Digital Soil Mapping Technologies for Countries with Sparse Data Infrastructures

This chapter reviews some hardware and software for digital soil mapping. By hardware we mean various kinds of sensor and instrument which can give us better soil and scorpan data, and by software we mean mathematical or statistical models that can improve our spatial predictions. There are two approaches for the development of hardware for acquiring soil information: the top-down, and the bottom-up. The top-down approach asks which technologies are available and which variables can we measure that are related to scorpan factors. The bottom-up approach starts from a problem that we systematically analyse so as to identify the information that is needed to solve it. We then tackle the technical problems of collecting this information, and only at the end move to developing the field technology. We evaluate various software approaches to improve spatial prediction of soil properties or soil classes. Finally, the implication of using data-mining tools for the production of digital soil maps is discussed.

[1]  Richard J. Harper,et al.  Use of on-ground gamma-ray spectrometry to measure plant-available potassium and other topsoil attributes , 1999 .

[2]  R. Lark,et al.  On spatial prediction of soil properties in the presence of a spatial trend: the empirical best linear unbiased predictor (E‐BLUP) with REML , 2006 .

[3]  Budiman Minasny,et al.  Incorporating taxonomic distance into spatial prediction and digital mapping of soil classes , 2007 .

[4]  É. Martins,et al.  Chapter 17 Visible–NIR Hyperspectral Imagery for Discriminating Soil Types in the La Peyne Watershed (France) , 2006 .

[5]  C. Justice,et al.  Development of vegetation and soil indices for MODIS-EOS , 1994 .

[6]  S. Bie,et al.  Comparison of four independent soil surveys by air-photo interpretation, paphos area (Cyprus) , 1973 .

[7]  U. Schmidhalter,et al.  High resolution topsoil mapping using hyperspectral image and field data in multivariate regression modeling procedures , 2006 .

[8]  A. Verhoef.  Remote estimation of thermal inertia and soil heat flux for bare soil , 2004 .

[9]  Leo Breiman,et al.  Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author) , 2001, Statistical Science.

[10]  J. Wilford,et al.  Application of airborne gamma-ray spectrometry in soil/regolith mapping and applied geomorphology , 1997 .

[11]  Karin Viergever,et al.  Knowledge discovery from models of soil properties developed through data mining , 2006 .

[12]  J. L. Boettinger,et al.  Chapter 27 Pedogenic Understanding Raster Classification Methodology for Mapping Soils, Powder River Basin, Wyoming, USA , 2006 .

[13]  K. Shepherd,et al.  Global soil characterization with VNIR diffuse reflectance spectroscopy , 2006 .

[14]  Yasushi Yamaguchi,et al.  Overview of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) , 1998, IEEE Trans. Geosci. Remote. Sens..

[15]  P. A. Agbu,et al.  Soil Property Relationships with SPOT Satellite Digital Data in East Central Illinois , 1990 .

[16]  Gerard B. M. Heuvelink,et al.  The Kalman filter for the pedologist's tool kit (Retracted article) , 2006 .

[17]  Cristine L. S. Morgan,et al.  In Situ Characterization of Soil Clay Content with Visible Near‐Infrared Diffuse Reflectance Spectroscopy , 2007 .

[18]  E. M. Barnes,et al.  Multispectral data for mapping soil texture: possibilities and limitations. , 2000 .

[19]  R. M. Lark,et al.  Using expert knowledge with control of false discovery rate to select regressors for prediction of soil properties , 2007 .

[20]  Alex B. McBratney,et al.  Multivariate calibration of hyperspectral γ‐ray energy spectra for proximal soil sensing , 2007 .

[21]  Budiman Minasny,et al.  A conditioned Latin hypercube method for sampling in the presence of ancillary information , 2006, Comput. Geosci..

[22]  Ning Wang,et al.  Review: Wireless sensors in agriculture and food industry-Recent development and future perspective , 2006 .

[23]  Budiman Minasny,et al.  Estimation and potential improvement of the quality of legacy soil samples for digital soil mapping , 2007 .

[24]  Y. Pachepsky,et al.  Development of pedotransfer functions in soil hydrology , 2004 .

[25]  George Christakos,et al.  Modern Spatiotemporal Geostatistics , 2000 .

[26]  N. McKenzie,et al.  Spatial prediction of soil properties using environmental correlation , 1999 .

[27]  Philippe Lagacherie,et al.  Digital soil mapping : an introductory perspective , 2007 .

[28]  R. V. Rossel,et al.  Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties , 2006 .

[29]  Simon E. Cook,et al.  Use of airborne gamma radiometric data for soil mapping , 1996 .

[30]  E. Ben-Dor.  Quantitative remote sensing of soil properties , 2002 .

[31]  Christophe Delacourt,et al.  Using ASTER remote sensing data set for geological mapping, in Namibia , 2005 .

[32]  Peggy A. O'Day.  Molecular environmental geochemistry , 1999 .

[33]  Susan L. Ustin,et al.  Multivariate statistical classification of soil spectra , 1996 .

[34]  D. Corwin,et al.  Apparent soil electrical conductivity measurements in agriculture , 2005 .

[35]  A. P. Annan,et al.  Ground-penetrating radar for high-resolution mapping of soil and rock stratigraphy , 1989 .

[36]  Alex B. McBratney,et al.  Using AVHRR images for spatial prediction of clay content in the lower Namoi Valley of eastern Australia. , 2000 .

[37]  Tim R. McVicar,et al.  Preprocessing EO-1 Hyperion hyperspectral data to support the application of agricultural indexes , 2003, IEEE Trans. Geosci. Remote. Sens..

[38]  Viacheslav I. Adamchuk,et al.  On-the-go soil sensors for precision agriculture , 2004 .

[39]  Leo Breiman,et al.  Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author) , 2001 .

[40]  Robert Tibshirani,et al.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.

[41]  Abdelaziz Merzouk,et al.  Comparaison des capteurs ASTER et ETM+ pour la cartographie de la dégradation des sols à l'aide de l'indice LDI , 2006 .

[42]  Chris Moran,et al.  Disaggregation of polygons of surficial geology and soil maps using spatial modelling and legacy data , 2001 .

[43]  Junhua Li,et al.  A rule-based method for mapping Canada's wetlands using optical, radar and DEM data , 2005 .

[44]  Budiman Minasny,et al.  On digital soil mapping , 2003 .

[45]  R. Dickinson,et al.  Relating MODIS‐derived surface albedo to soils and rock types over Northern Africa and the Arabian peninsula , 2002 .

[46]  D. Marx,et al.  Direct measurement of soil chemical properties on-the-go using ion-selective electrodes , 2005 .