic, M.[Marko],
Bush Detection for Vision-based UGV Guidance in Blueberry Orchards: Data Set and Methods,
Precognition23(3646-3655)
IEEE DOI 2309
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Meyer, L.[Lukas], Gilson, A.[Andreas], Scholz, O.[Oliver], Stamminger, M.[Marc],
CherryPicker: Semantic Skeletonization and Topological Reconstruction of Cherry Trees,
AgriVision23(6244-6253)
IEEE DOI 2309
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Elmoussaoui, E., Moumni, A., Lahrouni, A.,
Cartography of Moroccan Argan Tree Using Combined Optical and Sar Imagery Integrated With Digital Elevation Model,
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Haddadi, A., Leblon, B., Patterson, G.,
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.,
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Yandun, F., Silwal, A., Kantor, G.,
Visual 3D Reconstruction and Dynamic Simulation of Fruit Trees for Robotic Manipulation,
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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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Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Olive Trees, Orchards, Diseases .

Last update:Mar 17, 2025 at 20:02:03