23.4.12.6.5 Citrus Trees, Orchards, Diseases

Chapter Contents (Back)
Orchards. Citrus. Orange, lemon, lime.

Williams, D.H., Aggarwal, J.K.,
Computer Detection and Classification of Three Citrus Infestations,
CGIP(14), No. 4, December 1980, pp. 373-390.
Elsevier DOI BibRef 8012

Shrivastava, R.J.[Rahul J.], Gebelein, J.L.[Jennifer L.],
Land cover classification and economic assessment of citrus groves using remote sensing,
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Elsevier DOI 0703
Agriculture; Economy; Citrus Grove Area Estimation; Landsat BibRef

Zhang, M.[Min], Meng, Q.G.[Qing-Gang],
Automatic citrus canker detection from leaf images captured in field,
PRL(32), No. 15, 1 November 2011, pp. 2036-2046.
Elsevier DOI 1112
Citrus canker detection; Zone-based texture distribution; Classification; Hierarchical detection; Feature learning; Hue-intensity-saturation BibRef

Amoros Lopez, J., Izquierdo Verdiguier, E., Gomez Chova, L., Munoz Mari, J., Rodriguez Barreiro, J.Z., Camps Valls, G., Calpe Maravilla, J.,
Land cover classification of VHR airborne images for citrus grove identification,
PandRS(66), No. 1, January 2011, pp. 115-123.
Elsevier DOI 1101
Tree identification; Feature extraction/selection; Classification tree; Support vector machine; Artificial neural networks BibRef

Stagakis, S., González-Dugo, V., Cid, P., Guillén-Climent, M.L., Zarco-Tejada, P.J.,
Monitoring water stress and fruit quality in an orange orchard under regulated deficit irrigation using narrow-band structural and physiological remote sensing indices,
PandRS(71), No. 1, July 2012, pp. 47-61.
Elsevier DOI 1208
Water stress; Remote sensing; Narrow-band indices; Fruit quality; Regulated deficit; PRI BibRef

Jiménez-Bello, M.A., Ruiz, L.A., Hermosilla, T., Recio, J.A., Intrigliolo, D.S.,
Use of remote sensing and geographic information tools for irrigation management of citrus trees,
Other2012, pp. 147-159. In: The use of remote sensing and geographic information systems for irrigation amangement in Southwest Europe. CIHEAM.
PDF File. BibRef 1200

Recio, J.A., Hermosilla, T., Ruiz, L.A., Palomar, J.,
Automated extraction of tree and plot-based parameters in citrus orchards from aerial images,
CompElAg(90), 2013, pp. 24-34.
Elsevier DOI 1212
BibRef

Balaguer-Beser, A., Ruiz, L.A., Hermosilla, T., Recio, J.A.,
Using semivariogram indices to analyse heterogeneity in spatial patterns in remotely sensed images,
CompGosSci(50), 2013, pp. 115-127.
Elsevier DOI 1212
BibRef

Fieber, K.D.[Karolina D.], Davenport, I.J.[Ian J.], Ferryman, J.M.[James M.], Gurney, R.J.[Robert J.], Walker, J.P.[Jeffrey P.], Hacker, J.M.[Jorg M.],
Analysis of full-waveform LiDAR data for classification of an orange orchard scene,
PandRS(82), No. 1, August 2013, pp. 63-82.
Elsevier DOI 1306
Full-waveform; LiDAR; Backscattering coefficient; Classification; Reflectance; Vegetation BibRef

Colaço, A.F.[André F.], Trevisan, R.G.[Rodrigo G.], Molin, J.P.[José P.], Rosell-Polo, J.R.[Joan R.], Escolà, A.[Alexandre],
A Method to Obtain Orange Crop Geometry Information Using a Mobile Terrestrial Laser Scanner and 3D Modeling,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Richard, K.[Kyalo], Abdel-Rahman, E.M.[Elfatih M.], Mohamed, S.A.[Samira A.], Ekesi, S.[Sunday], Borgemeister, C.[Christian], Landmann, T.[Tobias],
Importance of Remotely-Sensed Vegetation Variables for Predicting the Spatial Distribution of African Citrus Triozid (Trioza erytreae) in Kenya,
IJGI(7), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Vanella, D.[Daniela], Ramírez-Cuesta, J.M.[Juan Miguel], Intrigliolo, D.S.[Diego S.], Consoli, S.[Simona],
Combining Electrical Resistivity Tomography and Satellite Images for Improving Evapotranspiration Estimates of Citrus Orchards,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Abdulridha, J.[Jaafar], Batuman, O.[Ozgur], Ampatzidis, Y.[Yiannis],
UAV-Based Remote Sensing Technique to Detect Citrus Canker Disease Utilizing Hyperspectral Imaging and Machine Learning,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Osco, L.P.[Lucas Prado], Ramos, A.P.M.[Ana Paula Marques], Pereira, D.R.[Danilo Roberto], Moriya, É.A.S.[Érika Akemi Saito], Imai, N.N.[Nilton Nobuhiro], Matsubara, E.T.[Edson Takashi], Estrabis, N.[Nayara], de Souza, M.[Maurício], Junior, J.M.[José Marcato], Gonçalves, W.N.[Wesley Nunes], Li, J.[Jonathan], Liesenberg, V.[Veraldo], Creste, J.E.[José Eduardo],
Predicting Canopy Nitrogen Content in Citrus-Trees Using Random Forest Algorithm Associated to Spectral Vegetation Indices from UAV-Imagery,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Ampatzidis, Y.[Yiannis], Partel, V.[Victor],
UAV-Based High Throughput Phenotyping in Citrus Utilizing Multispectral Imaging and Artificial Intelligence,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Osco, L.P.[Lucas Prado], dos Santos de Arruda, M.[Mauro], Junior, J.M.[José Marcato], da Silva, N.B.[Neemias Buceli], Marques Ramos, A.P.[Ana Paula], Moryia, É.A.S.[Érika Akemi Saito], Imai, N.N.[Nilton Nobuhiro], Pereira, D.R.[Danillo Roberto], Creste, J.E.[José Eduardo], Matsubara, E.T.[Edson Takashi], Li, J.[Jonathan], Gonçalves, W.N.[Wesley Nunes],
A convolutional neural network approach for counting and geolocating citrus-trees in UAV multispectral imagery,
PandRS(160), 2020, pp. 97-106.
Elsevier DOI 2001
Deep learning, Multispectral image, UAV-borne sensor, Object detection, Citrus tree counting, Orchard BibRef

Garza, B.N.[Blanca N.], Ancona, V.[Veronica], Enciso, J.[Juan], Perotto-Baldivieso, H.L.[Humberto L.], Kunta, M.[Madhurababu], Simpson, C.[Catherine],
Quantifying Citrus Tree Health Using True Color UAV Images,
RS(12), No. 1, 2020, pp. xx-yy.
DOI Link 2001
BibRef

García-Murillo, D.G.[Daniel G.], Caicedo-Acosta, J., Castellanos-Dominguez, G.,
Individual Detection of Citrus and Avocado Trees Using Extended Maxima Transform Summation on Digital Surface Models,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Deng, X.L.[Xiao-Ling], Zhu, Z.H.[Zi-Hao], Yang, J.C.[Jia-Cheng], Zheng, Z.[Zheng], Huang, Z.X.[Zi-Xiao], Yin, X.B.[Xian-Bo], Wei, S.J.[Shu-Jin], Lan, Y.B.[Yu-Bin],
Detection of Citrus Huanglongbing Based on Multi-Input Neural Network Model of UAV Hyperspectral Remote Sensing,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Chang, A.[Anjin], Yeom, J.[Junho], Jung, J.[Jinha], Landivar, J.[Juan],
Comparison of Canopy Shape and Vegetation Indices of Citrus Trees Derived from UAV Multispectral Images for Characterization of Citrus Greening Disease,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Vanella, D.[Daniela], Consoli, S.[Simona], Ramírez-Cuesta, J.M.[Juan Miguel], Tessitori, M.[Matilde],
Suitability of the MODIS-NDVI Time-Series for a Posteriori Evaluation of the Citrus Tristeza Virus Epidemic,
RS(12), No. 12, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Osco, L.P.[Lucas Prado], Ramos, A.P.M.[Ana Paula Marques], Pinheiro, M.M.F.[Mayara Maezano Faita], Moriya, É.A.S.[Érika Akemi Saito], Imai, N.N.[Nilton Nobuhiro], Estrabis, N.[Nayara], Ianczyk, F.[Felipe], de Araújo, F.F.[Fábio Fernando], Liesenberg, V.[Veraldo], de Castro Jorge, L.A.[Lúcio André], Li, J.[Jonathan], Ma, L.F.[Ling-Fei], Gonçalves, W.N.[Wesley Nunes], Marcato Junior, J.[José], Creste, J.E.[José Eduardo],
A Machine Learning Framework to Predict Nutrient Content in Valencia-Orange Leaf Hyperspectral Measurements,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link 2003
BibRef

You, J.[Jie], Lee, J.[Joonwhoan],
Offline mobile diagnosis system for citrus pests and diseases using deep compression neural network,
IET-CV(14), No. 6, September 2020, pp. 370-377.
DOI Link 2010
BibRef

Morell-Monzó, S.[Sergio], Sebastiá-Frasquet, M.T.[María-Teresa], Estornell, J.[Javier],
Land Use Classification of VHR Images for Mapping Small-Sized Abandoned Citrus Plots by Using Spectral and Textural Information,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef


Bollis, E., Pedrini, H., Avila, S.,
Weakly Supervised Learning Guided by Activation Mapping Applied to a Novel Citrus Pest Benchmark,
AgriVision20(310-319)
IEEE DOI 2008
Diseases, Databases, Insects, Benchmark testing, Agriculture, Task analysis, Mobile handsets BibRef

Moriya, É.A.S., Imai, N.N., Tommaselli, A.M.G., Berveglieri, A., Honkavaara, E., Soares, M.A., Marino, M.,
Detecting Citrus Huanglongbing in Brazilian Orchards Using Hyperspectral Aerial Images,
HyperMLPA19(1881-1886).
DOI Link 1912
BibRef

Sawant, S.A., Chakraborty, M., Suradhaniwar, S., Adinarayana, J., Durbha, S.S.,
Time Series Analysis Of Remote Sensing Observations For Citrus Crop Growth Stage And Evapotranspiration Estimation,
ISPRS16(B8: 1037-1042).
DOI Link 1610
BibRef

Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Rubber Trees, Plantations, Analysis .


Last update:Jun 9, 2021 at 21:04:26