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Original Articles

Biophysical and yield information for precision farming from near-real-time and historical Landsat TM images

Pages 2879-2904 | Published online: 26 Nov 2010

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Jibo Yue, Yuanyuan Fu, Wei Guo, Haikuan Feng & Hongbo Qiao. (2022) Estimating fractional coverage of crop, crop residue, and bare soil using shortwave infrared angle index and Sentinel-2 MSI. International Journal of Remote Sensing 43:4, pages 1253-1273.
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Xiaodong Zhang, Ho Jin Kim, Clinton Streeter, David A. Claypool, Ramesh Sivanpillai & Santhosh Seelan. (2011) Near real-time high-resolution airborne camera, AEROCam, for precision agriculture. Geocarto International 26:7, pages 537-551.
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B.R. Parida, W.B. Collado, R. Borah, M.K. Hazarika & L. Samarakoon. (2008) Detecting Drought-Prone Areas of Rice Agriculture Using a MODIS-Derived Soil Moisture Index. GIScience & Remote Sensing 45:1, pages 109-129.
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SergioM. Vicente‐Serrano, JoséM. Cuadrat‐Prats & Alfredo Romo. (2006) Early prediction of crop production using drought indices at different time‐scales and remote sensing data: application in the Ebro Valley (north‐east Spain). International Journal of Remote Sensing 27:3, pages 511-518.
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Klaus Ammann. (2008) Integrated farming: why organic farmers should use transgenic crops. New Biotechnology 25:2-3, pages 101-107.
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E. Pantaleoni, B. A. Engel & C. J. Johannsen. (2007) Identifying agricultural flood damage using Landsat imagery. Precision Agriculture 8:1-2, pages 27-36.
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Prasad S. Thenkabail, Eden A. Enclona, Mark S. Ashton & Bauke Van Der Meer. (2004) Accuracy assessments of hyperspectral waveband performance for vegetation analysis applications. Remote Sensing of Environment 91:3-4, pages 354-376.
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