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Updating Legacy Soil Maps for Climate Resilient Agriculture: A Case of Kilombero Valley, Tanzania

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Climate Change and Multi-Dimensional Sustainability in African Agriculture

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Abstract

Since the first documented soil survey in Tanzania by Milne (J Ecol 35:192–265, 1936), a number of other soil inventory exercises at different scales have been made. The main challenge has been the fragmented nature of the often outdated detailed soil maps and small-scale less-informative country-wide soil maps. Recent advances in information and computational technology have created vast potential to collect, map, harness, communicate and update soil information. These advances present favorable conditions to support the already popular shift from qualitative (conventional) to quantitative (digital) soil mapping (DSM). In this study, two decision tree machine learning algorithms, J48 and Random Forest (RF), were applied to digitally predict k-means numerically classified soil clusters to update a soil map produced in 1959. Predictors were derived from 1 arc SRTM digital elevation data and a 5 m RapidEye satellite image. J48 and RF predicted the soil units of the legacy maps with greater detail. However, RF showed superiority for predicting clusters J48 could not predict and for showing higher pixel contiguity. No significant difference (P = 0.05) was observed between the soil properties of the predicted soil clusters and the actual field validation points. Young soils (Entisols and Inceptisols) were found to occupy about 56 % of the study site’s 30,000 ha followed by Alfisols, Mollisols and Vertisols at 31, 9 and 4 %, respectively. This study demonstrates the usefulness of DSM techniques to update conventionally prepared legacy maps to offer soil information at improved detail to agricultural land use planners and decision makers of Tanzania to make evidence-based decisions for climate-resilient agriculture and other land uses.

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Author information

Authors and Affiliations

  1. Department of Soil and Geological Sciences, Sokoine University of Agriculture, P.O. Box 3008, Morogoro, Tanzania

    Boniface H. J. Massawe & Abel K. Kaaya

  2. School of Environment and Natural Resources, The Ohio State University, 210 Kottman Hall, 2021 Coffey Road, Columbus, Ohio, 43210, USA

    Brian K. Slater & Sakthi K. Subburayalu

  3. World Agroforestry Centre, United Nations Avenue, Gigiri, Nairobi, Kenya

    Leigh Winowiecki

Authors
  1. Boniface H. J. Massawe
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  2. Brian K. Slater
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  3. Sakthi K. Subburayalu
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  4. Abel K. Kaaya
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  5. Leigh Winowiecki
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Corresponding author

Correspondence to Boniface H. J. Massawe .

Editor information

Editors and Affiliations

  1. SENR-CMASC, The Ohio State University, Columbus, Ohio, USA

    Rattan Lal

  2. AEDE/CFAES, The Ohio State University, Columbus, Ohio, USA

    David Kraybill

  3. College of Food, Agricultural, and Environmental Sciences, The Ohio State University, Columbus, Ohio, USA

    David O. Hansen

  4. Norwegian University of Life Sciences, Ås, Norway

    Bal Ram Singh

  5. Sokoine University of Agriculture, Morogoro, Tanzania

    Theodosy Mosogoya

  6. Norwegian University of Life Sciences, Ås, Norway

    Lars Olav Eik

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Massawe, B.H.J., Slater, B.K., Subburayalu, S.K., Kaaya, A.K., Winowiecki, L. (2016). Updating Legacy Soil Maps for Climate Resilient Agriculture: A Case of Kilombero Valley, Tanzania. In: Lal, R., Kraybill, D., Hansen, D., Singh, B., Mosogoya, T., Eik, L. (eds) Climate Change and Multi-Dimensional Sustainability in African Agriculture. Springer, Cham. https://doi.org/10.1007/978-3-319-41238-2_19

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