Deforestation is a global issue that affects forests worldwide, as they play a crucial role in mitigating climate change, conserving water resources, and generating rainfall. In Ecuador, extensive deforestation has been observed in various locations, such as Palmira in the province of Chimborazo, where constant afforestation and deforestation occur due to activities carried out by both public and private entities. Additionally, the area also exhibits desert areas due to erosion over the years.

This research focuses on the forest dynamics of four specific sites in Palmira: Jatun Loma, Galte Laime, Galte Cuatro Esquinas, and Palmira Dávalos. By utilizing the Google Earth Engine (GEE) platform and temporal trend analysis algorithms like LandTrendr and Continuous Change Detection and Classification (CCDC), satellite images were collected from 2000 to 2020. These images were processed to obtain time series based on the Normalized Difference Vegetation Index (NDVI).

The obtained results show trends that align with existing documentation regarding the constant afforestation and deforestation in the study area. Disturbance, recovery, and stability processes have been identified over the years. The research demonstrates the utility of LandTrendr and CCDC algorithms in analyzing forest dynamics and their relationship with human activities in Palmira.

In terms of results, an increase in forest area was observed in Galte Laime until approximately 2006, followed by significant deforestation. On the other hand, Palmira Dávalos, known as the Palmira Desert, exhibited a consistent lack of vegetation due to centuries of erosion. Galte Cuatro Esquinas showed a stable downward trend, followed by a regrowth starting in 2009. In Jatun Loma, stability was initially observed, followed by gradual deforestation and subsequent reforestation.

In conclusion, this research has provided a detailed description of the forest dynamics in the Palmira area using temporal trend analysis algorithms and satellite-based time series. The obtained results align with existing documentation on the constant afforestation and deforestation in the area. The importance of utilizing remote sensing tools and algorithms like LandTrendr to monitor and understand forest changes and their relationship with human activities is highlighted. These findings can contribute to decision-making in forest management and the conservation of natural resources in the study area.