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An Automated Method for Annual Cropland Mapping along the Season for Various Globally-Distributed Agrosystems Using High Spatial and Temporal Resolution Time Series

Bibliographic reference Matton, Nicolas ; Sepulcre Canto, Guadalupe ; Waldner, François ; Valero, Silvia ; Morin, David ; et. al. An Automated Method for Annual Cropland Mapping along the Season for Various Globally-Distributed Agrosystems Using High Spatial and Temporal Resolution Time Series. In: Remote Sensing, Vol. 7, no.10, p. 13208-13232 (6 October 2015)
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  1. Rembold Felix, Atzberger Clement, Savin Igor, Rojas Oscar, Using Low Resolution Satellite Imagery for Yield Prediction and Yield Anomaly Detection, 10.3390/rs5041704
  2. Vicente-Serrano Sergio M., Evaluating the Impact of Drought Using Remote Sensing in a Mediterranean, Semi-arid Region, 10.1007/s11069-006-0009-7
  3. Gregory P. J., Ingram J. S. I., Brklacich M., Climate change and food security, 10.1098/rstb.2005.1745
  4. Zhang Minghua, Qin Zhihao, Liu Xue, Ustin Susan L, Detection of stress in tomatoes induced by late blight disease in California, USA, using hyperspectral remote sensing, 10.1016/s0303-2434(03)00008-4
  5. Messer Ellen, Cohen Marc J., Conflict, Food Insecurity and Globalization, 10.2752/155280107x211458
  6. Gebbers R., Adamchuk V. I., Precision Agriculture and Food Security, 10.1126/science.1183899
  7. Atzberger Clement, Advances in Remote Sensing of Agriculture: Context Description, Existing Operational Monitoring Systems and Major Information Needs, 10.3390/rs5020949
  8. Boryan Claire, Yang Zhengwei, Mueller Rick, Craig Mike, Monitoring US agriculture: the US Department of Agriculture, National Agricultural Statistics Service, Cropland Data Layer Program, 10.1080/10106049.2011.562309
  9. Whitcraft Alyssa, Becker-Reshef Inbal, Justice Christopher, A Framework for Defining Spatially Explicit Earth Observation Requirements for a Global Agricultural Monitoring Initiative (GEOGLAM), 10.3390/rs70201461
  10. Moschini Giancarlo, Hennessy David A., Chapter 2 Uncertainty, risk aversion, and risk management for agricultural producers, Handbook of Agricultural Economics (2001) ISBN:9780444507280 p.87-153, 10.1016/s1574-0072(01)10005-8
  11. Becker-Reshef I., Vermote E., Lindeman M., Justice C., A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data, 10.1016/j.rse.2010.01.010
  12. Prasad Anup K., Chai Lim, Singh Ramesh P., Kafatos Menas, Crop yield estimation model for Iowa using remote sensing and surface parameters, 10.1016/j.jag.2005.06.002
  13. Martínez-Fernández J., González-Zamora A., Sánchez N., Gumuzzio A., A soil water based index as a suitable agricultural drought indicator, 10.1016/j.jhydrol.2014.12.051
  14. Vicente-Guijalba Fernando, Martinez-Marin Tomas, Lopez-Sanchez Juan M., Dynamical Approach for Real-Time Monitoring of Agricultural Crops, 10.1109/tgrs.2014.2372897
  15. Ok, Eur. J. Remote Sens., 45, 421 (2012)
  16. Osman Julien, Inglada Jordi, Dejoux Jean-François, Assessment of a Markov logic model of crop rotations for early crop mapping, 10.1016/j.compag.2015.02.015
  17. Waldner François, Lambert Marie-Julie, Li Wenjuan, Weiss Marie, Demarez Valérie, Morin David, Marais-Sicre Claire, Hagolle Olivier, Baret Frédéric, Defourny Pierre, Land Cover and Crop Type Classification along the Season Based on Biophysical Variables Retrieved from Multi-Sensor High-Resolution Time Series, 10.3390/rs70810400
  18. Yu Le, Wang Jie, Clinton Nicholas, Xin Qinchuan, Zhong Liheng, Chen Yanlei, Gong Peng, FROM-GC: 30 m global cropland extent derived through multisource data integration, 10.1080/17538947.2013.822574
  19. Crnojevic Vladimir, Lugonja Predrag, Brkljac Branko, Brunet Borislav, Classification of small agricultural fields using combined Landsat-8 and RapidEye imagery: case study of northern Serbia, 10.1117/1.jrs.8.083512
  20. Johnson, Photogramm. Eng. Remote Sens., 11, 1201 (2010)
  21. Bartholomé E., Belward A. S., GLC2000: a new approach to global land cover mapping from Earth observation data, 10.1080/01431160412331291297
  22. Global Land Cover SHARE (GLC-SHARE) Database Beta-Release Version 1.0-2014
  23. Friedl M.A, McIver D.K, Hodges J.C.F, Zhang X.Y, Muchoney D, Strahler A.H, Woodcock C.E, Gopal S, Schneider A, Cooper A, Baccini A, Gao F, Schaaf C, Global land cover mapping from MODIS: algorithms and early results, 10.1016/s0034-4257(02)00078-0
  24. Waldner François, Fritz Steffen, Di Gregorio Antonio, Defourny Pierre, Mapping Priorities to Focus Cropland Mapping Activities: Fitness Assessment of Existing Global, Regional and National Cropland Maps, 10.3390/rs70607959
  25. Becker-Reshef Inbal, Justice Chris, Sullivan Mark, Vermote Eric, Tucker Compton, Anyamba Assaf, Small Jen, Pak Ed, Masuoka Ed, Schmaltz Jeff, Hansen Matthew, Pittman Kyle, Birkett Charon, Williams Derrick, Reynolds Curt, Doorn Bradley, Monitoring Global Croplands with Coarse Resolution Earth Observations: The Global Agriculture Monitoring (GLAM) Project, 10.3390/rs2061589
  26. Joint Experiment of Crop Assessment and Monitoring (JECAM)
  27. Di Gregorio (2005)
  28. JECAM Guidelines for Cropland and Crop Type Definition and Field Data Collection v1.0
  29. Pittman Kyle, Hansen Matthew C., Becker-Reshef Inbal, Potapov Peter V., Justice Christopher O., Estimating Global Cropland Extent with Multi-year MODIS Data, 10.3390/rs2071844
  30. Vintrou Elodie, Desbrosse Annie, Bégué Agnès, Traoré Sibiry, Baron Christian, Lo Seen Danny, Crop area mapping in West Africa using landscape stratification of MODIS time series and comparison with existing global land products, 10.1016/j.jag.2011.06.010
  31. Yang Chenghai, Everitt James H., Fletcher Reginald S., Murden Dale, Using high resolution QuickBird imagery for crop identification and area estimation, 10.1080/10106040701204412
  32. De Wit A. J. W., Clevers J. G. P. W., Efficiency and accuracy of per-field classification for operational crop mapping, 10.1080/01431160310001619580
  33. Castillejo-González Isabel Luisa, López-Granados Francisca, García-Ferrer Alfonso, Peña-Barragán José Manuel, Jurado-Expósito Montserrat, de la Orden Manuel Sánchez, González-Audicana María, Object- and pixel-based analysis for mapping crops and their agro-environmental associated measures using QuickBird imagery, 10.1016/j.compag.2009.06.004
  34. Marshall M. T., Husak G. J., Michaelsen J., Funk C., Pedreros D., Adoum A., Testing a high-resolution satellite interpretation technique for crop area monitoring in developing countries, 10.1080/01431161.2010.532168
  35. Bontemps, Remote Sens. (2015)
  36. Hagolle Olivier, Huc Mireille, Pascual David, Dedieu Gerard, A Multi-Temporal and Multi-Spectral Method to Estimate Aerosol Optical Thickness over Land, for the Atmospheric Correction of FormoSat-2, LandSat, VENS and Sentinel-2 Images, 10.3390/rs70302668
  37. Leo (2001)
  38. Jun Chen, Ban Yifang, Li Songnian, China: Open access to Earth land-cover map, 10.1038/514434c
  39. The Southern African Development Community (SADC) Land Cover Database
  40. U.S. Department of Agriculture’s Crop Data Layer
  41. Goudriaan, Volume 2 (2012)
  42. Hughes G., On the mean accuracy of statistical pattern recognizers, 10.1109/tit.1968.1054102
  43. Likas Aristidis, Vlassis Nikos, J. Verbeek Jakob, The global k-means clustering algorithm, 10.1016/s0031-3203(02)00060-2
  44. Agarwal P. K., Procopiuc C. M., Exact and Approximation Algorithms for Clustering, 10.1007/s00453-001-0110-y
  45. Desclée Baudouin, Bogaert Patrick, Defourny Pierre, Forest change detection by statistical object-based method, 10.1016/j.rse.2006.01.013
  46. Radoux Julien, Defourny Pierre, Automated Image-to-Map Discrepancy Detection using Iterative Trimming, 10.14358/pers.76.2.173
  47. Lillesand (2004)
  48. Otukei J.R., Blaschke T., Land cover change assessment using decision trees, support vector machines and maximum likelihood classification algorithms, 10.1016/j.jag.2009.11.002
  49. Valero, Remote Sens. (2015)
  50. Waldner François, Canto Guadalupe Sepulcre, Defourny Pierre, Automated annual cropland mapping using knowledge-based temporal features, 10.1016/j.isprsjprs.2015.09.013
  52. Hanchuan Peng, Fuhui Long, Ding C., Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy, 10.1109/tpami.2005.159
  53. Pineda-Bautista Bárbara B., Carrasco-Ochoa J.A., Martı́nez-Trinidad J. Fco., General framework for class-specific feature selection, 10.1016/j.eswa.2011.02.016