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Identification of a Set of Variables for the Classification of Páramo Soils Using a Nonparametric Model, Remote Sensing, and Organic Carbon

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  • Yadira Pazmiño

    (Department of Mining, Industrial and ICT Engineering, Manresa School of Engineering, Universitat Politècnica de Catalunya, 08242 Manresa, Spain)

  • José Juan de Felipe

    (Department of Mining, Industrial and ICT Engineering, Manresa School of Engineering, Universitat Politècnica de Catalunya, 08242 Manresa, Spain)

  • Marc Vallbé

    (Department of Mining, Industrial and ICT Engineering, Manresa School of Engineering, Universitat Politècnica de Catalunya, 08242 Manresa, Spain)

  • Franklin Cargua

    (Research and Development Group for the Environment and Climate Change, Escuela Superior Politécnica de Chimborazo, Riobamba 060150, Ecuador)

  • Luis Quevedo

    (Tourism Department, Universidad Nacional de Chimborazo UNACH, Riobamba 060150, Ecuador)

Abstract

Páramo ecosystems harbor important biodiversity and provide essential environmental services such as water regulation and carbon sequestration. Unfortunately, the scarcity of information on their land uses makes it difficult to generate sustainable strategies for their conservation. The purpose of this study is to develop a methodology to easily monitor and document the conservation status, degradation rates, and land use changes in the páramo. We analyzed the performance of two nonparametric models (the CART decision tree, CDT, and multivariate adaptive regression curves, MARS) in the páramos of the Chambo sub-basin (Ecuador). We used three types of attributes: digital elevation model (DEM), land use cover (Sentinel 2), and organic carbon content (Global Soil Organic Carbon Map data, GSOC) and a categorical variable, land use. We obtained a set of selected variables which perform well with both models, and which let us monitor the land uses of the páramos. Comparing our results with the last report of the Ecuadorian Ministry of Environment (2012), we found that 9% of the páramo has been lost in the last 8 years.

Suggested Citation

  • Yadira Pazmiño & José Juan de Felipe & Marc Vallbé & Franklin Cargua & Luis Quevedo, 2021. "Identification of a Set of Variables for the Classification of Páramo Soils Using a Nonparametric Model, Remote Sensing, and Organic Carbon," Sustainability, MDPI, vol. 13(16), pages 1-22, August.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:16:p:9462-:d:619951
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    1. Tesfaye C. Cholo & Luuk Fleskens & Diana Sietz & Jack Peerlings, 2018. "Is Land Fragmentation Facilitating or Obstructing Adoption of Climate Adaptation Measures in Ethiopia?," Sustainability, MDPI, vol. 10(7), pages 1-14, June.
    2. Allen Fleishman, 1978. "A method for simulating non-normal distributions," Psychometrika, Springer;The Psychometric Society, vol. 43(4), pages 521-532, December.
    3. Henk Ritzema & Hilary Kirkpatrick & Jakub Stibinger & Hans Heinhuis & Heinrich Belting & Raymond Schrijver & Herbert Diemont, 2016. "Water Management Supporting the Delivery of Ecosystem Services for Grassland, Heath and Moorland," Sustainability, MDPI, vol. 8(5), pages 1-19, May.
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    1. Julie Echeverría-Puertas & Magdy Echeverría & Franklin Cargua & Theofilos Toulkeridis, 2023. "Spatial Dynamics of the Shore Coverage within the Zone of Influence of the Chambo River, Central Ecuador," Land, MDPI, vol. 12(1), pages 1-21, January.

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