Effects of soil surface roughness on soil processes and remote sensing data interpretation and its measuring techniques - a review

Karolina Herodowicz, Jan Piekarczyk


Surface roughness is a very important physical feature of soil, affecting various soil processes and accuracy of remote sensing data interpretation. Thus, there is a need to describe it quantitatively. The main aim of the paper was to show needs and benefits of collecting quantitative information about soil surface roughness which is the most relevant parameter used as an index to predict water and wind erosion. Surface roughness can reduce soil erosion and soil losses even by up to 31%. Thereby, it increases the development of fauna and flora and improves the structure of soil and its biological quality. In the first section of the paper there are presented definitions of soil roughness proposed by different authors. The next section explains how various factors influence soil surface roughness. Then, the categorization of soil surface roughness discussed in literature is presented. The next part of the paper includes information about a role of soil roughness in agricultural, soil science and a hydrology research. Moreover, soil surface roughness plays an important role in a remote sensing of soils. The knowledge of quantitative soil surface roughness allows more accurate interpretation of the soil properties from remote sensing data, because this soil feature can decrease soil spectra even over 70% and makes their analysis difficult. In addition, deepening knowledge about soil roughness will allow more precise conclusions about the amount of reflected shortwave solar radiation indirectly shaping the Earth’s climate. In the final section, the techniques for measuring and indices for describing soil roughness are shown. However, the authors prefer a photogrammetry technique for collecting these data, because it is quick and easy to use, ensuring high resolution and accuracy of data (about 1 mm) and the image processing is currently simplifid as software to process is absolutely affordable.


soil surface roughness, tillage treatments, soil processes, remote sensing, soil surface roughness measuring techniques

Full Text:



Álvarez-Mozos, J., Campo, M.T., Gimenez, R., Casali, J., Leibar, U., 2011. Implications of scale, slope, tillage operation and direction in the estimation of surface depression storage. Soil and Tillage Research 111

(2): 142–153. https://doi.org/10.1016/j.still.2010.09.004.

Abban, B.K.B., Papanicolaou, A.N.T., Giannopoulos, C.P., Dermisis, D.C., Wacha, K.M., Wilson, C.G., Elhakeem, M., 2017. Quantifying the changes of soil surface microroughness due to rainfall-induced erosion on a smooth surface. Nonlinear Processes in Geophysics 24: 569-579. https://doi.org/10.5194/npg-2016-76.

Aguilar, M.A., Aguilar, F.J., Negreiros, J., 2009. Off-the-shelf laser scanning and close-range digital photogrammetry for measuring agricultural soils microrelief. Biosystems Engineering 103: 504–517. https://doi.org/10.1016/j.biosystemseng.2009.02.010.

Allmaras, R.R., Burwell, R., Larson, W.E., Holt, R.F., 1966. Total porosity and random roughness of the interrow zone as influence by tillage. USDA Conservation Research Report 7.

Amoah, J.K.O., Amatya, D.M., Nnaji, S., 2013. Quantifying watershed surface depression storage: determination and application in a hydrologic model. Hydrological Processes 27 (17): 2401–2413. https://doi.org/10.1002/hyp.9364.

Arika, C.L., Gregory, J.M., Borrelli, J., Zartman, R.E., 1986. A ridge- and clod-wind erosion model. ASAE Paper No. 86-2531. ASAE, St. Joseph, MI.

Arrouays, D., Grundy, M.G., Hartemink, A.E., Hempel, J.W., Heuvelink, G.B., Hong, S.Y., Zhang, G.L., 2014. Chapter Three-GlobalSoilMap: Toward a fine-resolution global grid of soil properties. Advances in Agronomy 125: 93–134. https://doi.org/10.1016/B978-0-12-800137-0.00003-0.

Baghdadi, N., Cerdan, O., Zribi, M., Auzet, A.-V., Darboux, F., El Hajj, M., Kheir, R., 2008. Operational performance of current synthetic aperture radar sensors in mapping soil surface characteristics in agricultural environments: Application to hydrological and erosion modelling. Hydrological Processes 22: 9-20. https://doi.org/10.1002/hyp.6609.

Barthès, B.G., Kouakoua, E., Larré-Larrouy, M.C., Razafimbelo, T.M., de Luca, E.F., Azontonde, A., Neves, C.S.V.J., de Freitas, P.L., Feller, C.L., 2008. Texture and sesquioxide effects on water-stable aggregates and organic matter in some tropical soils. Geoderma 143: 14–25.

Bayer, A., Bachmann, M., Müller, A., Kaufmann, H., 2012. A comparison of feature-based MLR and PLS regression techniques for the prediction of three soil constituents in a degraded South African ecosystem. Applied and Environmental Soil Science 2012. DOI: 10.1155/2012/971252.

Ben-Dor, E., Banin, A., 1995. Near-Infrared Analysis as a Rapid Method to Simultaneously Evaluate Several Soil Properties. Soil Science Society of America Journal 59 (2): 364-372. https://doi.org/10.2136/sssaj1995.03615995005900020014x.

Ben-Dor, E., Irons, J.R., Epema, G.F., 1999. Soil reflectance. In Manual of Remote Sensing: Remote Sensing for the Earth Sciences, 3rd ed.;Wiley & Sons: New York, NY, USA, 111–173.

Ben-Dor, E., N., Goldshleger, Y., Benyamini, M.A., Blumberg, D.G.. 2003. The spectral reflectance properties of soil structural crusts in the 1.2 to 2.5μm spectral region. Soil Science Society of America Journal 67: 289-299.

Ben-Dor, E., Chabrillat, S., Demattê, J.A.M., Taylor, G.R., Hill, J., Whiting, M.L., Sommer, S., 2009. Using imaging spectroscopy to study soil properties. Remote Sensing of Environment 113: 38–55. https://doi.org/10.1016/j.rse.2008.09.019.

Bertuzzi, P., Rauws, G., Courault, D., 1990. Testing roughness indices to estimate soil surface roughness changes due to simulated rainfall. Soil and Tillage Research 17 (1–2): 87–99. https://doi.org/10.1016/0167-1987(90)90008-2.

Bielders, C.L., Baveye, P., Wilding, L.P., Drees, L.R., Valentin, C., 1996. Tillage-induced spatial distribution of surface crusts on a sandy Paleustulf from Togo. Soil Science Society America Journal 60 (3): 843–855.

Bretar, F., Arab-Sedze, M., Champion, J., Pierrot-Deseilligny, M., Heggy, E., Jacquemoud, S., 2013. An advanced photogrammetric method to measure surface roughness: Application to volcanic terrains in the Piton de la Fournaise, Reunion Island. Remote Sensing of Environment 135: 1–11. https://doi.org/10.1016/j.rse.2013.03.026.

Bronick, C.J., Lal, R., 2005. Soil structure and management: A review. Geoderma 124: 3–22. https://doi.org/10.1016/j.geoderma.2004.03.005.

Brunet, D., Barthès, B.G., Chotte, J.L., Feller, C., 2007. Determination of carbon and nitrogen contents in Alfisols, Oxisols and Ultisols from Africa and Brazil using NIRS analysis: Effects of sample grinding and set heterogeneity. Geoderma 139: 106–117. https://doi.org/10.1016/j.geoderma.2007.01.007.

Cecillon, L., Cassagne, N., Czarnes, S., Gros, R., Brun, J.-J., 2008. Variable selection in near infrared spectra for the biological characterization of soil and earthworm casts. Soil Biology and Biochemistry, 40: 1975–1979.

Cerdan, O., Souchère, V., Lecomte, V., Couturier, A., Le Bissonnais, Y., 2002. Incorporating soil surface crusting processes in an expert-based runoff model: sealing and transfer by runoff and erosion related to agricultural management. CATENA 46: 189–205.

Cierniewski J., 1987. A model for soil surface roughness influence on the spectral response of bare soils in the visible and near infrared range. Remote Sensing of Environment 23: 97–115.

Cierniewski, J., 1999. Geometrical modeling of soil bidirectional reflectance in the optical domain. Bogucki Scientific Publishers, Poznań.

Cierniewski, J., Gdala, T., Karnieli, A., 2004. A hemispherical–directional reflectance model as a tool for understanding image distinctions between cultivated and uncultivated bare surfaces. Remote Sensing of Environment 90: 505–523. https://doi.org/10.1016/j.rse.2004.01.004.

Cierniewski, J., Kuśnierek, K., 2010. Influence of several soil properties on soil surface reflectance. Quaestiones Geographicae, 29 (1): 13–25.

Cierniewski J., Kaźmierowski C., Królewicz S., Piekarczyk J., 2013. Effects of soil roughness on the optimal time of cultivated soils observation by satellites for the soils average diurnal albedo approximation. Selected Topics in Applied Earth Observations and Remote Sensing 6 (3): 1194-1198. DOI: 10.1109/JSTARS.2012.2234440.

Cierniewski, J., Karnieli, A., Kazmierowski, C., Krolewicz, S., Piekarczyk, J., Lewinska, K., Goldberg, A., Wesolowski, R., Orzechowski, M., 2015. Effects of soil surface irregularities on the diurnal variation of soil broadband blue-sky albedo. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8 (2): 493–502. https://doi.org/10.1109/JSTARS.2014.2330691.

Croft, H., Anderson, K., Kuhn, N.J., 2012. Reflectance anisotropy for measuring soil surface roughness of multiple soil types. Catena 93: 87–96. https://doi.org/10.1016/j.catena.2012.01.007.

Cruse, R.M., Linden, D.R., Radke, J.K., Larson, W.E., Larntz, K., 1980. A model to predict tillage effects on soil temperature. Soil Science Society of America Journal 44 (2): 378–383. DOI: 10.2136/sssaj1980.03615995004400020034x.

Currence, H.D., 1969. Development of a method for measuring and describing soil surface roughness. Retrospective Theses and Dissertations, 3568.

Currence, H.D., Lovely, W.D., 1970. Analysis of soil surface roughness. Transactions of the ASAE 13 (6): 710–714.

Darboux, F., Davy, Ph., Gascuel-Odoux, C., Huang, C., 2002. Evolution of soil surface roughness and flowpath connectivity in overland flow experiments. Catena 46 (2-3): 125-139. https://doi.org/10.1016/S0341-8162(01)00162-X.

Darboux F., Huang C.-h., 2003. An instantaneous-profile laser scanner to measure soil surface microtopography. Soil Science Society of America Journal 67 (1): 92–99. DOI: 10.2136/sssaj2003.9200.

Daughtry, C.S.T., Doraiswamy, P.C., Hunt Jr., E.R., Stern, A.J., McMurtrey III, J.E., Prueger, J.H., 2006. Remote sensing of crop residue cover and soil tillage intensity. Soil and Tillage Research 91: 101–108.

Duiker, S.W., Rhoton, F.E., Torrent, J., E. Smeck, N., Ral, R., 2003. Iron (hydr)oxide crystallinity effects on soil aggregation. Soil Science Society of America Journal 67: 606-611. https://doi.org/10.2136/sssaj2003.0606.

FAO, 2011. The State of Food Insecurity in the World 2011: How Does International Price Volatility Affect Domestic Economies and Food Security. Food and Agriculture Organization of the United Nations, Rome.

Flanagan, D.C., Huang, C., Norton, L.D., Parker, S.C., 1995. Laser scanner for erosion plot measurements. Transactions of the ASAE 38: 703–710.

Foley, J. A., Defries, R., Asner, G., Barford, C., Bonan, G., Carpenter, S., Chapin III, F.S., Coe, M., Daily, G., Gibbs, H., Helkowski, J. H., Holloway, T., Howard, E. A., Kucharik, C., Monfreda, C., Patz, J., Prentice, I., Ramankutty, N., Snyder, P. K., 2005. Global Consequences of Land Use. Science 309: 570-574 (New York). https://doi.org/10.1126/science.1111772.

Foley, J.A., Ramankutty, N., Brauman, K.A., Cassidy, E.S., Gerber, J.S., Johnston, M., Mueller, N.D., O’Connell, C., Ray, D.K., West, P.C., Balzer, C., Bennett, E.M., Carpenter, S.R., Hill, J., Monfreda, C., Polasky, S., Rockström, J., Sheehan, J., Siebert, S., Tilman, D., Zaks, D.P.M., 2011. Solutions for a cultivated planet. Nature 478: 337–42. https://doi.org/10.1038/nature10452.

Fryrear, D.W., 1984. Soil ridge-clods and wind erosion. Transactions of the ASAE 27 (2): 445–448. DOI: 10.13031/2013.32808.

Gallant, J.C., Moore, I.D., Hutchinson, M.F., Gessler, P., 1994. Estimating fractal dimension of profiles: a comparison of methods. Mathematical Geology 26 (4): 455–481.

Garcia Moreno, R., 2006. Desarrollo de una metodología para la medición de la rugosidad del suelo. Ph. D. Dissertation, Polytechnic University of Madrid (UPM), 120 pp.

García Moreno R., Requejo A. S., Alonso A.M. T., Barrington S.,

Diaz M.C., 2008a. Shadow Analysis: A Method for Measuring Soil Surface Roughness. Geoderma 146: 201–208.

García Moreno R., Álvarez, M.C.D., Alonso A.M. T., Barrington S., Requejo A. S., 2008b. Tillage and soil type effects on soil surface roughness at semiarid climatic conditions. Soil and Tillage Research 98: 35-44.

García Moreno, R., Requejo, A.S., Altisent, J.M.D., Álvarez, M.C.D., 2011. Significance of soil erosion on soil surface roughness decay after tillage operations. Soil and Tillage Research 117: 49–54. https://doi.org/10.1016/j.still.2011.08.006.

Génermont, S., Cellier, P., 1997. A mechanistic model for estimating ammonia volatilization from slurry applied to bare soil. Agricultural and Forest Meteorology 88 (1-4): 145–167. https://doi.org/10.1016/S0168-1923(97)00044-0.

Ghidey, F., Alberts, E.E., 1998. Runoff and soil losses as affected by

corn and soybean tillage systems. Journal of Soil and Water Conservation 53: 64–70.

Gilliot, J.M., Vaudour, E., Michelin, J., 2017. Soil surface roughness measurement: A new fully automatic photogrammetric approach applied to agricultural bare fields. Computers and Electronics in Agriculture 134: 63–78. https://doi.org/10.1016/j.compag.2017.01.010.

Ginting, D., Moncrief, J.F., Gupta, S.C., Evans, S.D., 1998. Corn yield, runoff, and sediment losses from manure and tillage systems. Journal of Environmental Quality 27: 1396–1402.

Grunwald, S., Thompson, J.A., Boettinger, J.L., 2011. Digital soil mapping and modeling at continental scales: Finding solutions for global issues. Soil Sciences Society of America Journal 75: 1201–1213.

Guanter, L., Kaufmann, H., Segl, K., Förster, S., Rogaß, C., Chabrillat, S., Küster, T., Hollstein, A.;, Rossner, G., Chlebek, C., et al., 2015. The EnMAP spaceborne imaging spectroscopy mission for earth observation. Remote Sensing 7: 8830–8857. DOI: 10.3390/rs70708830.

Hansen, B., Schjönning, P., Sibbesen, E., 1999. Roughness indices

for estimation of depression storage capacity of tilled soil surfaces. Soil and Tillage Research 52 (1-2): 103-11. https://doi.org/10.1016/S0167-1987(99)00061-6.

Hauer, G., Klik, A., Jester, W., Truman, C.C., 2001. Field Investigations of Rainfall Impact on Soil Erosion and Soil Surface Roughness. Soil Erosion Research the 21st Century, Proc. Int. Symp. (3-5 January, Honolulu, USA). Eds. J.C. Ascough II and D.C. Flanagan. St. Joseph, MI: ASAE: 467–470. https://doi.org/10.13031/2013.4578.

Herodowicz, K., 2017. Influence of the distance between a reflectance sensor and soil samples with different roughness. Polish Journal of Soil Science XLIX/2: 133–147. https://doi.org/10.17951/pjss/2016.49.2.133.

Huang, C., Bradford, J. M., 1992. Applications of a laser scanner to quantify soil microtopography. Soil Science Society of America Journal 56 (1): 14–21, https://doi.org/10.2136/sssaj1992.03615995005600010002x.

Iziomon, M.G., Mayer, H., 2002. On the variability and modelling of surface albedo and long-wave radiation components. Agricultural and Forest Meteorology 111: 141–152. https://doi.org/10.1016/S0168-1923(02)00013-8.

Jester, W., Klik, A., 2005. Soil surface roughness measurement methods, applicability, and surface representation. Catena 64: 174–192. https://doi.org/10.1016/j.catena.2005.08.005.

Jones, C., Kiniry, J., 1986. CERES-Maize, A Simulation Model of Maize Growth and Development. College Station, Texas A&M University Press, College Station.

Kamphorst, E.C., Jetten, V., Guérif, J., Pitkänen, J., Iversen, B.V., Douglas, J.T., Paz, A., 2000. How to predict maximum water storage in depressions from soil roughness measurements. Soil Science Society of America Journal 64 (5): 1749–1758.

Korucu, T., Selvi, K.C., Ince, I., 2016. Effect of different subsoiling applications on soil surface roughness. International symposium ISB-INMA THE Agricultural and mechanical engineering, Bucharest 27-29 October.

Larney, F.J., Bullock, M.S., McGinn, S.M., Fryrear, D.W., 1995. Quantifying wind erosion on summer fallow in southern Alberta. Journal of Soil and Water Conservation 50 (1): 91–95.

Larney, F.J., Cessna, A.J., Bullock, M.S., 1999. Herbicide transport on wind-eroded sediment. Journal of Environmental Quality 28 (5): 1412–1421. DOI:10.2134/jeq1999.00472425002800050004x.

Lichti, D.D., Jamtsho, S., 2006. Angular Resolution of Terrestrial Laser Scanners. The Photogrammetric Record 21 (114): 141–160. https://doi.org/10.1111/j.1477-9730.2006.00367.x.

Linden, D.R., van Doren, Jr., 1986. Parameters for characterizing tillage-induced soil surface roughness. Soil Science Society of America Journal 50: 1560-1565. https://doi.org/10.2136/sssaj1986.03615995005000060035x.

Linder, W., 2006. Digital photogrammetry, a practical course. Springer Berlin, Heidelberg, New York, USA, 214 pp. https://doi.org/10.1007/3-540-29153-9.

Lobb, D.A., Huffman, E., Reicosky, D.C., 2007. Importance of information on tillage practices in the modelling of environmental processes and in the use of environmental indicators. Journal of Environmental Management 82: 377–387. https://doi.org/10.1016/j.jenvman.2006.04.019.

Loew, A., Mauser, W., 2008. Inverse modeling of soil characteristics from surface soil moisture observations: potential and limitations. Hydrology and Earth System Sciences Discussions 5: 95-145. https://doi.org/10.5194/hessd-5-95-2008.

Magunda, M. K., Larson, W. E., Linden, D. R., Nacer, E. A., 1997. Changes in microrelief and their effects on infiltration and erosion during simulated rainfall. Soil Technology 10 (1): 57–67. https://doi.org/10.1016/0933-3630(95)00039-9.

Malinverno, A., 1990. A simple method to estimate the fractal dimension of a self-affine series. Geophysical Research Letters 17 (11): 1953–1956. https://doi.org/10.1029/GL017i011p01953.

Martinez-Agirre, A., Álvarez-Mozos, J., Giménez, R., 2016. Evaluation of surface roughness parameters in agricultural soils with different tillage conditions using a laser profile meter. Soil and Tillage Research 161: 19–30. https://doi.org/10.1016/j.still.2016.02.013.

Marzahn, P., Ludwig, R., 2009. On the derivation of soil surface roughness from multi parametric PolSAR data and its potential for hydrological modeling. Hydrology and Earth System Sciences 13 (3): 381–394. https://doi.org/10.5194/hessd-5-3383-2008.

Marzahn, P., Rieke-Zapp, D., Ludwig, R., 2012. Assessment of soil surface roughness statistics for microwave remote sensing applications using a simple photogrammetric acquisition system. ISPRS Journal of Photogrammetry and Remote Sensing 72: 80–89. https://doi.org/10.1016/j.isprsjprs.2012.06.005.

Matthias, A.D., Fimbres, A., Sano, E.E., Post, D.F., Accioly, L., Batchily, A.K., Ferreira, L. G., 2000. Surface roughness effects on soil albedo. Soil Science Society of America Journal 64 (3): 1035-1041. DOI: 10.2136/sssaj2000.6431035x.

Merrill, S.D., Huang, C., Zobeck, T.M., Tanaka, D.L., 2001. Use of the chain set for scale-sensitive and erosion relevant measurement of soil surface roughness. Stott, D.E., Mohtar, R.H., Steinhardt, G.C., (Eds), Sustaining the Global Farm. Selected papers from the 10th International Soil Conservation Organization Meeting held May 24-29, 1999 at Purdue University and the USDA-ARS National Soil Erosion Resear 594–600.

Mikhajlova, N.A., Orlov, D.S., 1986. Optical properties of soils and soil components (in Russian). Moskva, Russia, Nauka, 35–38.

Mirzaei, M., Ruy, S., Ziarati, T., 2012. Monitoring of soilroughness caused by rainfall using stereo-photogrammetry. International Research Journal of Applied and Basic Sciences 3 (2): 322–338.

Moldenhauer, W.C., 1970. Influence of rainfall energy on soil loss and infiltration rates: II. effect of clod size distribution. Soil Science Society of America Journal 34 (2): 673-677. DOI:10.2136/sssaj1970.03615995003400040037x.

Moron, A., Cozzolino, D., 2003. Exploring the use of near infrared reflectance spectroscopy to study physical properties and microelements in soils. Journal of Near Infrared Spectroscopy 154: 145–154.

Murillo, J.M., Moreno, E., Girón, I.F., Oblitas, M.I., 2004. Conservation tillage: long term effect on soil and crops under rained conditions in south-west Spain (Western Andalusia). Spanish Journal Agricultural Research 2 (1): 35–43.

Nanni, M.R., Demattê, J.A.M., 2006. Spectral reflectance methodology in comparison to traditional soil analysis. Soil Science Society of America Journal 70 (2): 393-407. https://doi.org/10.2136/sssaj2003.0285.

Nouwakpo, S., Huang, Ch., Frankenberger, J., Bethel, J., 2010. A simplified close range photogrammetry method for soil erosion assessment. 2nd Joint Federal Interagency Conference, Las Vegas, NV, 27 June – 1 July.

Oades, J.M., Waters, A.G., 1991. Aggregate hierarchy in soils. Australian Journal of Soil Research 29: 815-828. http://dx.doi.org/10.1071/SR9910815.

Or, D., Smets, B. F., Wraith, J. M., Dechesne, A., Friedman, S. P., 2007. Physical constraints 30 affecting bacterial habitats and activity in unsaturated porous media – a review. Advances in Water Reso urces

: 1505–1527.

Pardini, G., 2003. Fractal scaling of surface roughness in artificially weathered smectite-rich soil regoliths. Geoderma 117 (1-2): 157-167. https://doi.org/10.1016/S0016-7061(03)00164-2.

Piekarczyk, J., Kazmierowski, C., Krolewicz, S., Cierniewski, J., 2016. Effects of Soil Surface Roughness on Soil Reflectance Measured in Laboratory and Outdoor Conditions. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9: 827–834. https://doi.org/10.1109/JSTARS.2015.2450775.

Potter K.N., Horton R., Cruse R.M., 1987. Soil surface roughness effects on radiation reflectance and soil heat flux. Soil Science Society of America Journal 51 (4): 855–860.

Potter, K.N., Zobeck, T.M., Hagen, L.J., 1990. A micro-relief index to estimate soil erodibility by wind. Transactions of the ASAE 33 (1): 151–155. DOI: 10.13031/2013.31309.

Power, A. G., 2010. Ecosystem services and agriculture: tradeoffs and synergies. Philosophical Transactions of the Royal Society B, 365: 2959–2971. DOI: 10.1098/rstb.2010.0143.

Ramankutty, N., Foley, J. A., Norman, J., McSweeney, K., 2002. The global distribution of cultivable lands: current patterns and sensitivity to possible climate change. Global Ecology and Biogeography 11 (5): 377–392. https://doi.org/10.1046/j.1466-822x.2002.00294.x.

Ramankutty, N., Evan, A. T., Monfreda, C., Foley, J. A., 2008. Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Global Biogeochemical Cycles 22 (1): GB1003. https://doi.org/10.1029/2007GB002952.

Richter, N., Chabrillat, S., Kaufmann, H., Gfz, G.P., Sensing, S.R., 2005. Preliminary analysis for soil organic carbon determination from spectral reflectance in the frame of the EU project DeSurvey. The 1st International Conference on Remote Sensing and Geoinformation Processing in the Assessment of Land Degradation and Desertification, Trier, September 7-9, Sierra 1–6.

Richter, N., Jarmer, T., Chabrillat, S., Oyonarte, C., Hostert, P., Kaufmann, H., 2009. Free iron oxide determination

in Mediterranean soils using diffuse reflectance spectroscopy. Soil Science Society of America Journal 73 (1): 72–81. DOI: 10.2136/sssaj2008.0025.

Rieke-Zapp, D.H., Nearing, M.A., 2005. Digital close range photogrammetry for measurement of soil erosion. Photogrammetric Record 20: 69–87. https://doi.org/10.1111/j.1477-9730.2005.00305.x.

Röhrig, R., Langmaack, M., Schrader, S., Larink, O., 1998. Tillage systems and soil compaction - their impact on abundance and vertical distribution of Enchytraeidae. Soil and Tillage Research 46 (1-2): 117-127. https://doi.org/10.1016/S0167-1987(98)80113-X.

Römkens, M.J.M., Wang, J. Y., 1986a. Effect of tillage on surface roughness. Transactions of the ASAE 29 (2): 429-433. https://doi.org/10.13031/2013.30167.

Römkens, M.J.M., Singarayar, S., Gantzer, C.J., 1986b. An automated non contact surface profile meter. Soil and Tillage Research 6 (3): 193–202. https://doi.org/10.1016/0167-1987(86)90454-X.

Römkens, M.J. M., Wang, J.Y., 1987. Soil roughness changes from rainfall. Transactions of the ASAE 30 (1): 101-107. https://doi.org/10.13031/2013.30409.

Rosa, J. D., Cooper, M., Darboux, F., Medeiros, J. C., 2012. Soil roughness evolution in different tillage systems under simulated rainfall using a semivariogram-based index. Soil and Tillage Research 124: 226–232. https://doi.org/10.1016/j.still.2012.06.001.

Saleh, A., 1993. Soil roughness measurement: chain method. Journal of Soil and Water Conservation 48 (6): 527-529.

Santanello, J.A., Peters-Lidard, C.D., Garcia, M.E., Mocko, D.M., Tischler, M.A., Moran, M.S., Thoma, D.P., 2007. Using remotely-sensed estimates of soil moisture to infer soil texture and hydraulic properties across a semi-arid watershed. Remote Sensing of Environment 110 (1): 79–97. https://doi.org/10.1016/j.rse.2007.02.007.

Skidmore, E.L., 1997. Comments on chain methods for measuring soil roughness. Soil Science Society of America Journal 61 (5): 1532-1533.

Smith, M., 2014. Roughness in the Earth Sciences Earth-Science Reviews 136: 202-225. https://doi.org/10.1016/j.earscirev.2014.05.016.

Steinberg, A., Chabrillat, S., Stevens, A., Segl, K., Foerster, S., 2016. Prediction of common surface soil properties based on Vis-NIR airborne and simulated EnMAP imaging spectroscopy data: Prediction accuracy and influence of spatial resolution. Remote Sensing 8 (7): 613. DOI: 10.3390/rs8070613.

Stevens, A., van Wesemael, B., Bartholomeus, H., Rosillon, D., Tychon, B., Ben-Dor, E., 2008. Laboratory, field and airborne spectroscopy for monitoring organic carbon content in agricultural soils. Geoderma 144: 395–404. https://doi.org/10.1016/j.geoderma.2007.12.009.

Stevens, A., Udelhoven, T., Denis, A., Tychon, B., Lioy, R., Hoffmann, L., vanWesemael, B., 2010. Measuring soil organic carbon in croplands at regional scale using airborne imaging spectroscopy. Geoderma 158: 32–45.

Sullivan, D.G., Shaw, J.N., Rickman, D., 2005. IKONOS imagery to estimate surface soil property variability in two Alabama physiographies. Soil Science Society of America Journal 69: 1789–98.

Taconet, O., Ciarletti, V., 2007. Estimating soil roughness indices

on a ridge-and-furrow surface using stereo photogrammetry. Soil and Tillage Research 93: 64–76. https://doi.org/10.1016/j.still.2006.03.018.

Thomsen, L.M., Baartman, J.E.M., Barneveld, R.J., Starkloff, T., Stolte, J., 2014. Soil surface roughness: comparing old and new measuring methods and application in a soil erosion model. SOIL Discussions 1: 981–1012. https://doi.org/10.5194/soild-1-981-2014.

Thomsen, L.M., Baartman, J.E.M., Barneveld, R.J., Starkloff, T., Stolte, J., 2015. Soil surface roughness: comparing old and new measuring methods and application in a soil erosion model. Soil 1: 399–410. https://doi.org/10.5194/soil-1-399-2015.

VandenBygaart, A.J., Protz, R., 1998. The representative elementary area (REA) in studies of quantitative soil micromorphology. Geoderma, 89 (1999): 333–346.

Van der Meer, F., 1995. Spectral reflectance of carbonate mineral mixtures and bidirectional reflectance theory: Quantitative analysis techniques for application in remote sensing. Remote Sensing Reviews 13 (1-2): 67–94. https://doi.org/10.1080/02757259509532297.

Vannier, E., Gademer, A., Ciarletti, V., 2006. A new approach for roughness analysis of soil surfaces. 14th European Signal Processing Conference (EUSIPCO), Florence, Italy, 4-8 September.

Vaudour, E., Bel, L., Gilliot, J.M., Coquet, Y., Hadjar, D., Cambier, P., Michelin, J., Houot, S., 2013. Potential of SPOT multispectral satellite images for mapping topsoil organic carbon content over peri-urban croplands. Soil Science Society of America Journal 77 (6): 2122-2139. DOI: 10.2136/sssaj2013.02.0062.

Verhoest, N.E.C., Lievens, H., Wagner, W., Álvarez-Mozos, J., Moran, M.S., Mattia, F., 2008. On the soil roughness parameterization problem in soil moisture retrieval of bare surfaces from synthetic aperture radar. Sensors 8 (7): 4213–4248.

Vermang, J., Norton, L.D., Baetens, J.M., Huang, C., Cornelis, W.M., Gabriels, D., 2013. Quantification of soil surface roughness evolution under simulated rainfall. American Society of Agricultural Engineers 56: 505–514. https://doi.org/10.13031/2013.42670.

Vidal Vázquez, E., González, P.A., Miranda, V.J.G., 2005. Characterizing anisotropy and heterogeneity of soil surface microtopography using fractal models. Ecological Modelling 182 (3-4): 337–353. DOI: 10.1016/j.ecolmodel.2004.04.012.

Vidal Vázquez, E., Miranda, J.G. V, Alves, M.C., González, P.A., 2006. Effect of tillage on fractal indices describing soil surface microrelief of a Brazilian Alfisol. Geoderma 134: 428–439. https://doi.org/10.1016/j.geoderma.2006.03.012.

Vidal Vázquez, E., Miranda, V.J.G., Gonzalez, P.A., 2007. Describing soil surface microrelief by crossover length and fractal dimension. Nonlinear Processes in Geophysics 14 (3): 223-235. https://doi.org/10.5194/npg-14-223-2007.

Viscarra Rossel, R.A., McGlynn, R.N., McBratney, A.B., 2006. Determining the composition of mineral-organic mixes using UV–vis–NIR diffuse reflectance spectroscopy. Geoderma 137: 70–82.

Wagner, L.E., Yiming, Y., 1991. Digitization of profile meter photographs. Transactions of the ASAE 34 (2): 412–416.

Wegmuller, U., Santoro, M., Mattia, F., Balenzano, A., Satalino, G., Marzahn, P., Ludwig, R., Floury, N., 2011. Progress in the understanding of narrow directional microwave scattering of agricultural fields. Remote Sensing of Environment 115 (10): 2423–2433. https://doi.org/10.1016/j.rse.2011.04.026.

Wischmeier, W.H., Smith, D.D., 1978. Predicting Rainfall Erosion Losses - A Guide to Conservation Planning. Agriculture Handbook. Department of Agriculture Science and Education Administration, Washington, District of Columbia USA.

Young, I. M., Crawford, J. W., Rappoldt, C., 2001. New methods and models for characterising structural heterogeneity of soil. Soil and Tillage Research 61 (1-2): 33–45. https://doi.org/10.1016/S0167-1987(01)00188-X.

Zheng, B., Campbell, J.B., Serbin, G., Galbraith, J.M., 2014. Remote sensing of crop residue and tillage practices: Present capabilities and future prospects. Soil and Tillage Research 138: 26-34. https://doi.org/10.1016/j.still.2013.12.009.

Zhixiong, L., Nan, C., Perdok, U.D., Hoogmoed, W.B., 2005. Characterisation of soil profile roughness. Biosystems Engineering 91 (3): 369–377. https://doi.org/10.1016/j.biosystemseng.2005.04.004.

Zribi, M., Ciarletti, V., Taconet, O., Paillé, J., Boissard, P., 2000. Characterisation of the soil structure and microwave backscattering based on numerical three-dimensional surface representation: Analysis with a fractional Brownian model. Remote Sensing of Environment 72: 159–169. https://doi.org/10.1016/S0034-4257(99)00097-8.

DOI: http://dx.doi.org/10.17951/pjss.2018.51.2.229
Data publikacji: 2018-09-19 14:32:00
Data złożenia artykułu: 2018-04-10 23:32:37


Total abstract view - 1428
Downloads (from 2020-06-17) - PDF - 654



  • There are currently no refbacks.

Copyright (c) 2018 Karolina Herodowicz, Jan Piekarczyk

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.