Adams, J. B., Sabol, D. E., Kapos, V., Filho, R. A., Roberts, D. A. and Smith, M. O. 1995. Classification of multispectral images based on fractions of endmembers: application to land-cover change in the Brazilian Amazon. Remote Sens. Environ. 52, 137-154.
Anon. 2004. National Survey of Conservation Tillage Practices. Conservation Technology Information Center. West Lafayette. Available at http://www.ctic.purdue.edu.
Bannari, A., Pacheco, A., Staenz, K., McNairn, H. and Omari, K. 2006. Estimating and mapping crop residues cover on agricultural lands using hyperspectral and IKONOS data. Remote Sens. Environ. 104, 447-459.
Boardman, J. W. 1993. Automated spectral unmixing of AVIRIS data using convex geometry
concepts: in Summaries. Fourth JPL Airborne Geoscience Workshop. JPL Pub. 1, 11-14.
Crippen, R. E. 1990. Calculating the vegetation index faster. Remote Sens. Environ. 34, 71-73.
Darvishsefat, A. A., Pir Bavaghar, M. and Rajab-Pourrahmati, M. 2005. Remote Sensing for GIS Managers. University of Tehran Press. (in Farsi)
Daughtry, C. S. T., Doraiswamy, P. C., Hunt, E. R., Stern, A. J., McMurtrey, J. E. and Prueger, J. H. 2006. Remote sensing of crop residue cover and soil tillage intensity. Soil Till. Res. 91, 101-108.
Dennison, P. E. and Roberts, D. A. 2003. The effects of vegetation phenology on endmember
selection and species mapping in Southern California Chaparral. Remote Sens. Environ.
87, 295-309.
Eck, K. J. and Brown, D. E. 2011. Estimating Corn and Soybean Residue Cover. Available at http://www.extension.purdue.edu.
Gitelson, A. A., Kaufman, Y. J. and Merzlyak, M. N. 1996. Use of a green channel in remote sensing of global vegetation from EOSMODIS. Remote Sens. Environ. 58, 289-298.
Godwin, R. J. 1990. Tillage for Crop Production in Areas of Low Rainfall. Food and Agriculture Organization of the United Nation. ISBN-10: 9251025428
Jordan, C. F. 1969. Derivation of leaf area index from quality measurements of light on the forest floor. Ecology. 50, 663-666.
Kaufman, Y. J. and Tanre, D. 1992. Atmospherically resistant vegetation index (ARVI) for EOS-MODIS. IEEE. T. Geosci. Remote Sens. 30, 261-270.
Lobb, D. A., Huffman, E. and Reicosky, C. 2007. Importance of information on tillage practices in the modeling of environmental processes and in the use of environmental indicators. J. Environ. Manage. 82, 377-387.
Pacheco, A. and McNairn, H. 2010. Evaluating multispectral remote sensing and spectral unmixing analysis for crop residue mapping. Remote Sens. Environ. 114, 2219-2228.
Pacheco, A. and McNairn, H. 2011. Mapping crop residue cover over regional agricultural landscapes in Canada. International Symposium on Remote Sensing of Environment. April 10-15. Sydney, Australia,
Roujean, J. L. and Breon, F. M. 1995. Estimating PAR absorbed by vegetation from bidirectional reflectance measurements. Remote Sens. Environ. 51(3): 375-384.
Schaub, D., French, N. H. F., Brooks, C. and Powell, R. 2007. Using ASTER data to detect crop
residue and to improve crop classification.
ASPRS Annual Conference. May 7-11. Tampa.
Florida.
Serbin, G., Daughtry, C. S. T., Hunt, E. R., Brown, D. J. and McCarty, G. W. 2009. Effect of soil spectral properties on remote sensing of crop residue cover. Soil Sci. Soc. Am. J. 73, 1545-1558.
Shelton, D. P. and Jasa, P. J. 2012. Estimating of Percent Residue Cover Using the Line Transect method. Institute of Agriculture and Natural Resources. University of Nebraska Lincoln Extension.
Singer, R. B. and McCord, T. B. 1979. Mars: Large scale mixing of bright and dark materials and implications for analysis of spectral reflectance. Lunar Planet Sci. 10, 1825–1848.
Sullivan, D. G., Fulmer, J. L., Strickland, T. C., Masters, M. and Yao, H. 2007. Field scale evaluation of crop residue cover distribution using airborne and satellite remote sensing. Proceedings of the Georgia Water Resources Conference. March 27-29. University of Georgia.
Thoma, D., Gupta, S. C. and Bauer, M. E. 2004. Evaluation of optical remote sensing models for crop residue cover assessment. J. Soil Water Conserv. Soc. 59(5): 224-233.
Yang, C., Everitt, J. H. and Bradford, J. M. 2006. Comparison of QuickBird satellite imagery and airborne imagery for mapping grain sorghum yield patterns. Precision Agric. 7, 33-44.
Yang, Z., Willis, P. and Mueller, R. 2008. Impact of band ratio enhanced a WIFS image to crop classification accuracy. Proceeding of the PECORA 17: The Future of Land Imaging Going Operational. Nov. 18-20. Denver, Colorado,
)