IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i16p9462-d619951.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/16/9462/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/16/9462/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Allen Fleishman, 1978. "A method for simulating non-normal distributions," Psychometrika, Springer;The Psychometric Society, vol. 43(4), pages 521-532, December.
    2. 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.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Doole, Graeme J. & Romera, Alvaro J. & Leslie, Jennifer E. & Chapman, David F. & Pinxterhuis, Ina (J.B.). & Kemp, Peter D., 2021. "Economic assessment of plantain (Plantago lanceolata) uptake in the New Zealand dairy sector," Agricultural Systems, Elsevier, vol. 187(C).
    2. Headrick, Todd C. & Sheng, Yanyan & Hodis, Flaviu-Adrian, 2007. "Numerical Computing and Graphics for the Power Method Transformation Using Mathematica," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 19(i03).
    3. Pesaran, M. Hashem & Yamagata, Takashi, 2012. "Testing CAPM with a Large Number of Assets," IZA Discussion Papers 6469, Institute of Labor Economics (IZA).
    4. Ndip, Francis Ebai & Molua, Ernest L. & Mvodo, Meyo-Elise Stephanie & Nkendah, Robert & Djomo Choumbou, Raoul Fani & Tabetando, Rayner & Akem, Nina Fabinin, 2023. "Farmland Fragmentation, crop diversification and incomes in Cameroon, a Congo Basin country," Land Use Policy, Elsevier, vol. 130(C).
    5. Schinckus, Christophe, 2015. "The valuation of social impact bonds: An introductory perspective with the Peterborough SIB," Research in International Business and Finance, Elsevier, vol. 35(C), pages 104-110.
    6. Max Auerswald & Morten Moshagen, 2015. "Generating Correlated, Non-normally Distributed Data Using a Non-linear Structural Model," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 920-937, December.
    7. Weihua Fan & Gregory R. Hancock, 2012. "Robust Means Modeling," Journal of Educational and Behavioral Statistics, , vol. 37(1), pages 137-156, February.
    8. Mohan D. Pant & Todd C. Headrick, 2017. "Simulating Uniform- and Triangular- Based Double Power Method Distributions," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 6(1), pages 1-1.
    9. Mahul, Olivier, 2002. "Hedging Price Risk in the Presence of Crop Yield and Revenue Insurance," 2002 International Congress, August 28-31, 2002, Zaragoza, Spain 24881, European Association of Agricultural Economists.
    10. Löhndorf, Nils, 2016. "An empirical analysis of scenario generation methods for stochastic optimization," European Journal of Operational Research, Elsevier, vol. 255(1), pages 121-132.
    11. Shaobo Jin & Fan Yang-Wallentin, 2017. "Asymptotic Robustness Study of the Polychoric Correlation Estimation," Psychometrika, Springer;The Psychometric Society, vol. 82(1), pages 67-85, March.
    12. Schinckus, Christophe, 2018. "The valuation of social impact bonds: An introductory perspective with the Peterborough SIB," Research in International Business and Finance, Elsevier, vol. 45(C), pages 1-6.
    13. Foss, Tron & Jöreskog, Karl G. & Olsson, Ulf H., 2011. "Testing structural equation models: The effect of kurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2263-2275, July.
    14. Pelagatti, Matteo M. & Sen, Pranab K., 2013. "Rank tests for short memory stationarity," Journal of Econometrics, Elsevier, vol. 172(1), pages 90-105.
    15. Nicolas Depraetere & Martina Vandebroek, 2014. "Order selection in finite mixtures of linear regressions," Statistical Papers, Springer, vol. 55(3), pages 871-911, August.
    16. Emanuela Raffinetti & Pier Alda Ferrari, 2021. "A dependence measure flow tree through Monte Carlo simulations," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(2), pages 467-496, April.
    17. Al-Subaihi, Ali A., 2004. "Simulating Correlated Multivariate Pseudorandom Numbers," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 9(i04).
    18. Ringle, Christian M. & Götz, Oliver & Wetzels, Martin & Wilson, Bradley, 2009. "On the Use of Formative Measurement Specifications in Structural Equation Modeling: A Monte Carlo Simulation Study to Compare Covariance-Based and Partial Least Squares Model Estimation Methodologies," MPRA Paper 15390, University Library of Munich, Germany.
    19. Africa Borges del Rosal & Concepción San Luis & Alfonso Sánchez-Bruno, 2003. "Dominance Statistics: A Simulation Study on the d Statistic," Quality & Quantity: International Journal of Methodology, Springer, vol. 37(3), pages 303-316, August.
    20. Salaisook, Phastraporn & Faysse, Nicolas & Tsusaka, Takuji W., 2020. "Reasons for adoption of sustainable land management practices in a changing context: A mixed approach in Thailand," Land Use Policy, Elsevier, vol. 96(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:16:p:9462-:d:619951. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.