AUTHOR=Sollier Valentine , Frappart Frédéric , Bourrel Luc , Couvreur Thomas L. P. , Peaucelle Marc , Renaudineau Solène , Huaraca Luis , Wigneron Jean-Pierre 

TITLE=Long-term evolution of forest cover in the Pacific coast of Ecuador (1960–2019): a comparison of Land Use/Land Cover (LULC) remote sensing products

JOURNAL=Frontiers in Remote Sensing

VOLUME=Volume 6 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2025.1536105

DOI=10.3389/frsen.2025.1536105

ISSN=2673-6187

ABSTRACT=Ecosystem services provided by forests are increasingly threatened by anthropogenic and climatic disturbances. International initiatives to reduce greenhouse gas emissions from forest disturbances, such as Reducing Emissions from Deforestation and Degradation+ (REDD+), require robust quantifications of the dynamics and extent of Land Use/Land Cover (LULC). However, no study present yet a comparative synthesis of existing LULC products and long-term landscape evolution on the Pacific Slope and Coast of Ecuador (EPSC). In addition, previous studies on the evolution of the forest cover in the EPSC were achieved on small regions and short time-scales, never analysing before the 1990s. In this context, we conducted a long-term study of landscape dynamics at the scale of the EPSC on the last 6 decades (1960-2019). In addition, we propose a comparative synthesis of the main land use databases from remote sensing. To do this, we compared six LULC databases (HILDA+, ESA-CCI, MODIS, GLCLUC, TMF, GFC) derived from remote sensing using the Ecuadorian Ministry of Environment and Water (MAATE) LULC dataset as a reference. This comparison was performed with confusion matrices. Three metrics are calculated from the confusion matrices: Accuracy, F1-score and MCC. HILDA+ and TMF products showed the best agreement with the MAATE map (F1-score of 0.63 and 0.65, respectively). HILDA + captured net forest cover losses better than TMF (65% vs 27% of the net losses recorded by MAATE). Of the six databases analysed, HILDA+ was identified as the product with the best correlation with the Ministry’s LULC maps. Therefore, HILDA+ was chosen to analyse deforestation since 1960 in the EPSC. The major limitation encountered using HILDA+ is the coarse spatial resolution of 1 km. Yet, four deforestation phases were identified in the EPSC over 1960–2019. They reflect the historical, social, political, and climatical context of each ecosystem. Over the entire period (1960-2019), forest cover decreased by 43.9%. Since the 1960s, tropical rainforest areas declined by a third. Dry and transitional tropical forests lost more than half their area.