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,
PandRS(61), No. 5, January 2007, pp. 341-353.
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.F.[Yi-Fannis],
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.F.[Yi-Fannis],
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.H.[Jin-Ha],
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
Qi, Y.[Yuan],
Dong, X.[Xuhua],
Chen, P.C.[Peng-Chao],
Lee, K.H.[Kyeong-Hwan],
Lan, Y.[Yubin],
Lu, X.Y.[Xiao-Yang],
Jia, R.C.[Rui-Chang],
Deng, J.Z.[Ji-Zhong],
Zhang, Y.[Yali],
Canopy Volume Extraction of Citrus reticulate Blanco cv. Shatangju
Trees Using UAV Image-Based Point Cloud Deep Learning,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Yuan, H.T.[Hao-Tian],
Huang, K.[Kekun],
Ren, C.X.[Chuan-Xian],
Xiong, Y.Z.[Yong-Zhu],
Duan, J.[Jieli],
Yang, Z.[Zhou],
Pomelo Tree Detection Method Based on Attention Mechanism and
Cross-Layer Feature Fusion,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Tian, H.X.[Hao-Xin],
Fang, X.P.[Xi-Peng],
Lan, Y.[Yubin],
Ma, C.Y.[Chen-Yang],
Huang, H.[Huasheng],
Lu, X.Y.[Xiao-Yang],
Zhao, D.H.[De-Hua],
Liu, H.[Hanchao],
Zhang, Y.[Yali],
Extraction of Citrus Trees from UAV Remote Sensing Imagery Using
YOLOv5s and Coordinate Transformation,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Yu, G.B.[Guo-Bin],
Zhang, L.[Li],
Luo, L.X.[Ling-Xia],
Liu, G.H.[Gui-Hua],
Chen, Z.Y.[Zong-Yi],
Xiong, S.S.[Shan-Shan],
Mapping Insect-Proof Screened Citrus Orchards Using Sentinel-2 MSl
Time-Series Images,
RS(15), No. 11, 2023, pp. 2867.
DOI Link
2306
BibRef
Morell-Monzó, S.[Sergio],
Sebastiá-Frasquet, M.T.[María-Teresa],
Estornell, J.[Javier],
Moltó, E.[Enrique],
Detecting abandoned citrus crops using Sentinel-2 time series. A case
study in the Comunitat Valenciana region (Spain),
PandRS(201), 2023, pp. 54-66.
Elsevier DOI
2307
Sentinel-2, Time series, Crop monitoring,
Agricultural land abandonment, Perennial crops, Citrus crops
BibRef
Lu, X.Y.[Xiao-Yang],
Li, W.[Wanjian],
Xiao, J.Q.[Jun-Qi],
Zhu, H.Y.[Hong-Yun],
Yang, D.C.[Da-Cheng],
Yang, J.[Jing],
Xu, X.[Xidan],
Lan, Y.[Yubin],
Zhang, Y.[Yali],
Inversion of Leaf Area Index in Citrus Trees Based on Multi-Modal
Data Fusion from UAV Platform,
RS(15), No. 14, 2023, pp. 3523.
DOI Link
2307
BibRef
Li, H.[Hao],
Zhang, J.[Jia],
Wang, J.[Jia],
Feng, Z.K.[Zhong-Ke],
Liang, B.[Boyi],
Xiong, N.[Nina],
Zhang, J.P.[Jun-Ping],
Sun, X.T.[Xiao-Ting],
Li, Y.B.[Yi-Bing],
Lin, S.Q.[Shu-Qi],
Extracting Citrus in Southern China (Guangxi Region) Based on the
Improved DeepLabV3+ Network,
RS(15), No. 23, 2023, pp. 5614.
DOI Link
2312
BibRef
Li, Y.[Yong],
Liu, W.J.[Wen-Jing],
Ge, Y.[Ying],
Yuan, S.[Sai],
Zhang, T.X.[Ting-Xuan],
Liu, X.[Xiuhui],
Extracting Citrus-Growing Regions by Multiscale UNet Using Sentinel-2
Satellite Imagery,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link
2401
BibRef
Li, W.J.[Wen-Jie],
Tang, B.[Biyu],
Hou, Z.[Zhen],
Wang, H.B.[Hong-Bo],
Bing, Z.Y.[Zong-Yu],
Yang, Q.[Qiong],
Zheng, Y.Q.[Yong-Qiang],
Dynamic Slicing and Reconstruction Algorithm for Precise Canopy
Volume Estimation in 3D Citrus Tree Point Clouds,
RS(16), No. 12, 2024, pp. 2142.
DOI Link
2406
BibRef
Yang, X.H.[Xuan-Han],
Wang, S.[Shan],
Lu, D.G.[Dan-Gui],
Shao, Y.[Yakui],
Feng, Z.K.[Zhong-Ke],
Wang, Z.C.[Zhi-Chao],
Ecological Adaptation and Sustainable Cultivation of Citrus
reticulata by Applying Mixed Design Principles under Changing Climate
in China,
RS(16), No. 13, 2024, pp. 2338.
DOI Link
2407
BibRef
Li, D.[Dasui],
Hu, Q.Q.[Qing-Qing],
Zhang, J.Z.[Jin-Zhi],
Dian, Y.Y.[Yuan-Yong],
Hu, C.G.[Chun-Gen],
Zhou, J.J.[Jing-Jing],
Leaf Nitrogen and Phosphorus Variation and Estimation of Citrus Tree
under Two Labor-Saving Cultivation Modes Using Hyperspectral Data,
RS(16), No. 17, 2024, pp. 3261.
DOI Link
2409
BibRef
Zhang, F.[Fukai],
Jin, X.B.[Xiao-Bo],
Jiang, J.[Jie],
An, S.[Shan],
Lyu, Q.[Qiang],
WCANet: Wavelet Channel Attention Network for Citrus Variety
Identification,
ICIP23(2845-2849)
IEEE DOI Code:
WWW Link.
1806
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
Apple Trees, Plantations, Analysis, Diseases .