Abstract

The scarcity of information that allows for understanding the importance of natural resources from an economic approach is often a limitation to establishing parameters related to environmental investment in conservation plans. This study proposes a methodology that allows for modeling the variability of páramo land uses and the EV of the Chambo-Ecuador sub-basin from bioeconomic monitoring that links the economic rent of páramo land uses with remote sensing tools and geographic information systems. Multilayer Perception, Markov Chains, and Automata Cells algorithms were efficient for the detection of land uses in páramo; the normalized differential humidity index was the most relevant variable to identify crops, showing that leaf properties and water stress are linked to crop yields in the Andean region. The páramo decreased by 13% between 2000 and 2010, increasing its degradation to 19% between 2010 and 2020. A 28% reduction is expected between 2000 and 2030; the EV between 2000 and 2020 was $2.86 × 108 and $2.59 × 108 respectively. In 2030, EV is expected to decrease to $2.48 × 108. Transitions in land use and EV are associated with productive dynamics, which decrease environmental services, such as water retention and carbon storage, intensifying changes in the ecosystem climate.

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