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Found 16 dataset(s) matching "Pohnpei".
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U.S. Geological Survey (USGS) scientists conducted field work efforts during February 15-23, 2017 and April 10-25, 2019 in the mangrove forests of Pohnpei, Federated States of Micronesia (FSM)...
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U.S. Geological Survey (USGS) scientists conducted field work efforts during February 15-23, 2017 and April 10-25, 2019 in the mangrove forests of Pohnpei, Federated States of Micronesia (FSM)...
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Landslide hazards pose a significant threat to communities and infrastructure across the Federated States of Micronesia (FSM). To support hazard assessment and mitigation efforts, the USGS...
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Surface elevation of the mangrove forest is important for understanding current and future vulnerability to sea-level rise. Due to the lack of LiDAR data and insufficient accuracy of space-borne...
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Model projections of mangrove soil elevation under a range of sea-level rise scenarios (37, 52, 67, and 117 cm by 2100). Soil elevation changed in response to mineral and organic matter inputs and...
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Water level was monitored at two mangrove forest sites across Pohnpei, Federated States of Microneisa. Water levels were recorded with pressure-transducing dataloggers (Solinst) for eight months...
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Soil cores were collected in mangrove forests across Pohnpei, Federated States of Micronesia to understand spatial variation in accretion rates. Cores were dated using lead-210 and processed for...
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Landslides hazards pose a serious threat to people and infrastructure in the Federated States of Micronesia (FSM). To develop a comprehensive understanding of the landslides hazards in FSM, the...
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Mangrove species dominance on Pohnpei island, Federated States of Micronesia was modeled with two geospatial model types: k-nearest neighbor (KNN) and random forest (RF) and a common set of...
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Mangrove species dominance on Pohnpei island, Federated States of Micronesia was modeled with two geospatial model types: k-nearest neighbor (KNN) and random forest (RF) and a common set of...
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Future sea-level rise poses a risk to mangrove forests. To better understand potential vulnerability, we developed a new numerical model of soil elevation for mangrove forests. We used the model...
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Future sea-level rise poses a risk to mangrove forests. To better understand potential vulnerability, we developed a new numerical model of soil elevation for mangrove forests. We used the model...
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CBRegion1@acf.hhs.gov - please use for grantee plan submissionsAmy LockhartAmy.Lockhart@acf.hhs.govJFK Federal Building, Rm. 200015 Sudbury StreetBoston, MA 02203(617) 565-1135States: ...
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This dataset contains physical and meteorological data collected from non-Federal stations throughout the United States Pacific Islands. The data is predominantly long time series at fixed...
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The foundation of this ongoing collection are high-resolution directional wave spectra and parameters measured by Datawell Waverider buoys deployed across US waters. Supplementing the spectral...
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Benthic, fish, and macroinvertebrate census data are collected from sites around Micronesia as part of the ongoing Micronesia Challenge. Information on the program can be found at...
