Sugar Cane Crop Analysis, Production, Detection, Health, Change

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Classification. Sugar Cane.

Silva, W.F.[Wagner F.], Rudorff, B.F.T.[Bernardo F.T.], Formaggio, A.R.[Antonio R.], Paradella, W.R.[Waldir R.], Mura, J.C.[Jose C.],
Discrimination of agricultural crops in a tropical semi-arid region of Brazil based on L-band polarimetric airborne SAR data,
PandRS(64), No. 5, September 2009, pp. 458-463.
Elsevier DOI 0910
Remote sensing; Classification; Multi-polarization; Contextual classifier; Image classification BibRef

Formaggio, A.R.[Antonio R.], Vieira, M.A., Rennó, C.D., Aguiar, D.A., Mello, M.P.,
Object-Based Image Analysis and Data Mining for Mapping Sugarcane with Landsat Imagery in Brazil,
PDF File. 1007

Rudorff, B., Aguiar, D., Silva, W., Sugawara, L., Adami, M., Moreira, M.,
Studies on the Rapid Expansion of Sugarcane for Ethanol Production in São Paulo State (Brazil) Using Landsat Data,
RS(2), No. 4, April 2010, pp. 1057-1076.
DOI Link 1203
Award, Remote Sensing, Second. 2014. See:
DOI Link BibRef

Aguiar, D., Rudorff, B., Silva, W., Adami, M., Mello, M.,
Remote Sensing Images in Support of Environmental Protocol: Monitoring the Sugarcane Harvest in São Paulo State, Brazil,
RS(3), No. 12, December 2011, pp. 2682-2703.
DOI Link 1203

Miphokasap, P., Honda, K., Vaiphasa, C., Souris, M., Nagai, M.,
Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy,
RS(4), No. 6, June 2012, pp. 1651-1670.
DOI Link 1208

Adami, M., Mello, M.P., Aguiar, D.A., Rudorff, B.F.T., Souza, A.,
A Web Platform Development to Perform Thematic Accuracy Assessment of Sugarcane Mapping in South-Central Brazil,
RS(4), No. 10, October 2012, pp. 3201-3214.
DOI Link 1210

Duveiller, G., López-Lozano, R., Baruth, B.,
Enhanced Processing of 1-km Spatial Resolution fAPAR Time Series for Sugarcane Yield Forecasting and Monitoring,
RS(5), No. 3, March 2013, pp. 1091-1116.
DOI Link 1304

Mulianga, B.[Betty], Bégué, A.[Agnès], Simoes, M.[Margareth], Todoroff, P.[Pierre],
Forecasting Regional Sugarcane Yield Based on Time Integral and Spatial Aggregation of MODIS NDVI,
RS(5), No. 5, 2013, pp. 2184-2199.
DOI Link 1307

Morel, J.[Julien], Todoroff, P.[Pierre], Bégué, A.[Agnès], Bury, A.[Aurore], Martiné, J.F.[Jean-François], Petit, M.[Michel],
Toward a Satellite-Based System of Sugarcane Yield Estimation and Forecasting in Smallholder Farming Conditions: A Case Study on Reunion Island,
RS(6), No. 7, 2014, pp. 6620-6635.
DOI Link 1408

Mulianga, B.[Betty], Bégué, A.[Agnès], Clouvel, P.[Pascal], Todoroff, P.[Pierre],
Mapping Cropping Practices of a Sugarcane-Based Cropping System in Kenya Using Remote Sensing,
RS(7), No. 11, 2015, pp. 14428.
DOI Link 1512

Luna, I.[Inti], Lobo, A.[Agustín],
Mapping Crop Planting Quality in Sugarcane from UAV Imagery: A Pilot Study in Nicaragua,
RS(8), No. 6, 2016, pp. 500.
DOI Link 1608

Silva, A.L.[Alindomar Lacerda], Alves, D.S.[Diógenes Salas], Ferreira, M.P.[Matheus Pinheiro],
Landsat-Based Land Use Change Assessment in the Brazilian Atlantic Forest: Forest Transition and Sugarcane Expansion,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808

Karimi, P.[Poolad], Bongani, B.[Bhembe], Blatchford, M.[Megan], de Fraiture, C.[Charlotte],
Global Satellite-Based ET Products for the Local Level Irrigation Management: An Application of Irrigation Performance Assessment in the Sugarbelt of Swaziland,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903

Jiang, H.[Hao], Li, D.[Dan], Jing, W.L.[Wen-Long], Xu, J.H.[Jian-Hui], Huang, J.X.[Jian-Xi], Yang, J.[Ji], Chen, S.S.[Shui-Sen],
Early Season Mapping of Sugarcane by Applying Machine Learning Algorithms to Sentinel-1A/2 Time Series Data: A Case Study in Zhanjiang City, China,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904

Molijn, R.A.[Ramses A.], Iannini, L.[Lorenzo], Rocha, J.V.[Jansle Vieira], Hanssen, R.F.[Ramon F.],
Sugarcane Productivity Mapping through C-Band and L-Band SAR and Optical Satellite Imagery,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link 1905

Natarajan, S.[Sijesh], Basnayake, J.[Jayampathi], Wei, X.M.[Xian-Ming], Lakshmanan, P.[Prakash],
High-Throughput Phenotyping of Indirect Traits for Early-Stage Selection in Sugarcane Breeding,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912

Xiao, S.F.[Shun-Fu], Chai, H.H.[Hong-Hong], Shao, K.[Ke], Shen, M.Y.[Meng-Yuan], Wang, Q.[Qing], Wang, R.[Ruili], Sui, Y.[Yang], Ma, Y.T.[Yun-Tao],
Image-Based Dynamic Quantification of Aboveground Structure of Sugar Beet in Field,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link 2001

Zhang, J.[Jing], Tian, H.[Haiqing], Wang, D.[Di], Li, H.[Haijun], Mouazen, A.M.[Abdul Mounem],
A Novel Approach for Estimation of Above-Ground Biomass of Sugar Beet Based on Wavelength Selection and Optimized Support Vector Machine,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link 2003

Rahman, M.M.[Muhammad Moshiur], Robson, A.[Andrew],
Integrating Landsat-8 and Sentinel-2 Time Series Data for Yield Prediction of Sugarcane Crops at the Block Level,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004

Xin, F.F.[Feng-Fei], Xiao, X.M.[Xiang-Ming], Cabral, O.M.R.[Osvaldo M.R.], White, P.M.[Paul M.], Guo, H.Q.[Hai-Qiang], Ma, J.[Jun], Li, B.[Bo], Zhao, B.[Bin],
Understanding the Land Surface Phenology and Gross Primary Production of Sugarcane Plantations by Eddy Flux Measurements, MODIS Images, and Data-Driven Models,
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link 2007

Zhang, J.[Junyi], Sun, H.[Hong], Gao, D.H.[De-Hua], Qiao, L.[Lang], Liu, N.[Ning], Li, M.[Minzan], Zhang, Y.[Yao],
Detection of Canopy Chlorophyll Content of Corn Based on Continuous Wavelet Transform Analysis,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009

Chen, J.H.[Jing-Hua], Zhang, Q.[Qian], Chen, B.[Bin], Zhang, Y.G.[Yong-Guang], Ma, L.[Li], Li, Z.H.[Zhao-Hui], Zhang, X.K.[Xiao-Kang], Wu, Y.F.[Yun-Fei], Wang, S.Q.[Shao-Qiang], Mickler, R.A.[Robert A.],
Evaluating Multi-Angle Photochemical Reflectance Index and Solar-Induced Fluorescence for the Estimation of Gross Primary Production in Maize,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009

Xu, J.X.[Jing-Xian], Ma, J.[Jun], Tang, Y.N.[Ya-Nan], Wu, W.X.[Wei-Xiong], Shao, J.H.[Jin-Hua], Wu, W.B.[Wan-Ben], Wei, S.Y.[Shu-Yun], Liu, Y.F.[Yi-Fei], Wang, Y.C.[Yuan-Chen], Guo, H.Q.A.[Hai-Qi-Ang],
Estimation of Sugarcane Yield Using a Machine Learning Approach Based on UAV-LiDAR Data,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009

Zan, X.L.[Xu-Li], Zhang, X.[Xinlu], Xing, Z.[Ziyao], Liu, W.[Wei], Zhang, X.D.[Xiao-Dong], Su, W.[Wei], Liu, Z.[Zhe], Zhao, Y.Y.[Yuan-Yuan], Li, S.[Shaoming],
Automatic Detection of Maize Tassels from UAV Images by Combining Random Forest Classifier and VGG16,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009

Meng, R.[Ran], Lv, Z.G.[Zhen-Gang], Yan, J.B.[Jian-Bing], Chen, G.S.[Geng-Shen], Zhao, F.[Feng], Zeng, L.L.[Ling-Lin], Xu, B.Y.[Bin-Yuan],
Development of Spectral Disease Indices for Southern Corn Rust Detection and Severity Classification,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010

Guan, H.X.[Hai-Xiang], Liu, H.J.[Huan-Jun], Meng, X.T.[Xiang-Tian], Luo, C.[Chong], Bao, Y.L.[Yi-Lin], Ma, Y.Y.[Yu-Yang], Yu, Z.Y.[Zi-Yang], Zhang, X.L.[Xin-Le],
A Quantitative Monitoring Method for Determining Maize Lodging in Different Growth Stages,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010

Yu, L.H.[Li-Hong], Shang, J.L.[Jia-Li], Cheng, Z.Q.[Zhi-Qiang], Gao, Z.B.[Ze-Bin], Wang, Z.X.[Zi-Xin], Tian, L.[Luo], Wang, D.T.[Dan-Tong], Che, T.[Tao], Jin, R.[Rui], Liu, J.G.[Jian-Gui], Dong, T.F.[Tai-Feng], Qu, Y.H.[Yong-Hua],
Assessment of Cornfield LAI Retrieved from Multi-Source Satellite Data Using Continuous Field LAI Measurements Based on a Wireless Sensor Network,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010

Bi, K., Xiao, S., Gao, S., Zhang, C., Huang, N., Niu, Z.,
Estimating Vertical Chlorophyll Concentrations in Maize in Different Health States Using Hyperspectral LiDAR,
GeoRS(58), No. 11, November 2020, pp. 8125-8133.
Laser radar, Vegetation mapping, Remote sensing, Distance measurement, Monitoring, Indexes, Biomedical monitoring, vertical distribution BibRef

Liu, J., Ferrazzoli, P., Guerriero, L., Bai, J., Liu, Q., Zhang, Z.,
Modeling Microwave Emission of Corn Crop Considering Leaf Shape and Orientation Under the Physical Optics Approximation,
GeoRS(58), No. 12, December 2020, pp. 8316-8331.
Vegetation mapping, Microwave measurement, Shape, Microwave theory and techniques, Scattering, multiple scattering modeling BibRef

Kavats, O.[Olena], Khramov, D.[Dmitriy], Sergieieva, K.[Kateryna], Vasyliev, V.[Volodymyr],
Monitoring of Sugarcane Harvest in Brazil Based on Optical and SAR Data,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012

Chen, X.X.[Xin-Xin], Feng, L.[Lan], Yao, R.[Rui], Wu, X.J.[Xiao-Jun], Sun, J.[Jia], Gong, W.[Wei],
Prediction of Maize Yield at the City Level in China Using Multi-Source Data,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101

Denis, A.[Antoine], Desclee, B.[Baudouin], Migdall, S.[Silke], Hansen, H.[Herbert], Bach, H.[Heike], Ott, P.[Pierre], Kouadio, A.L.[Amani Louis], Tychon, B.[Bernard],
Multispectral Remote Sensing as a Tool to Support Organic Crop Certification: Assessment of the Discrimination Level between Organic and Conventional Maize,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101

Mudereri, B.T., Abdel-Rahman, E.M., Dube, T., Landmann, T., Niassy, S., Tonnang, H.E.Z., Khan, Z.R.,
Potential of Resampled Multispectral Data for Detecting Desmodium-brachiaria Intercropped With Maize In A 'push-pull' System,
DOI Link 2012

Mufungizi, A.A., Musakwa, W., Gumbo, T.,
A Land Suitability Analysis of the Vhembe District, South Africa, The Case of Maize and Sorghum,
DOI Link 2012

Rahimi Jamnani, M., Liaghat, A., Mirzaei, F.,
Optimization of Sugarcane Harvest Using Remote Sensing,
DOI Link 1912

Khosravirad, M., Omid, M., Sarmadian, F., Hosseinpour, S.,
Predicting Sugarcane Yields in Khuzestan Using a Large Time-series Of Remote Sensing Imagery Region,
DOI Link 1912

do Valle Gonçalves, R.R., Zullo, J., Romani, L.A.S., do Amaral, B.F., Sousa, E.P.M.,
Agricultural monitoring using clustering techniques on satellite image time series of low spatial resolution,
data visualisation, feature extraction, geophysical image processing, image resolution, time series, Sugarcane BibRef

Scrivani, R., Zullo, J., Romani, L.A.S.,
SITS for estimating sugarcane production,
vegetation mapping, Brazil, Sa~o Paulo, agrometeorological data, correlation coefficient, environmental data, time series BibRef

Baloloy, A.B., Blanco, A.C., Gana, B.S., Santa Ana, R.C., Olalia, L.C.,
Landsat-Based Detection and Severity Analysis of Burned Sugarcane Plots in Tarlac, Philippines Using Differenced Normalized Burn Ratio (dNBR),
DOI Link 1612

Santos Romani, L.A.[L. Alvim], do Valle Goncalves, R.R.[R. Ribeiro], Amaral, B.F., Chino, D.Y.T., Zullo, J., Traina, C., Sousa, E.P.M., Traina, A.J.M.,
Clustering analysis applied to NDVI/NOAA multitemporal images to improve the monitoring process of sugarcane crops,

do Valle Goncalves, R.R.[R. Ribeiro], Zullo, J., Peron, T.M.[T. Marques], Medeiros Evangelista, S.R., Santos Romani, L.A.[L. Alvim],
Numerical models to forecast the sugarcane production in regional scale based on time series of NDVI/AVHRR images,
agricultural engineering BibRef

do Valle Goncalves, R.R.[R. Ribeiro], Zullo, J., Ferraresso, C.S., Sousa, E.P.M., Santos Romani, L.A.[L. Alvim], Traina, A.J.M.,
Analysis of NOAA/AVHRR multitemporal images, climate conditions and cultivated land of sugarcane fields applied to agricultural monitoring,

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