In 2010, the U.S. Geological Survey in Woods Hole, MA and St. Petersburg, FL, in partnership with the U.S. Army Corps of Engineers, Mobile District conducted geologic mapping to characterize the seafloor and shallow subsurface stratigraphy offshore of the Gulf Islands of Mississippi. The mapping was carried out during two cruises in March, 2010 on the R/V Tommy Munro of Biloxi, MS. Data were acquired with the following equipment: an SEA Ltd SwathPlus interferometric sonar (both 234 kHz and 468 kHz systems), a Klein 3000 and a Klein 3900 dual frequency sidescan-sonar, and an Edgetech 512i chirp subbottom profiling system. The long-term goal of this mapping effort is to produce high-quality, high-resolution geologic maps and geophysical interpretations that can be utilized to identify sand resources within the region and better understand the Holocene evolution and anticipate future changes in this coastal system. More information on the field work can be accessed from the Woods Hole Coastal and Marine Science Center Field Activity webpage https://cmgds.marine.usgs.gov/fan_info.php?fan=2010-012-FA or the St. Petersburg Coastal and Marine Geology InfoBank https://walrus.wr.usgs.gov/infobank/m/m210gm/html/m-2-10-gm.meta.html.

Real-time data- and location-sharing using mesh networking radios paired with smartphones may improve situational awareness and safety in remote environments lacking communications infrastructure. Despite being increasingly used for wildland fire and public safety applications, there has been little formal evaluation of the network connectivity of these devices. The objectives of this study were to 1) characterize the connectivity of mesh networks in variable forest and topographic conditions; 2) evaluate the abilities of lidar and satellite remote sensing data to predict connectivity; and 3) assess the relative importance of the predictive metrics. A large field experiment was conducted to test the connectivity of a network of one mobile and five stationary goTenna Pro mesh radios on 24 Public Land Survey System sections approximately 260 ha in area in northern Idaho. Dirichlet regression was used to predict connectivity using 1) both lidar- and satellite-derived metrics (LIDSAT); 2) lidar-derived metrics only (LID); and 3) satellite-derived metrics only (SAT). On average the full network was connected only 32.6% of the time (range: 0% to 90.5%) and the mobile goTenna was disconnected from all other devices 18.2% of the time (range: 0% to 44.5%). RMSE for the six connectivity levels ranged from 0.101 to 0.314 for the LIDSAT model, from 0.103 to 0.310 for the LID model, and from 0.121 to 0.313 for the SAT model. Vegetation-related metrics affected connectivity more than topography. Developed models may be used to predict the connectivity of real-time mesh networks over large spatial extents using remote sensing data in order to forecast how well similar networks are expected to perform for wildland firefighting, forestry, and public safety applications. However, safety professionals should be aware of the impacts of vegetation on connectivity. The datasets are described in the associated manuscript submitted to PLOS ONE. The LIDSAT, LID, and SAT files are structured the same way, with each row representing a Public Land Survey System (PLSS) section and each column representing a response variable or remote sensing predictor. The first column ( section_id ) indicates the PLSS section ID. The next six columns ( received_6 to received_1 ) represent the number of transmitted signals received by 5, 4, 3, 2, 1, and 0 stationary goTennas, respectively, and the tot_trans column represents the total number of signals transmitted by the mobile goTenna in the section. The next six columns ( Con_6_obs to Con_1_obs ) represent the proportion of transmitted signals received by 5, 4, 3, 2, 1, and 0 stationary goTennas (i.e., the six connectivity levels). These were calculated by dividing the respective received columns by the tot_trans column (e.g., Con_6_obs = received_6/tot_trans, etc.). Because Dirichlet regression cannot handle zero values, zeroes were imputed as described in the manuscript in order to derive the next six columns ( Con_6 to Con_1 ). These columns correspond to the compositional response variables used to develop the Dirichlet regression models and represent the proportion of time 5, 4, 3, 2, 1, and 0 stationary goTennas were connected to the mobile goTenna, respectively. All remaining columns after Con_1 correspond to either a lidar- or satellite-derived metric calculated for each section, according to the descriptions and variable keys located in the manuscript. The LIDSAT, LID, and SAT datasets have identical response variables and the only difference between them is the inclusion of different remote sensing predictors. The LIDSAT dataset contains all of the lidar- and satellite-derived predictors, the LID dataset only contains the lidar-derived predictors, and the SAT dataset only contains the satellite-derived predictors. The ATAK_Full_RS_Metrics_MaxMinValues dataset contains the maximum and minimum values for each remote sensing predictor variable which were used to normalize the variables as described in the manuscript. The first column contains the remote sensing predictor variable name and matches the remote sensing variable names in the LIDSAT, LID, and SAT datasets. The next two columns list the minimum and maximum values of the corresponding predictor. File Directory: LIDSAT.csv: LID.csv: SAT.csv: ATAK_Full_RS_Metrics_MaxMinValues.csv: Contains the maximum and minimum values for each remote sensing predictor variable which were used to normalize the variables as described in the manuscript. Header Key: [Column 1]: Contains the remote sensing predictor variable name and matches the remote sensing variable names in the LIDSAT, LID, and SAT datasets. min: Minimum values of the corresponding predictor. Max: Maximum values of the corresponding predictor. readme.txt

In 2010, the U.S. Geological Survey in Woods Hole, MA and St. Petersburg, FL, in partnership with the U.S. Army Corps of Engineers, Mobile District conducted geologic mapping to characterize the seafloor and shallow subsurface stratigraphy offshore of the Gulf Islands of Mississippi. The mapping was carried out during two cruises in March, 2010 on the R/V Tommy Munro of Biloxi, MS. Data were acquired with the following equipment: an SEA Ltd SwathPlus interferometric sonar (both 234 kHz and 468 kHz systems), a Klein 3000 and a Klein 3900 dual frequency sidescan-sonar, and an Edgetech 512i chirp subbottom profiling system. The long-term goal of this mapping effort is to produce high-quality, high-resolution geologic maps and geophysical interpretations that can be utilized to identify sand resources within the region and better understand the Holocene evolution and anticipate future changes in this coastal system. More information on the field work can be accessed from the Woods Hole Coastal and Marine Science Center Field Activity webpage https://cmgds.marine.usgs.gov/fan_info.php?fan=2010-012-FA or the St. Petersburg Coastal and Marine Geology InfoBank https://walrus.wr.usgs.gov/infobank/m/m210gm/html/m-2-10-gm.meta.html.

In 2010, the U.S. Geological Survey in Woods Hole, MA and St. Petersburg, FL, in partnership with the U.S. Army Corps of Engineers, Mobile District conducted geologic mapping to characterize the seafloor and shallow subsurface stratigraphy offshore of the Gulf Islands of Mississippi. The mapping was carried out during two cruises in March, 2010 on the R/V Tommy Munro of Biloxi, MS. Data were acquired with the following equipment: an SEA Ltd SwathPlus interferometric sonar (both 234 kHz and 468 kHz systems), a Klein 3000 and a Klein 3900 dual frequency sidescan-sonar, and an Edgetech 512i chirp subbottom profiling system. The long-term goal of this mapping effort is to produce high-quality, high-resolution geologic maps and geophysical interpretations that can be utilized to identify sand resources within the region and better understand the Holocene evolution and anticipate future changes in this coastal system. More information on the field work can be accessed from the Woods Hole Coastal and Marine Science Center Field Activity webpage https://cmgds.marine.usgs.gov/fan_info.php?fan=2010-012-FA or the St. Petersburg Coastal and Marine Geology InfoBank https://walrus.wr.usgs.gov/infobank/m/m210gm/html/m-2-10-gm.meta.html.

In 2010, the U.S. Geological Survey in Woods Hole, MA and St. Petersburg, FL, in partnership with the U.S. Army Corps of Engineers, Mobile District conducted geologic mapping to characterize the seafloor and shallow subsurface stratigraphy offshore of the Gulf Islands of Mississippi. The mapping was carried out during two cruises in March, 2010 on the R/V Tommy Munro of Biloxi, MS. Data were acquired with the following equipment: an SEA Ltd SwathPlus interferometric sonar (both 234 kHz and 468 kHz systems), a Klein 3000 and a Klein 3900 dual frequency sidescan-sonar, and an Edgetech 512i chirp subbottom profiling system. The long-term goal of this mapping effort is to produce high-quality, high-resolution geologic maps and geophysical interpretations that can be utilized to identify sand resources within the region and better understand the Holocene evolution and anticipate future changes in this coastal system. More information on the field work can be accessed from the Woods Hole Coastal and Marine Science Center Field Activity webpage https://cmgds.marine.usgs.gov/fan_info.php?fan=2010-012-FA or the St. Petersburg Coastal and Marine Geology InfoBank https://walrus.wr.usgs.gov/infobank/m/m210gm/html/m-2-10-gm.meta.html.

In 2010, the U.S. Geological Survey in Woods Hole, MA and St. Petersburg, FL, in partnership with the U.S. Army Corps of Engineers, Mobile District conducted geologic mapping to characterize the seafloor and shallow subsurface stratigraphy offshore of the Gulf Islands of Mississippi. The mapping was carried out during two cruises in March, 2010 on the R/V Tommy Munro of Biloxi, MS. Data were acquired with the following equipment: an SEA Ltd SwathPlus interferometric sonar (both 234 kHz and 468 kHz systems), a Klein 3000 and a Klein 3900 dual frequency sidescan-sonar, and an Edgetech 512i chirp subbottom profiling system. The long-term goal of this mapping effort is to produce high-quality, high-resolution geologic maps and geophysical interpretations that can be utilized to identify sand resources within the region and better understand the Holocene evolution and anticipate future changes in this coastal system. More information on the field work can be accessed from the Woods Hole Coastal and Marine Science Center Field Activity webpage https://cmgds.marine.usgs.gov/fan_info.php?fan=2010-012-FA or the St. Petersburg Coastal and Marine Geology InfoBank https://walrus.wr.usgs.gov/infobank/m/m210gm/html/m-2-10-gm.meta.html.