Abstract
This study demonstrates the usefulness of an approach based on the Online Positioning User Service (OPUS) provided by the National Geodetic Survey (NGS) of the National Oceanic and Atmospheric Administration (NOAA) to process Global Positioning System (GPS) data and conduct long-term landslide monitoring in the Puerto Rico and Virgin Islands region. Continuous GPS data collected at a creeping landslide site during 2 years were used to evaluate different scenarios for landslide surveying: continuous or campaign, long duration or short duration, morning or afternoon (during different weather conditions). OPUS uses the Continuously Operating Reference Station (CORS) network managed by the NGS as control points and user-collected data to solve for the position of the occupied station (rover). In July 2011, there were 19 NGS CORS sites in the Puerto Rico and Virgin Islands region. This dense GPS network provided a precise and reliable reference frame for subcentimeter-accuracy landslide monitoring in this region. OPUS static solutions (OPUS-S) for sessions as short as 4 h, and OPUS rapid static solutions (OPUS-RS) for sessions as short as 15 min, can achieve subcentimeter horizontal accuracy if the collection of data during extreme weather conditions is avoided. The uncertainty (peak-to-peak error) reported by a single OPUS-S solution differs from the “true” accuracy by a factor of 1.7 for the horizontal components and 1.3 for the vertical component. The uncertainty reported by a single OPUS-RS solution differs from the accuracy by a factor of 1.4 for horizontal components, while the uncertainty of vertical component statistically agrees with the vertical accuracy. This study also indicates that rainfall events can seriously degrade the performance of high-accuracy GPS. Field GPS landslide surveying should avoid rainfall episodes when accompanied by thunderstorms and the passage of detrimental weather fronts. Once appropriate precautions are taken, the results of this investigation show that OPUS-S and OPUS-RS are ideal alternative tools for subcentimeter-accuracy landslide monitoring.

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