At present, most governments, particularly in low and middle-income countries, are not effectively using ecosystem services (ES) indicators for conservation monitoring, which is in part due to the complexity of current indicators. This study seeks to contribute to this implementation gap by illustrating the performance of a remote sensing based indicator, the Ecosystem Services Provision Index (ESPI) (based on the Normalized Difference Vegetation Index), as a feasible indicator for monitoring ES supply. We examined ESPI's performance by analyzing its spatial congruence (regression and cluster analysis) with four type-specific ES indicators, namely timber provision, forage provision, opportunities for recreation and water regulation, for different types of temperate native forests, non-native tree plantations, shrublands and grasslands, within a southern district in Chile. We additionally compared values of ESPI and ES indicators across land uses and covers by means of ANOVA and Tuckey test (post-hoc). The regression analysis showed medium to low fitting of ES indicators to linear and non-linear variations of ESPI. Unexplained variation can arise from different dispersion sources: a) uncaptured variation in specific ES flow by variation in their corresponding indicators (specific ES indicators and ESPI), b) distances between parametric values of different ES indicators and ESPI, and c) mismatches between ESPI and ES indicator scales and resolutions. Cluster analysis showed ESPI-ES hotspot congruence of 62% for water regulation, followed by the ES bundle (56%), recreation opportunities (38%), timber supply (36%) and forage provision (32%). The values of ESPI, water regulation and recreation opportunities were significantly higher on old growth forests. Our study contributes to establish to what extent remote sensing indicators can be used as a proxy of ES supply, which is relevant for the adoption of these indicators in monitoring conservation outcomes when specific ES indicators are not available or they lack the necessary spatial and temporal coverage.