Please login first
Evaluation of Land Cover and Use through Artificial Intelligence in the Premontane Humid Forest of the Munchique Natural Reserve, Quilichao River Basin, Cauca, Colombia
* 1 , 1 , 2 , 3 , 4
1  Department of Geography/Faculty of Humanities/Meléndez Campus, Universidad del Valle, Santiago de Cali 760034, Colombia
2  Department of Mathematics/Facultad de Ciencias Naturales y Exactas/Campus Meléndez, Universidad del Valle, Santiago de Cali 760034, Colombia
3  Faculty of Engineering and Administration/Palmira Campus, Universidad Nacional de Colombia, Palmira 763537, Colombia
4  Faculty of Engineering / School of Natural Resources and Environmental Engineering (EIDENAR) /Meléndez Campus, Universidad del Valle, Santiago de Cali 760034, Colombia
Academic Editor: Giorgos Mallinis

Abstract:

Land cover and land use assessment is crucial for the sustainable management of natural resources and biodiversity conservation, especially in diverse and fragile ecosystems such as the Andean forests. This research aimed to identify changes in vegetation cover and their impact on land use in the Munchique Natural Reserve, in the Quilichao river basin, Cauca, Colombia, an area that harbors high biodiversity and numerous ecosystem services.

A land use and land cover classification (LULC) was performed using Sentinel 2 satellite imagery for the period 2018-2021, using ArcMap 10.8 and QGIS 2.18 software with the MOLUSCE plugin. A multi-layer artificial neural network (ANN) was used to predict changes up to the years 2030 and 2050, allowing to assess future land use dynamics. The land transition analysis showed a reduction of 102 ha of dense vegetation and 17 ha of pasture between 2019 and 2021, due to agricultural expansion.

The MOLUSCE plugin simulated land cover for 2030 and 2050. The validation of the simulation showed an accuracy of 98.70% and a kappa coefficient of 0.99487, indicating high accuracy in predicting land cover change. Future predictions suggest the loss of more than 300 ha of dense vegetation between 2021 and 2030, and 437.26 ha between 2021 and 2050, in addition to an increase of approximately 800 ha of crops in the same period. These impacts must be integrated into planning to ensure biodiversity and ecosystem services.

The results of this research provide key information to identify territorial conflicts and contribute to the sustainable management of natural resources in this region of Colombia.

Keywords: Land Cover; Land Use; Artificial neural network (ANN); MOLUSCE; Ecosystem Services
Comments on this paper
DAVID MUNOZ
The research titled "Evaluation of Land Cover and Use through Artificial Intelligence in the Premontane Humid Forest of the Munchique Natural Reserve, Quilichao River Basin, Cauca, Colombia" is crucial for both Cauca and Colombia for several reasons:

Biodiversity Protection: This study will help monitor land use changes in the highly biodiverse and vulnerable premontane humid forest, crucial for preserving endemic species and ecosystems.

Artificial Intelligence for Land Management: Using AI allows more precise and efficient monitoring, providing valuable tools for decision-making. This approach can be replicated in other protected areas across Colombia.

Climate Change Mitigation: The study will shed light on how local land changes impact carbon sequestration and water cycles, crucial for combating climate change.

Informed Decision-Making: The results will support better territorial planning and public policy, balancing conservation and economic activities.

Benefits for Local Communities: Indigenous and Afro-Colombian communities directly depend on ecosystem services from the reserve. The study will contribute to sustainable land use and strengthen resilience to climate change.



 
 
Top