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

January 9, 2022 Siddhant Goyal

Date of Publication: Aug 23, 2021

Author: by Yadira Pazmiao, Josa Juan de Felipe, Marc Vallba, Franklin Cargua and Luis Quevedo

Summary:

Paramo 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 paramo. We analyzed the performance of two nonparametric models (the CART decision tree, CDT, and multivariate adaptive regression curves, MARS) in the paramos 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 paramos. Comparing our results with the last report of the Ecuadorian Ministry of Environment (2012), we found that 9% of the paramo has been lost in the last 8 years. View Full-Text

Link to Full Reading:

https://www.mdpi.com/2071-1050/13/16/9462