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Remote Sensing Applications in Sugarcane Cultivation: A Review
Jaturong Som-ard, Clement Atzberger, Emma Izquierdo-Verdiguier, Francesco Vuolo and Markus Immitzer Remote Sensing 13(20) 4040 (2021) https://doi.org/10.3390/rs13204040
Progress in Advanced Computing and Intelligent Engineering
Shyamal Virnodkar, V. K. Pachghare, V. C. Patil and Sunil Kumar Jha Advances in Intelligent Systems and Computing, Progress in Advanced Computing and Intelligent Engineering 1199 163 (2021) https://doi.org/10.1007/978-981-15-6353-9_15
Empirical model for forecasting sugarcane yield on a local scale in Brazil using Landsat imagery and random forest algorithm
Ana Cláudia dos Santos Luciano, Michelle Cristina Araújo Picoli, Daniel Garbellini Duft, Jansle Vieira Rocha, Manoel Regis Lima Verde Leal and Guerric le Maire Computers and Electronics in Agriculture 184 106063 (2021) https://doi.org/10.1016/j.compag.2021.106063
Snow and glacial feature identification using Hyperion dataset and machine learning algorithms
Mohd Anul Haq, Mohammed Alshehri, Gazi Rahaman, Abhijit Ghosh, Prashant Baral and Chander Shekhar Arabian Journal of Geosciences 14(15) (2021) https://doi.org/10.1007/s12517-021-07434-3
Priscila M. Kai, Ronaldo M. da Costa, Bruna M. de Oliveira, Deborah S. A. Fernandes, Juliana Felix and Fabrizzio Soares 1212 (2020) https://doi.org/10.1109/COMPSAC48688.2020.00-91
A Time Series Mining Approach for Agricultural Area Detection
Investigating the identification of atypical sugarcane using NIR analysis of online mill data
Justin Sexton, Yvette Everingham, David Donald, Steve Staunton and Ronald White Computers and Electronics in Agriculture 168 105111 (2020) https://doi.org/10.1016/j.compag.2019.105111
ICT Analysis and Applications
Shyamal S. Virnodkar, Vinod K. Pachghare, V. C. Patil and Sunil Kumar Jha Lecture Notes in Networks and Systems, ICT Analysis and Applications 93 539 (2020) https://doi.org/10.1007/978-981-15-0630-7_55
Site-specific assessment of spatial and temporal variability of sugarcane yield related to soil attributes
A generalized space-time OBIA classification scheme to map sugarcane areas at regional scale, using Landsat images time-series and the random forest algorithm
Ana Cláudia dos Santos Luciano, Michelle Cristina Araújo Picoli, Jansle Vieira Rocha, Daniel Garbellini Duft, Rubens Augusto Camargo Lamparelli, Manoel Regis Lima Verde Leal and Guerric Le Maire International Journal of Applied Earth Observation and Geoinformation 80 127 (2019) https://doi.org/10.1016/j.jag.2019.04.013
Classification of sugarcane varieties using visible/near infrared spectral reflectance of stalks and multivariate methods
Spectral separability and mapping potential of cassava leaf damage symptoms caused by whiteflies (Bemisia tabaci)
Neil C Sims, Paul De Barro, Glenn J Newnham, Andrew Kalyebi, Sarina Macfadyen and Tim J Malthus Pest Management Science 74(1) 246 (2018) https://doi.org/10.1002/ps.4718
Remote Sensing and Cropping Practices: A Review
Agnès Bégué, Damien Arvor, Beatriz Bellon, Julie Betbeder, Diego De Abelleyra, Rodrigo P. D. Ferraz, Valentine Lebourgeois, Camille Lelong, Margareth Simões and Santiago R. Verón Remote Sensing 10(1) 99 (2018) https://doi.org/10.3390/rs10010099
Forecasting yield by integrating agrarian factors and machine learning models: A survey
Dhivya Elavarasan, Durai Raj Vincent, Vishal Sharma, Albert Y. Zomaya and Kathiravan Srinivasan Computers and Electronics in Agriculture 155 257 (2018) https://doi.org/10.1016/j.compag.2018.10.024
Pixel-based crop classification in Peru from Landsat 7 ETM+ images using a Random Forest model
Kenichi TATSUMI, Yosuke YAMASHIKI, Anggie Karolin Morales MORANTE, Lia Ramos FERNÁNDEZ and Ricardo Apaclla NALVARTE Journal of Agricultural Meteorology 72(1) 1 (2016) https://doi.org/10.2480/agrmet.D-15-00010
Accurate prediction of sugarcane yield using a random forest algorithm
Yvette Everingham, Justin Sexton, Danielle Skocaj and Geoff Inman-Bamber Agronomy for Sustainable Development 36(2) (2016) https://doi.org/10.1007/s13593-016-0364-z
Identifying Sugarcane Plantation using LANDSAT-8 Images with Support Vector Machines
Detecting Sirex noctilio grey-attacked and lightning-struck pine trees using airborne hyperspectral data, random forest and support vector machines classifiers
Land-use/cover classification in a heterogeneous coastal landscape using RapidEye imagery: evaluating the performance of random forest and support vector machines classifiers
Classification of soybean varieties using different techniques: case study with Hyperion and sensor spectral resolution simulations
Fábio M. Breunig, Le^nio S. Galvão, Anto^nio R. Formaggio and José C. N. Epiphanio Journal of Applied Remote Sensing 5(1) 053533 (2011) https://doi.org/10.1117/1.3604787
Climate Change, Intercropping, Pest Control and Beneficial Microorganisms
Discriminating cropping systems and agro-environmental measures by remote sensing
José Manuel Peña-Barragán, Francisca López-Granados, Luis García-Torres, et al. Agronomy for Sustainable Development 28(2) 355 (2008) https://doi.org/10.1051/agro:2007049