Method development to extract spatial association structure from soil polygon maps
Abstract
Existing soil information systems contain mainly qualitative data on soilscapes, however, quantitative data would be necessary to more effectively guide digital soil mapping efforts. Detailed analysis of small scale overview maps offers the most appropriate way to delineate soilscapes where they are available. In our study, the genetic soil map of Hungary have been used which displays the most complete representation of the Hungarian Soil Classification System. Our goal was to analyse spatial association structure based on the boundary segments between soil polygons. We transformed the polygons into lines. The features of each line segment were the names (or codes) of the soil polygons on both sides. After omission soils with low representation (less than three polygons) and boundaries beside state border, forests and cities, 69 soil units were retained. We calculated a similarity matrix among soil types based on logarithm of ratios between existing segment lengths and theoretical segment lengths. The theoretical lengths were calculated with a Chi-squared calculation by using sums of lengths in rows and columns in the 69 × 69 matrix. The similarity matrix was converted into dissimilarity matrix to distinguish between complete dissimilarity (missing values) and complete similarity (main diagonal). Dissimilarity matrix was clustered and represented in a form of dendrogram both in original form and after dimension reduction with multidimensional scaling method. Our method has resulted a promising approach for delineating soilscapes in presence of overview soil maps. The study resulted fuzzy soilscapes with broad transition zones. The method should be refined by using variable sized moving window method and by combining boundary data with terrain, geology etc.
References
AIR 2013. Agrár-környezetgazdálkodási Indormációs rendszer (Information System for the Agri-environmental schemes). Nyilvános térképek (Open access maps). (in Hungarian)
Behrens, T., Schneider, O., Lösel, G., Scholten, T., Hennings, V., Felix-Henningsen, P. and Hartwich, R. 2009. Analysis on pedodiversity and spatial subset representativity - the German soil map 1:1 000 000. Journal of Plant Nutrion and Soil Science 172. 91-100. https://doi.org/10.1002/jpln.200700339
Boyack, K.W., Klavans, R. and Börner, K. 2005. Mapping the backbone of science. Scientometrics 64. (3): 351-374. https://doi.org/10.1007/s11192-005-0255-6
Bui, E. 2004. Soil survey as a knowledge system. Geoderma 120. (1-2): 17-26. https://doi.org/10.1016/j.geoderma.2003.07.006
Buol, S.W., Hole, F.D. and McCracken, R.J. 1973. Soil genesis and classification. Ames, University Press, IA, USA. 404 p.
Cambule, A.H., Rossiter, D.G. and Stoorvogel, J.J. 2013. A methodology for digital soil mapping in poorly-accessible areas. Geoderma 192. 341-353. https://doi.org/10.1016/j.geoderma.2012.08.020
Campbell, J.B. and Edmonds, W.J. 1984. The missing geographic dimension to soil taxonomy. Annals of the Association of American Geographers 74. 83-97. https://doi.org/10.1111/j.1467-8306.1984.tb01436.x
Chrisman, N.R. 1989. Modelling error in overlaid categorical maps. In Accuracy of spatial databases. Eds.: Goodchild, M. and Gopal S. London, Taylor & Francis, 21-34.
Creamer, R., Simo, I., Reidy, B., Carvalho, J., Fealy, R., Hallett, S., Jones, R., Holden, A., Holden, N., Hannam, J., Massey, P., Mayr, T., McDonald, E., O'Rourke, S., Sills, P., Truckell, I., Zawadzka, J. and Schulte R. 2010. Irish Soil Information System Synthesis Report. No. 130, Johnstown Castle, Environmental Protection Agency, Ireland.
Dobos, E., Daroussin, J. and Montanarella, L. 2005. An SRTM-based procedure to delineate SOTER Terrain Units on 1:1 and 1:5 million scales. EUR 21571 EN, Luxembourg, Office for Official Publications of the European Communities. 55 p.
Dobos, E., Daroussin, J. and Montanarella, L. 2010. A quantitative procedure for building physiographic units supporting a global SOTER database. Hungarian Geographical Bulletin 59. (2): 181-205.
Dobos, E., Montanarella, L., Negre, T. and Michéli, E. 2001. A regional scale soil mapping approach using integrated AVHRR and DEM data. International Journal of Applied Earth Observation and Geoinformation 3. (1): 30-42. https://doi.org/10.1016/S0303-2434(01)85019-4
Finke, P., Hartwich, R., Dudal, R., Ibanez, J., Jamagne, M., King, D., Montanarella, L. and Yassoglou, N. 2001. Georeferenced Soil Database for Europe. Manual of procedures. Version 1.1. European Soil Bureau, Research Report No. 5. EUR 18092 EN. European Communities
Grinand, C., Arrouays, D., Laroche, B. and Martin, M.P. 2008. Extrapolating regional soil landscapes from an existing soil map: Sampling intensity, validation procedures, and integration of spatial context. Geoderma 143. (1-2): 180-190. https://doi.org/10.1016/j.geoderma.2007.11.004
Häring, T., Dietz, E., Osenstetter, S., Koschitzki, Th. and Schröder, B. 2012. Spatial disaggregation of complex soil map units: A decision-tree based approach in Bavarian forest soils. Geoderma 185-186. 37-47. https://doi.org/10.1016/j.geoderma.2012.04.001
Hartigan, J.A. 1967. Representation of similarity matrices by trees. Journal of the American Statistical Association 62. (320.) 1140-1158. https://doi.org/10.1080/01621459.1967.10500922
Hengl, T., Toomanian, N., Reuter, H.I. and Malakouti, M.J. 2007. Methods to interpolate soil categorical variables from profi le observations: lessons from Iran. Geoderma 140. 417-427. https://doi.org/10.1016/j.geoderma.2007.04.022
Hewitt, A.E., 1993. Predictive modelling in soil survey. Soil and Fertilizers 56. (3): 305-314.
Hewitt, A.E., Barringer, J.R.F., Forrester, G.J. and McNeill, S.J. 2010. Soilscapes basis for digital soil mapping in New Zealand. In Digital Soil Mapping Bridging Research, Environmental Application, and Operation. Eds.: Boettinger, J.L., Howell, D.W., Moore, A.C., Hartemink, A.E. and Kienast- Brown, S. Dortdrecht, Springer, The Netherlands, 297-308. https://doi.org/10.1007/978-90-481-8863-5_24
Hole, F.D. 1978. An approach to landscape analysis with emphasis on soils. Geoderma 21. 1-23. https://doi.org/10.1016/0016-7061(78)90002-2
Horváth, B., Izsó I., Jassó, F., Király, L., Parászka, L. and Várallyay, Gy. 1987. Guide to conduct nationwide fine-scale soil mapping. Melioráció-öntözés és talajvédelem. Budapest, Agroinform.
Horváth, B., Izsó, I., Jassó, F., Király, L., Parászka, L. and Szabóné Kele, G. 1989. Guide to conduct nationwide fine-scale soil mapping. Melioráció-öntözés és tápanyaggazdálkodás. Budapest, Agroinform. Georgikon Napok, LIV. VII. szekció, vízgazdálkodás.
Hudson, B.D. 1990. Concepts of soil mapping and interpretation. Soil Survey Horizons 31. (3): 63-72. https://doi.org/10.2136/sh1990.3.0063
ISRIC 1993. Global and National Soils and Terrain Digital Databases (SOTER). Procedures Manual. UNEP-ISSSISRIC-FAO. ISRIC. Wageningen, Netherlands. 115 p.
IUSS Working Group WRB 2007. World Reference Base for Soil Resources 2006, first update 2007. World Soil Resources Reports No. 103. Rome, FAO.
IUSS Working Group WRB 2014. World Reference Base for Soil Resources 2014. International soil classification system for naming soils and creating legends for soil maps. World Soil Resources Reports No. 106. Rome, FAO.
Jenny, H. 1941. Factors of Soil Formation, A System of Quantitative Pedology. New York, McGraw-Hill, 191 p.
Krasilnikov, P., Arnold, R. and Michéli, E. 2009. Soil Classification of Hungary. In A handbook of soil terminology, correlation and classification. Eds.: Arnold, R., Shoba, S., Krasilnikov, P. and Marti, J.J.I. London, Earthscan, Sterling, VA.
Lagacherie, P., Robbez-Masson, J.M., Nguyen-The, N. and Barthes, J.P. 2001. Mapping of reference area representativity using a mathematical soilscape distance. Geoderma 101. 105-118. https://doi.org/10.1016/S0016-7061(00)00101-4
Lilburne, L.R., Hewitt, A.E. and Webb, T.W. 2012. Soil and informatics science combine to develop S-map: A new generation soil information system for New Zealand. Geoderma 170. 232-238. https://doi.org/10.1016/j.geoderma.2011.11.012
Mattyasovszky, J., Görög, L. and Stefanovits, P. 1953. 1:200 000 m.a. mezőgazdasági talajtérkép (Agricultural soil map at a scale of 1:200 000). Budapest, Tervgazdasági Könyvkiadó.
Mcbratney, A., Mendonca Santos, M.L. and Minasny, B. 2003. On digital soil mapping. Geoderma 117. 3-52. https://doi.org/10.1016/S0016-7061(03)00223-4
McBratney, A.B., Hart, G.A. and McGarry, D. 1991. The use of region partitioning to improve the representation of geostatistically mapped soil attributes. Journal of Soil Science 42. 513-532. https://doi.org/10.1111/j.1365-2389.1991.tb00427.x
McSweeney, K., Slater, B. K., Hammer, R.D., Bell, J.C., Gessler, P.E., Petersen, G.W. 1994. Towards a new framework for modelling the soil-landscape continuum. In Factors of Soil Formation: A 50th Anniversary Retrospective. Eds.: Amundson, R., Harden, J. and Singer, M. SSSA Special Publication 33. 127-145. https://doi.org/10.2136/sssaspecpub33.c8
MÉM (1983-1988). Magyarország agrotopográfiai térképe 1:100 000 m.a. (Agrotopographic map of Hungary 1:100 000). Budapest, MÉM Országos Földügyi és Térképészeti Hivatal, 84 térképlap/mapsheet, 51 x 66 cm.
MÉM-NAK 1983. Magyarország genetikai talajtérképe 1:200 000 m.a. (Genetic soil map of Hungary 1:200,000). Budapest, Mezőgazdasági és Élelmezésügyi Minisztérium.
Mendonça-Santos, M.D.L., Santos, H.G., Dart, R.O. and Pares, J.G. 2008. Digital mapping of soil classes in Rio de Janeiro State, Brazil: data, modelling and prediction. In Digital Soil Mapping with Limited Data. Eds.: Hartemink, A.E., Mcbratney, A. and Mendonça-Santos, M.L. Dordrecht, Springer, 381-396. https://doi.org/10.1007/978-1-4020-8592-5_34
Michéli, E., Fuchs, M., Hegymegi, P. and Stefanovits, P. 2006. Classification of the major soils of Hungary and their correlation with the World Reference Base for Soil Resources (WRB). Agrokémia és Talajtan 55. (1): 19-28. https://doi.org/10.1556/Agrokem.55.2006.1.3
Pásztor, L., Bakacsi, Zs., Laborczi, A. and Szabó, J. 2013. Downscaling of categorical soil maps with the aid of auxiliary spatial soil information and data mining methods. Agrokémia és Talajtan 62. 205-218. https://doi.org/10.1556/Agrokem.62.2013.2.3
Pecora, L.M., Carroll, T.L. and Heagy, J.F. 1995. Statistics for mathematical properties of maps between time series embeddings. Physical Review E 52. (4): 3420. p. https://doi.org/10.1103/PhysRevE.52.3420
Pontius Jr, R.G. 2002. Statistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolutions. Photogrammetric Engineering and Remote Sensing 68. (10): 1041-1050.
Schmidt, K., Behrens, T., Friedrich, K. and Scholten, T. 2010. A method to generate soilscapes from soil maps. Journal of Plant Nutrition and Soil Science 173. (2): 163-172. https://doi.org/10.1002/jpln.200800208
Scull, P., Franklin, J. and Chadwick, O.A. 2005. The application of classification tree analysis to soil type prediction in a desert landscape. Ecological Modelling 181. 1-15. https://doi.org/10.1016/j.ecolmodel.2004.06.036
Scull, P., Franklin, J., Chadwick, O.A. and McArthur, D. 2003. Predictive soil mapping: a review. Progress in Physical Geography 27. (2): 171-197. https://doi.org/10.1191/0309133303pp366ra
Sisák, I. and Benő, A. 2012. Digital publication of the 1:200 000 scale agricultural soil map on the Georgikon Mapserver. LIV. Georgikon Napok, Keszthely, 2012. okt. 11-12. Papers, 431-436.
Sisák, I. and Benő, A. 2014. Probability-based harmonization of digital maps to produce conceptual soil maps. Agrokémia és Talajtan 63. (1): 89-98. https://doi.org/10.1556/Agrokem.63.2014.1.10
Sun, X.L., Zhao, Y.G., Zhang, G.L., Wu, S.C., Man, Y.B. and Wong, M.H. 2011. Application of a digital soil mapping method in producing soil orders on mountain areas of Hong Kong based on legacy soil data. Pedosphere 21. (3): 339-350. https://doi.org/10.1016/S1002-0160(11)60134-3
Várallyay, Gy., Szűcs, L., Murányi, A., Rajkai, K. and Zilahy, P. 1979. Magyarország termőhelyi adottságait meghatározó talajtani tényezők 1:100 000 méretarányú térképe I. (1:100,000 map of the properties determining soil productivity in Hungary I.) Agrokémia és Talajtan 28. 363-384.
Várallyay, Gy., Szűcs, L., Murányi, A., Rajkai, K. and Zilahy, P. 1980. Magyarország termőhelyi adottságait meghatározó talajtani tényezők 1:100 000 méretarányú térképe II. (1:100,000 map of the properties determining soil productivity in Hungary II.) Agrokémia és Talajtan 29. 35-76.
Yu, J., Pressoir, G., Briggs, W.H., Bi, I.V., Yamasaki, M., Doebley, J.F., McMullen, M.D., Gaut, B.S., Nielsen, D.M., Holland, J.B., Kresovich, S. and Buckler, E.S. 2005. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics 38. (2): 203-208. https://doi.org/10.1038/ng1702
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