Current estimates of CO₂ emissions from forest degradation are generally based on insufficient information and are characterized by high uncertainty, while a global definition of ‘forest degradation’ is currently being discussed in the scientific arena. This study proposes an automated approach to monitor degradation using a Landsat time series. The methodology was developed using the Google Earth Engine (GEE) and applied in a pine forest area of the Dominican Republic. Land cover change mapping was conducted using the random forest (RF) algorithm and resulted in a cumulative overall accuracy of 92.8%. Forest degradation was mapped with a 70.7% user accuracy and a 91.3% producer accuracy. Estimates of the degraded area had a margin of error of 10.8%. A number of 344 Landsat collections, corresponding to the period from 1990 to 2018, were used in the analysis. Additionally, 51 sample plots from a forest inventory were used. The carbon stocks and emissions from forest degradation were estimated using the RF algorithm with an R² of 0.78. GEE proved to be an appropriate tool to monitor the degradation of tropical forests, and the methodology developed herein is a robust, reliable, and replicable tool that could be used to estimate forest degradation and improve monitoring, reporting, and verification (MRV) systems under the reducing emissions from deforestation and forest degradation (REDD+) mechanism.

In Chile, 49.1% of the national territory is affected by soil degradation (including erosion and loss of soil organic matter), whereby of the 51.7 Mha that have been historically associated with agricultural-livestock and forestry activities, only 35.5 Mha are being used at the present. Consequently, soil degradation has resulted in the release of about 11.8 Gg yr⁻¹ of carbon (C) equivalent (CO_2eq) to the atmosphere. Silvopastoral systems (SPS), however, can increase soil organic C (SOC) through sequestration (C→SOC), improve ecosystem services, and have been internationally recommended for sustainable land use. Therefore, it was proposed to determine the effects of SPS on soils, over five years, in degraded sites that were located in the Ranchillo Alto (SPS-RA) (37°04′52″ S, 71°39′14″ W), Ñuble region. The sites were rated according to previous canopy disturbance levels (+) as follows: open (O_p)+++, semi open (SO_p)++, and semi closed (SC)+. The analysis was performed on different physical and chemical soil properties (0–5 and 5–20 cm depths), that were expressed as soil indicators (S_IND) for chemical and physical properties, which were used to calculate a soil quality (SQ) index (SQI). The results indicated overall SQI values of 37.6 (SC) > 29.8 (O_p) > 28.8 (SO_p), but there were no significant variations (p < 0.05) in physical SQ, whereas chemical SQ varied in all conditions, mostly at 0–5 cm in O_p and SO_p. Increases of SOC were also observed (2015–2018 period) of 22.5, 14.5, and 4.8 Mg ha⁻¹ for SO_p, O_p, and SC, respectively, showing that SPS promote the reclamation of Ranchillo Alto soils.