Multi-seasonal land cover changes of South Peruvian Highland Andean ecosystems

The highland ecosystems in the southern Peruvian Andes represent an important resource for people who depend on them for water regulation, agriculture, and energy generation. These ecosystems change over time due to natural causes, climate variations, or anthropic intervention. Remote sensing studies have quantified land cover changes in this domain annually, but have neglected the seasonal ecosystem variations, which are conditioned by seasonal weather patterns, species phenology, or applied management. One high-elevation headwater in this region, the Vilcanota-Urubamba Basin (VUB) in Cusco-Peru is characterized by glaciers surrounded by barren areas, flooded areas such as lakes and wetlands, and vegetation ranging from sparse grasslands to forests in the northwest of the catchment.

In this study, we used a land cover classification model at a multi-seasonal scale over 10 years to observe the seasonal dynamics and links between the land cover classes in VUB. We applied the Random Forest classification model on Landsat 7 and 8 imagery (30 m/pixel), trained with selecting 10 points for seven land cover classes, to discriminate land cover every 3 months from 2013 to 2022 over an extended area of the VUB system. We ran the model in the Google Earth Engine platform, using as inputs six spectral indices and three topographic indices obtained from an SRTM DEM.

Our overall results indicate that the VUB area (11,047 km²) is mainly occupied by Agriculture and Pasture (~52.5%) distributed in the upper-middle areas above 3000 masl, followed by Barren (~18.9%). Shrub (~8.4%) and Forest (~8.25%) areas which are more concentrated in the northwest region, and Wetland (~3.94%), Water (~2%), and Snow and Ice (~1.88%) areas, which are mostly located in the Southeast region. We apply two general accuracy assessments based on a set of collected validation points (0.74) and random points (0.72). The results show limited availability of high-quality images during January to March of almost every year, related to the high cloudiness, but much better image availability in the other months.

We find strong seasonal variations in the Snow/Ice, Water, and Wetland classes related to the precipitation regime of the region; but Barren, Shrub, and Forest areas do not vary much seasonally. We determined the correlation between land cover classes for each season and considering all seasons together to identify relevant interrelationships between classes. We find that Snow/Ice changes are correlated (p<0.05) to the Wetland areas (r=0.35) and Water bodies (r=0.71) which are also related to each other (r=0.49). The Agriculture and Pasture areas change with Barren areas (r=-0.65) but have a slight inverse correlation to Wetlands (r=-0.27) highlighting the importance of the seasonal climate. We can interpret these results to infer the dependence between highland vegetated ecosystems and the seasonal hydrological response to glaciers and weather patterns. Overall this work provides important insights into the seasonal landcover change dynamics in this region and the important interrelationships between components of Peruvian highland ecosystems.