Share This Article:

Review Article: Remote Sensing, Surface Residue Cover and Tillage Practice

Full-Text HTML XML Download Download as PDF (Size:196KB) PP. 211-217
DOI: 10.4236/jep.2012.32026    6,540 Downloads   10,657 Views   Citations


A growing world population and possible liquid fuel energy shortages are likely to result in worldwide agricultural intensification, and the possible expansion of non-sustainable practices. The adoption of non-sustainable practices could result in the loss of currently productive land, with potential impacts on human welfare and economic viability. One of the easiest techniques to maintain productivity is to maintain surface soil organic matter. However, developing reliable, cost effective and accurate methods for quantifying and monitoring crop residue cover (a major source of soil organic matter) that remains on top of the soil over large spatial extents constitutes a significant challenge. This article reviews potential remote sensing approaches for estimating surface residue cover with a view to mapping tillage practice.

Cite this paper

O. Paul, "Review Article: Remote Sensing, Surface Residue Cover and Tillage Practice," Journal of Environmental Protection, Vol. 3 No. 2, 2012, pp. 211-217. doi: 10.4236/jep.2012.32026.


[1] H. Blanco-Canqui, R. Lal, W. M. Post and L. B. Owens, “Changes in Long-Term No-Till Corn Growth and Yield under Different Rates of Stover Mulch,” Agronomy Jour- nal., Vol. 98, No. 4, 2006, pp. 1128-1136. doi:10.2134/agronj2006.0005
[2] P. Gallagher, M. Dikeman, J. Fritz, E. Wailes, W. Gauther and H. Shapouri, “Biomass from Crop Residues: Cost and Supply Estimates,” U.S.D.A., Office of the Chief Eco- nomist, Office of Energy Policy and New Uses. Agricul- tural Economic Report No. 819, 2003.
[3] E. Davidson, and I. Janssens, “Temperature Sensitivity of soil Carbon Decomposition and Feedbacks to Climate Change,” Nature, Vol. 440, No. 9, 2006, pp. 165-173. doi:10.1038/nature04514
[4] J. Fargione, J. Hill, D. Tilman, S. Polasky and P. Hawthorne, “Land Clearing and the Biofuel Carbon Debt,” Science, Vol. 319, No. 5867, 2008, pp. 1235-1238. doi:10.1126/science.1152747
[5] P. Garnier, C. Neel, C. Aita, S. Recous, F. Lafolie and B. Mary, “Modeling Carbon and Nitrogen Dynamics in a Bare Soil with and without Straw Incorporation,” Euro- pean Journal of Soil Science, Vol. 54, No. 3, 2003, pp. 555-568. doi:10.1046/j.1365-2389.2003.00499.x
[6] A. Bannari, A. Pacheco, K. Staenz, H. McNairn and K. Omari, “Estimating and Mapping Crop Residue Cover on Agricultural Lands Using Hyperspectral and IKONOS Data,” Remote Sensing of Environment, Vol. 104, No. 4, 2006, pp. 447-459. doi:10.1016/j.rse.2006.05.018
[7] H. Blanco-Canqui and R. Lal, “Corn Stover Removal for Expanded Uses Reduces Soil Fertility and Structural Stability,” Soil Science Society of America Journal, Vol. 73, No. 2, 2009, pp. 418-426. doi:10.2136/sssaj2008.0141
[8] J. Scharlemann and W. Laurance, “How Green Are Bio- fuels?” Science, Vol. 319, No. 5859, 2008, pp. 43-44. doi:10.1126/science.1153103
[9] T. Searchinger, R. Heimlich, R. Houghton, F. Dong, A. Elobeid, J. Fabiosa, S. Tokgoz, D. Hayes and T. Yu, “Use of U.S. Croplands for Biofuels Increases Greenhouse Gases through Emissions from Land-Use Change,” Sci- ence, Vol. 319, No. 5867, 2008, pp. 1238-1240. doi:10.1126/science.1151861
[10] D. Lu, “The Potential and Challenge of Remote Sensing- Based Biomass Estimation,” International Journal of Re- mote Sensing, Vol. 27, No. 7, 2006, pp. 1297-1328. doi:10.1080/01431160500486732
[11] A. Vi?a, A Peters and L. Ji, “Use of Multispectral Ikonos Imagery for Discriminating between Conventional and Conservation Agricultural Tillage Practices,” Photogram- metric Engineering and Remote Sensing, Vol. 69, No. 5, 2003, pp. 537-544.
[12] R. L. Graham, R. Nelson, J. Sheehan, R. Perlack and L. Wright, “Current and Potential U.S. Corn Stover Supplies,” Agronomy Journal, Vol. 99, No. 1, 2007, pp. 1-11. doi:10.2134/agronj2005.0222
[13] H. Blanco-Canqui and R. Lal, “Soil and Crop Response Harvesting Corn Residues for Biofuel Production,” Geoderma, Vol. 141, No. 3-4, 2007, pp. 355-362. doi:10.1016/j.geoderma.2007.06.012
[14] C. T. Daughtry, P. C. Doraiswamy, E. R. Hunt Jr., A. J. Stern, J. E. McMurtrey and J. H. Prueger, “Remote Sensing of Crop Residue Cover and Soil Tillage Intensity,” Soil and Tillage Research, Vol. 91, No. 1-2, 2006, pp. 101-108. doi:10.1016/j.still.2005.11.013
[15] CTIC, “National Survey of Conservation Tillage Practices,” Conservation Technology Information Center, CTIC, West Lafayette, IN., 2004.
[16] N. Madden, J. Southard and P. Mitchell “Conservation Tillage Reduces PM10 Emissions in Dairy Forage Rota- tions,” Atmospheric Environment, Vol. 42, No. 16, 2008, pp. 3795-3808. doi:10.1016/j.atmosenv.2007.12.058
[17] A. Pacheco and H. McNairn, “Evaluating Multispectral Remote Sensing and Spectral Unmixing Analysis for Crop Residue Mapping,” Remote Sensing of Environment, Vol. 114, No. 10, 2010, pp. 2219-2228. doi:10.1016/j.rse.2010.04.024
[18] G. Serbin, T. Craig, C. S. T. Daughtry, E. R. Hunt Jr., D.I. Brown, and G. W. McCarty, “Effect of Soil Spectral Pro- perties on Remote Sensing of Crop Residue Cover,” Soil Science of America Journal, Vol. 73, No. 5, 2009, pp. 1545-1558. doi:10.2136/sssaj2008.0311
[19] S. Upadhyaya, K. Lancas, G. Santos-Filho and N. Rag- huwanshi, “One-Pass Tillage Equipment Outstrips Con- ventional Tillage Method,” California Agriculture, Vol. 55, No. 5, 2001, pp. 44-47. doi:10.3733/ca.v055n05p44
[20] E. M. Barnes, K.A. Sudduth, J. W. Hummel, S. M. Lesch, D. L. Corwin, C. Yang, C.T. Daughtry and W. C. Bausch, “Remote- and Ground-Based Sensor Techniques to Map Soil Properties,” Photogrammetric Engineering & Re- mote Sensing, Vol. 69, No. 6, 2003, pp. 619-630.
[21] N. Wollenhaupt, “Estimating Residue: Line Transect Me- thod,” G1570, MU extension, 1993. (accessed online on 14th January 2011).
[22] J. Ju, E. Kolaczyk and S. Gopal, “Gaussian Mixture Dis- criminant Analysis and Sub-Pixel Land Cover Charac- terization in Remote Sensing,” Remote Sensing of Environment, Vol. 84, No. 4, 2003, pp. 550-560. doi:10.1016/S0034-4257(02)00172-4
[23] F. van der Meer and S. de Jong, “Improving the Results of Spectral Unmixing of Landsat Thematic Mapper Im- agery by Enhancing the Orthogonality of End-Members,” International Journal of Remote Sensing, Vol. 21, No. 15, 2000, pp. 2781-2797. doi:10.1080/01431160050121249
[24] C. T. Daughtry, E. R. Hunt Jr., P. C. Doraiswamy, J. E. McMurtrey, “Remote Sensing the Spatial Distribution of Crop Residues,” Agronomy Journal, Vol. 97, No. 3, 2005, pp. 864-871. doi:10.2134/agronj2003.0291
[25] C. T. Daughtry and E. R. Hunt Jr., “Mitigating the Effects of Soil and Residue Water Contents on Remotely Sensed Estimates of Crop Residue Cover,” Remote Sensing of Environment, Vol. 112, No. 4, 2008, pp. 1647-1657. doi:10.1016/j.rse.2007.08.006
[26] B. K. Gelder, A. L. Kaleita and R. M. Cruse, “Estimating Mean Field Residue Cover on Midwestern Soils Using Satellite Imagery,” Agronomy Journal, Vol. 101, No. 3, 2009, pp. 635-643. doi:10.2134/agronj2007.0249
[27] G. Serbin, C. S. T. Daughtry, R. Hunt Jr., J. Reeves and D. I. Brown, “Effect of Soil Composition and Mineralogy on Remote Sensing of Crop Residue Cover,” Remote Sens- ing of Environment, Vol. 113, No. 1, 2009, pp. 224-238. doi:10.1016/j.rse.2008.09.004
[28] D. Thoma, C. Gupta and E. Bauer, “Evaluation of Optical Remote Sensing Models for Crop Residue Cover Assess- ment,” Journal of Soil and Water Conservation, Vol. 59, No. 5, 2004, pp. 224-233.
[29] G. Serbin, E. R. Hunt Jr., C. S. T. Daughtry, G. W. Mc- Carty and P. C. Doraiswamy, “An Improved ASTER In- dex for Remote Sensing of Crop Residue,” Remote Sens- ing, Vol. 1, No. 4, 2009, pp. 971-991. doi:10.3390/rs1040971
[30] N. D. Uri, J. D. Atwood and J. Sanabria, “The Environ- mental Benefits and Costs of Conservation Tillage,” En- vironmental Geology, Vol. 38, No. 2, 1999, pp. 111-125.
[31] S. South, J. Qi and D. Lusch, “Optimal Classification Methods for Mapping Agricultural Tillage Practices,” Remote Sensing of Environment, Vol. 91, No. 1, 2004, pp. 90-97. doi:10.1016/j.rse.2004.03.001
[32] G. Robertson, P. Eldor and R. Harwood, “Greenhouse Gases in Intensive Agriculture: Contributions of Individual Gases to the Radiative Forcing of the Atmosphere,” Science, Vol. 289, No. 5486, 2000, pp. 922-925. doi:10.1126/science.289.5486.1922
[33] R. A. Evans and J. Young, “Plant Litter and Establish- ment of Alien Annual Weed Species in Rangeland Com- munities,” Weed Science, Vol. 18, 1970, pp. 697-703.
[34] E. A. Holland and D. C. Coleman, “Litter Placement Ef- fects on Microbial and Organic Matter Dynamics in an Agroecosystem,” Ecology, Vol. 68, No. 2, 1987, pp. 425- 433. doi:10.2307/1939274
[35] A. K. Knapp and T. R. Seastedt, “Detritus Accumulation Limits Productivity of Tallgrass Prairie,” Bioscience, Vol. 36, No. 10, 1986, pp. 622-688. doi:10.2307/1310387
[36] G. De’ath and K. Fabricius, “Classification and Regression Trees: A Powerful yet Simple Technique for Ecological Data Analysis,” Ecology, Vol. 81, No. 11, 2000, pp. 3178- 3192. doi:10.1890/0012-9658(2000)081[3178:CARTAP]2.0.CO;2
[37] J. E. McMurtrey III, E. W. Chappelle, C. T. Daughtry and M. S. Kim, “Fluorescence and Reflectance of Crop Resi- due and Soil,” Journal of Soil and Water Conservation, Vol. 48, No. 3, 1993, pp. 207-213.
[38] S. Tompkins, J. F. Mustard, C. M. Pieters and D. W. Forysth, “Optimization of Endmembers for Spectral Mixture Analysis,” Remote Sensing of Environment, Vol. 59, No. 3, 1997, pp. 472-489. doi:10.1016/S0034-4257(96)00122-8
[39] USGS, “Earth Observing 1 (EO-1): Sensors-Hyperion,” EROS Data Center, USGS, Sioux Falls, SD, 2007.
[40] H. McNarin and R. Protz, “Mapping Corn Residue Cover on Agricultural Fields in Oxford County, Ontario, Using Thematic Mapper,” Canadian Journal of Remote Sensing, Vol. 19, No. 2, 1993, pp. 152-159.
[41] F. Biard and F. Baret, “Crop Residue Estimation Using Multiband Reflectance,” Remote Sensing of Environment, Vol. 59, No. 3, 1997, pp. 530-536. doi:10.1016/S0034-4257(96)00125-3
[42] G. Foody and A. Mathur, “The Use of Small Training Sets Containing Mixed Pixels for Accurate Hard Image Classification: Training on Mixed Spectral Responses for Classification by SVM,” Remote Sensing of Environment, Vol. 103, No. 2, 2006, pp. 179-189. doi:10.1016/j.rse.2006.04.001
[43] M. O. Smith, S. L. Ustin, J. B. Adams and A. R. Gillespie, “Vegetation in Deserts: I.A Regional Measure of Abun- dance from Multispectral Images,” Remote Sensing of Environment, Vol. 31, No. 1, 1990, pp. 1-26. doi:10.1016/0034-4257(90)90074-V
[44] M. O. Smith, P. E. Johnston and J. Adams, “Quantitative Determination of Mineral Types and Abundances from Reflectance Spectra Using Principal Component Analy- sis,” Journal of Geophysical Research, Vol. 90, 1985, pp. 797-804.
[45] P. E. Dennison and D. A. Roberts, “Endmember Selection for Multiple Endmember Spectral Mixture Analysis Us- ing Endmember Average RMSE,” Remote Sensing of En- vironment, Vol. 87, No. 2-3, 2003, pp. 123-135. doi:10.1016/S0034-4257(03)00135-4
[46] D. A. Roberts, M. O. Smith and J. B. Adams, “Green Vegetation, Non-Photosynthetic Vegetation, and Soils in AVIRIS Data,” Remote Sensing of Environment, Vol. 44, No. 2-3, 1993, pp. 255-269. doi:10.1016/0034-4257(93)90020-X
[47] D. Roberts, M. Gardner, R. Church, S. Ustin, G. Scheer and R. Green, “Mapping Chaparral in the Santa Monica Mountains Using Multiple Endmember Spectral Mixture Models,” Remote Sensing of Environment, Vol. 65, No. 3,1998, pp. 267-279. doi:10.1016/S0034-4257(98)00037-6
[48] Fan Wenyi, H. Baoxin, M.John, L. Mingze, “Compara- tive Study between a New Nonlinear Model and Common Linear Model for Analyzing Laboratory Simulated-Forest Hyperspectral Data,” International Journal of Remote Sensing, Vol. 30, No. 11, 2009, pp. 2951-2962. doi:10.1080/01431160802558659
[49] A. R. Huete, “Separation of Soil-Plant Spectral Mixtures by Factor Analysis,” Remote Sensing of Environment, Vol. 19, No. 3, 1986, pp. 237-251. doi:10.1016/0034-4257(86)90055-6
[50] T. W. Ray and B. C. Murray, “Nonlinear Spectral Mixing in Desert Vegetation,” Remote Sensing of Environment, Vol. 55, No. 1, 1996, pp. 59-64. doi:10.1016/0034-4257(95)00171-9
[51] I. Numata, D. Roberts, O. Chadwick, J. Schimel, F. Sampaio, F. Leonidas and J. Soares, “Characterization of Pasture Biophysical Properties and the Impact of Grazing Intensity Using Remotely Sensed Data,” Remote Sensing of Environment, Vol. 109, No. 3, 2007, pp. 314-327. doi:10.1016/j.rse.2007.01.013
[52] F. J. Garc?a-Haro, M. A. Gilabert and J. Meli?, “Extrac- tion of Endmembers from Spectral Mixtures,” Remote Sensing of Environment, Vol. 68, No. 3,1999, pp. 237- 253. doi:10.1016/S0034-4257(98)00115-1
[53] D. R. Peddle and A. M. Smith, “Spectral Mixture Analy- sis of Agricultural Crops: Endmember Validation and Biophysical Estimation in Potato Plots,” International Journal of Remote Sensing, Vol. 26, No. 22, 2005, pp. 4959-4979. doi:10.1080/01431160500213979

comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.