Abstract
This chapter introduces the concepts of data rescue of legacy soil surveys, here defined as a simple conversion to archival format by scanning or direct entry into a database, and data renewal, here defined as the process of bringing these surveys up to modern standards by taking advantage of technological and conceptual advances in geoinformation technology. This is especially important in areas with sparse soil data infrastructure, as it is both more likely that the data will be lost and less likely that a new survey can be commissioned. Digital Soil Mapping (DSM) techniques, although designed for new surveys, can play an important role in data rescue and renewal, in particular as geodetic control for a GIS coverage, as a medium-resolution elevation model (DEM) and derived terrain parameters to adjust terrain-related boundaries, and synoptic satellite imagery to adjust vegetation or landuse-related boundaries. The semantic issues raised by soil-landscape modelling within DSM are especially important for data renewal and integration with supplementary surveys. As with DSM in general, a data renewal exercise may require cultural and institutional change in traditional soil survey organization.
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References
Batjes, N. H. (Ed.), 1995. A homogenized soil data file for global environmental research: a subset of FAO, ISRIC and NRCS profiles (Version 1.0). Working Paper and Preprint 95/10b. International Soil Reference and Information Centre (ISRIC), Wageningen (NL).
Batjes, N. H., Al-Adamat, R., Bhattacharyya, T., Bernoux, M., Cerri, C. E. P., Gicheru, P., Kamoni, P., Milne, E., Pal, D. K., Rawajfih, Z., 2007. Preparation of consistent soil data sets for modelling purposes: Secondary SOTER data for four case study areas. Agriculture, Ecosystems&Environment 122, 26–34.
Bellamy, P. H., Loveland, P. J., Bradley, R. I., Lark, R. M., Kirk, G. J. D., 2005. Carbon losses from all soils across England and Wales 1978–2003. Nature 437, 245–248.
Bui, E. N., 2004. Soil survey as a knowledge system. Geoderma 120, 17–26.
Bui, E. N., Moran, C. J., 2001. Disaggregation of polygons of surficial geology and soil maps using spatial modelling and legacy data. Geoderma 103, 79–94.
Coote, D., MacDonald, K., 2000. The Canadian soil database. In: Sumner, M. (Ed.), Handbook of Soil Science. CRC Press, Boca Raton, FL, pp. H-41–H-51.
D’Avelo, T. P., McLeese, R. L., 1998. Why are those lines placed where they are?: An investigation of soil map recompilation methods. Soil Survey Horizons 39, 119–126.
Davis, R. E., Foote, F. S., Anderson, J. M., Mikhail, E. M., 1981. Surveying: Theory and Practice, 6th Edition. McGraw-Hill, NewYork.
de Man, W. H. E., 2006. Understanding SDI: complexity and institutionalization. International Journal of Geographical Information Science 20, 329–343.
Dent, D. L., Ahmed, F. B., 1995. Resurrection of soil surveys: a case study of the acid sulphate soils of The Gambia. I. Data validation, taxonomic and mapping units. Soil Use and Management 11, 69–76.
Forbes, T., Rossiter, D., Van Wambeke, A., 1982. Guidelines for evaluating the adequacy of soil resource inventories. SMSS Technical Monograph 4. Cornell University Department of Agronomy, Ithaca, New York.
Gorokhovich, Y., Voustianiouk, A., 2006. Accuracy assessment of the processed SRTM-based elevation data by CGIAR using field data from USA and Thailand and its relation to the terrain characteristics. Remote Sensing of Environment 104, 409–415.
Groot, R., McLaughlin, J. (Eds.), 2000. Geospatial Data Infrastructure: Concepts, Cases, and Good Practice. Oxford University Press, Oxford.
Hengl,T., Rossiter, D., 2003. Supervised landform classification to enhance and replace photo-interpretation in semi-detailed soil survey. Soil Science Society of America Journal 67, 1810–1822.
Heuvelink, G. B. M., Webster, R., 2001. Modelling soil variation: past, present, and future. Geoderma 100, 269–301.
Ibañez, J. J., Ruiz Ramos, M., Zinck, J. A., Bru, A., 2005. Classical pedology questioned and defended. Eurasian Soil Science 38(Supplement 1), 75–80.
ISRIC, 1995. SOTER database of Kenya. Kenya Soil Survey, ISRIC – World Soil Information, Wageningen (NL), Nairobi.
Kenya Departmentof Agriculture, 1961. Soil survey of the East Konyango area: parts of survey of Kenya, G.S.G.S., 4786 series, sheets 129/II, 129/IV, 130/I&120/III. Map&Report, Government Printer, Nairobi.
Krol, B., Rossiter, D. G., Siderius,W., 2006. Ontology-based multi-source data integration for predictive soil mapping. In: Lagacherie, P., McBratney, A., Voltz, M. (Eds.), Digital Soil Mapping: An Introductory Perspective. Developments in Soil Science 31. Elsevier, Amsterdam, 119–133.
Lagacherie, P., Andrieux, P., Bouzigues, R., 1996. Fuzziness and uncertainty of soil boundaries: from reality to coding in GIS. In: Burrough, P. A., Frank, A. U. (Eds.), Geographic objects with indeterminate boundaries. GISDATA 2. Taylor&Francis, London, pp. 275–286.
MacMillan, R. A., Pettapiece, W. W., Nolan, S. C., Goddard, T. W., 2000. A generic procedure for automatically segmenting landforms into landform elements using DEMs, heuristic rules and fuzzy logic. Fuzzy Sets and Systems 113, 81–109.
McBratney, A. B., Mendonça Santos, M. L., Minasny, B., 2003. On digital soil mapping. Geo-derma 117, 3–52.
Metternicht, G. I., Zinck, J. A., 2003. Remote sensing of soil salinity: potentials and constraints. Remote Sensing of Environment 85, 1–20.
Mugnier, C., 2003. Grids and datums: Republic of Kenya. Photogrammetric Engineering & Remote Sensing 69, 593–597.
Oksanen, J., Sarjakoski, T., 2005. Error propagation of DEM-based surface derivatives. Comput-ers&Geosciences 31, 1015–1027.
Rabus, B., Eineder, M., Roth, A., Bamler, R., 2003. The shuttle radar topography mission – a new class of digital elevation models acquired by spaceborne radar. ISPRS Journal of Pho-togrammetry and Remote Sensing 57, 241–262.
Rossiter, D. G., 2004. Digital soil resource inventories: status and prospects. Soil Use and Management 20, 296–301.
Rossiter, D. G., 2007. A compendium of on-line soil survey information. On-line document, http://www.itc.nl/personal/rossiter/research/rsrch_ss.html; Accessed: 17-October-2007.
Rossiter, D. G., Hengl, T., 2002. Creating geometrically-correct photo-interpretations, photomosaics, and base maps for a project GIS; 3rd revised version. Technical note, International Institute for Geo-information Science and Earth Observation (ITC), http://www. itc.nl/personal/rossiter/teach/sis/TN_Georef_wFigs_Screen_V3.pdf; Accessed: 16-October-2007.
Schmidt, J., Hewitt, A., 2004. Fuzzy land element classification from DTMs based on geometry and terrain position. Geoderma 121, 243–256.
Scull, P., Franklin, J., Chadwick, O., McArthur, D., 2003. Predictive soil mapping: a review. Progress in Physical Geography 27, 171–197.
Selvaradjou, S.-K., Montanarella, L., Spaargaren, O., Dent, D., 2005a. European Digital Archive of Soil Maps (EuDASM) – Soil Maps of Africa. EUR 21657EN. Office for Official Publications of the European Communities, Luxembourg.
Selvaradjou, S.-K., Montanarella, L., Spaargaren, O., Dent, D., 2005b. European Digital Archive of Soil Maps (EuDASM) – Soil Maps of Asia. EUR 21823 EN. Office for Official Publications of the European Communities, Luxembourg.
Selvaradjou, S.-K., Montanarella, L., Spaargaren, O., Dent, D., 2005c. European Digital Archive of Soil Maps (EuDASM) – Soil Maps of Latin America and Carribean Islands. EUR 21822 EN. Office for Official Publications of the European Communities, Luxembourg.
Soil Survey Staff, 2007. Soil Survey Geographic (SSURGO) Database. http:// soildatamart.nrcs.usda.gov; Accessed: 16-October-2007.
Thompson, J. A., Bell, J. C., Butler, C. A., 2001. Digital elevation model resolution: effects on terrain attribute calculation and quantitative soil-landscape modeling. Geoderma 100, 67–89.
Thorp, J., Smith, G., 1949. Higher categories of soil classification. Soil Science 67, 117–126.
Wilson, J. P., Gallant, J. (Eds.), 2000. Terrain analysis: principles and applications. Wiley&Sons, New York.
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Rossiter, D. (2008). Digital Soil Mapping as a Component of Data Renewal for Areas with Sparse Soil Data Infrastructures. In: Hartemink, A.E., McBratney, A., Mendonça-Santos, M.d. (eds) Digital Soil Mapping with Limited Data. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-8592-5_6
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