Description: In 2019, NOAA launched the Pacific Mapping Cooperative: RICHARD (Rainier Integrates Charting Hydrography and Reef Demographics) Marianas Campaign to develop a plan to conduct much-needed mapping in the Marianas Archipelago. NCCOS was requested to generate contemporary, high-resolution shallow water benthic habitat maps for select areas off Saipan, which is the largest territory in the Commonwealth of the Northern Mariana Islands (CNMI). This effort will support coastal management, disaster response, navigation improvements, and national security interests in CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: In 2019, NOAA launched the Pacific Mapping Cooperative: RICHARD (Rainier Integrates Charting Hydrography and Reef Demographics) Marianas Campaign to develop a plan to conduct much-needed mapping in the Marianas Archipelago. NCCOS was requested to generate contemporary, high-resolution shallow water benthic habitat maps for select areas off Saipan, which is the largest territory in the Commonwealth of the Northern Mariana Islands (CNMI). This effort will support coastal management, disaster response, navigation improvements, and national security interests in CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: In 2019, NOAA launched the Pacific Mapping Cooperative: RICHARD (Rainier Integrates Charting Hydrography and Reef Demographics) Marianas Campaign to develop a plan to conduct much-needed mapping in the Marianas Archipelago. NCCOS was requested to generate contemporary, high-resolution shallow water benthic habitat maps for select areas off Saipan, which is the largest territory in the Commonwealth of the Northern Mariana Islands (CNMI). This effort will support coastal management, disaster response, navigation improvements, and national security interests in CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: In 2019, NOAA launched the Pacific Mapping Cooperative: RICHARD (Rainier Integrates Charting Hydrography and Reef Demographics) Marianas Campaign to develop a plan to conduct much-needed mapping in the Marianas Archipelago. NCCOS was requested to generate contemporary, high-resolution shallow water benthic habitat maps for select areas off Saipan, which is the largest territory in the Commonwealth of the Northern Mariana Islands (CNMI). This effort will support coastal management, disaster response, navigation improvements, and national security interests in CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show the sites where benthic photographs were acquired and annotated visually to the nearest 1% for key substrate and biological cover taxonoimc groups. These sites were converted to presences (1) and absences (0) and used to train and validate benthic habitat predictions and a habitat map for select areas offshore of Saipan, CNMI.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic and governmental organizations.
Description: These datasets show predicted benthic substrate and biological cover types for select areas offshore of Saipan, CNMI.The mean probability of occurrence layers denote the average probability (ranging from 0 to 100%) that a substrate or biological cover type is present in a raster cell. Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present. The coefficient of variation (CoV) layers denotes the variation in the predicted probability of occurrence for each substrate type. CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models. For example, if in a pixel, the mean probability is 0.5 and the CoV is 0.1, then 0.5 × 0.1 = ±0.05 or ± one SD). Assuming normally distributed errors, 68.3% of the data will fall between ±0.05 (or 1 SD), 95.5% of the data will fall between ±0.1 (or 2 SD), and 99.7% of the data will fall between ±0.15 (or 3 SD).
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: These datasets show predicted benthic substrate types for select areas offshore of Saipan, CNMI.The mean probability of occurrence layers denote the average probability (ranging from 0 to 100%) that a substrate type is present in a raster cell. Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a substrate type is less likely to be present. Higher probabilities (closer to 100%) indicate a substrate type is more likely to be present. The coefficient of variation (CoV) layers denotes the variation in the predicted probability of occurrence for each substrate type. CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models. For example, if in a pixel, the mean probability is 0.5 and the CoV is 0.1, then 0.5 × 0.1 = ±0.05 or ± one SD). Assuming normally distributed errors, 68.3% of the data will fall between ±0.05 (or 1 SD), 95.5% of the data will fall between ±0.1 (or 2 SD), and 99.7% of the data will fall between ±0.15 (or 3 SD).
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Live Coral Reef (All Species) - Mean Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the average predicted probability of occurrence (%) for live coral reef (all species) around Navy Base Guam. Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Live Coral Reef (All Species) - Coefficient of Variation
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the variation in the predicted probability of occurrence for live coral reef (all species) for select areas offshore of Saipan, CNMI. Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the average predicted probability of occurrence (%) for dead reef (all species) for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the variation in the predicted probability of occurrence for dead reef for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the average predicted probability of occurrence (%) for pavement for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the variation in the predicted probability of occurrence for pavement for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the average predicted probability of occurrence (%) for rubble for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the variation in the predicted probability of occurrence for rubble for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the average predicted probability of occurrence (%) for sand for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the variation in the predicted probability of occurrence for sand for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: These datasets show predicted benthic biological cover types for select areas offshore of Saipan, CNMI.The mean probability of occurrence layers denote the average probability (ranging from 0 to 100%) that a biological cover type is present in a raster cell. Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present. The coefficient of variation (CoV) layers denotes the variation in the predicted probability of occurrence for each substrate type. CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models. For example, if in a pixel, the mean probability is 0.5 and the CoV is 0.1, then 0.5 × 0.1 = ±0.05 or ± one SD). Assuming normally distributed errors, 68.3% of the data will fall between ±0.05 (or 1 SD), 95.5% of the data will fall between ±0.1 (or 2 SD), and 99.7% of the data will fall between ±0.15 (or 3 SD).
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Live Coral (Branching and Columnar) - Mean Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the average predicted probability of occurrence (%) for Live Coral (Branching and Columnar) for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Live Coral (Branching and Columnar) - Coefficient of Variation
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the variation in the predicted probability of occurrence for Live Coral (Branching and Columnar) for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Live Coral (Branching) - Mean Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the average predicted probability of occurrence (%) for Live Coral (Branching) for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Live Coral (Branching) - Coefficient of Variation
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the variation in the predicted probability of occurrence for Live Coral (Branching) for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Live Coral (Encrusting) - Mean Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the average predicted probability of occurrence (%) for Live Coral (Encrusting) for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Live Coral (Encrusting) - Coefficient of Variation
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the variation in the predicted probability of occurrence for Live Coral (Encrusting) for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Live Coral (Porites Rus) - Mean Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the average predicted probability of occurrence (%) for Live Coral (Porites Rus) for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Live Coral (Porites Rus) - Coefficient of Variation
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the variation in the predicted probability of occurrence for Live Coral (Porites Rus) for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Live Coral (Isopora palifera) - Mean Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the average predicted probability of occurrence (%) for Live Coral (Porites Rus) for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Live Coral (Isopora palifera) - Coefficient of Variation
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the variation in the predicted probability of occurrence for Live Coral (Porites Rus) for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Seagrass (Halodule spp) - Mean Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the average predicted probability of occurrence (%) for Seagrass (Halodule spp.) for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Seagrass (Halodule spp) - Coefficient of Variation
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the variation in the predicted probability of occurrence for Seagrass (Halodule spp.) for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Seagrass (Enhaus spp) - Mean Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the average predicted probability of occurrence (%) for Seagrass (Halodule spp.) for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Seagrass (Enhalus spp) - Coefficient of Variation
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the variation in the predicted probability of occurrence for Seagrass (Halodule spp.) for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Cyanobacteria - Mean Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the average predicted probability of occurrence (%) for Cyanobacteria for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the variation in the predicted probability of occurrence for Cyanobacteria for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Algae (Turf) - Mean Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the average predicted probability of occurrence (%) for Algae (turf) for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the variation in the predicted probability of occurrence for Algae (turf) for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Algae (Halimeda) - Mean Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the average predicted probability of occurrence (%) for Algae (Halimeda spp) for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the variation in the predicted probability of occurrence for Algae (Halimeda spp) for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Algae (CCA) - Mean Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the average predicted probability of occurrence (%) for Algae (CCA) for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the variation in the predicted probability of occurrence for Algae (CCA) for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Name: Algae (Other) - Mean Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This dataset shows the average predicted probability of occurrence (%) for Algae (Other) for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the variation in the predicted probability of occurrence for Algae (Other) for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the average predicted probability of occurrence (%) for bare substrate (i.e., no biological cover) for select areas offshore of Saipan, CNMI.Average probabilities were calculated by creating 100 separate models, and then averaging the predicted probabilities in each pixel across the models. Lower probabilities (closer to 0%) indicate a habitat type is less likely to be present. Higher probabilities (closer to 100%) indicate a habitat type is more likely to be present.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: This dataset shows the variation in the predicted probability of occurrence for bare substrate (i.e., no biological cover) for select areas offshore of Saipan, CNMI.Variation is described as coefficient of variation (CoV). CoV is unitless and is the ratio of the standard deviation to the mean for each pixel. It was calculated by creating 100 separate models, and then calculating the mean and standard deviation of probability of occurrence in each pixel across the models.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.
Description: Boosted classification trees were used to develop this benthic habitat map depicting the distribution of the 7 habitats (plus artificial) identified by hierarchical cluster analysis. The probability of occurrence maps for individual substrate (n=5) and biological cover (n=14) types were used as predictors. The accuracy of this map was evaluated using an independent set of field data from 495 annotations at 341 validation sites. The overall accuracy is 91.5% and tau is 0.9 for this habitat map.
Copyright Text: This project was funded, designed and executed by the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) in consultation with local academic, industry and governmental organizations.