摘要：Decision makers and stakeholders need high-quality data to manage ecosystem services (ES)efficiently. Landscape-level data on ES that are of sufficient quality to identify spatial tradeoffs, co-occurrence and hotspots of ES are costly to collect, and it is therefore important toincrease the efficiency of sampling of primary data. We demonstrate how ES could beassessed more efficiently through image-based point intercept method and determine thetradeoff between the number of sample points (pins) used per image and the robustness ofthe measurements. We performed a permutation study to assess the reliability implications ofreducing the number of pins per image. We present a flexible approach to optimize landscape-level assessments of ES that maximizes the information obtained from 1 m2 digitalimages. Our results show that 30 pins are sufficient to measure ecosystem service indicatorswith a crown cover higher than 5% for landscape scale assessments. Reducing the number ofpins from 100 to 30 reduces the processing time up to a 50% allowing to increase thenumber of sampled plots, resulting in more management-relevant ecosystem service maps.The three criteria presented here provide a flexible approach for optimal design of landscapelevel assessments of ES.
关键词：Image based point intercept;ecosystem service indicators;vegetation;ground truth;monitoring;permutation;pins
