Remote sensing razor clam abundance data from western Cook Inlet, Alaska, June 22 to June 27, 2017

These datasets are part of the development of remote sensing methods for estimating razor clam abundance in western Cook Inlet. The data are broken down into three objectives. Objective 1: Hydraulic sampling. We sampled with hydraulic pumps at 9 sites on the south side of the Crescent river bar during minus-tide series June 22-27, 2017. At each site, a hydraulic pump was used to extract razor calms from the substrate at 25-136 quadrats (0.5m-square) spaced 1-2 m apart. These data are in two space delimited files. Lengths.prn has date (mdd), time (am or pm) loct (location) FSLM (razor calm length in mm) and age. Counts.prn has date (mdd), Time (am, pm), Tide (in feet) LOCT (location and quadrant), LTDG (latitude degrees), LTMN (latitude minutes and seconds), LGDG (longitude degrees), LGMN (longitude minutes and seconds), RCNT (razor clam count), BCNT (butter clam count), LCNT (littleneck clam count) and NCNT (neptunia clam count). Objective 2: Multi-beam sonar data was collected along equidistant parallel transects in tow survey area on the Crescent river bar on June 24 (1620-1730 hours), June 26 (1930-2100 hours) and June 27 (0540-0710). Transducers for both systems were pole mounted on an 10-m aluminum vessel and transcets surveyed at 2 m/sec. The MBES was mounted on the port side and the SBES was mounted on the starboard. The two systems were not operated at the same time due to "cross talk" between them. The MBES system consisted of a Kongsberg GeoSwath Plus Compact Shallow Water Multi-beam sonar (250 kHz) which collected sediment data over a 20-m swathe of seafloor on each side of vessel. The MBES was equipped with a sound velocity sensor (mini-SVS) and a Kongsberg MRU-H motion reference unit for system calibration. A patch test was conducted approximately 2 km southwest of the survey area that provided distinct bathymetric features for calibration of any navigation latency and angular offsets. To provide for accurate estimation of bathymetry, local water level changes were mesausred using a HOBO (Model U20) pressure sensor (accuracy +- 1.5 cm). Post-processing of MBES was conducted using Kongsberg GeoAcoustics GS4 software. Objective 3: Sub-bottom profiling sonar. SBES acoustic date were also collected along equidistant (40-50m) parallel transectsin two survey areas on the south side of the Crescent River Bar on June 24 (1620-1730 hrs), June 26 (1930-2100 hrs) and June 27 (0540-0710 hrs). The SBES system consisted of an Innomar SES-2000 Compact Sub-bottom Profiler with a low frequency echosounder (15kHz) to collect acoustic data below the seafloor and a high frequency echosounder (100kHz) to measure depth of seafloor. The system had no side lobes on acoustic beam reducing spurious signals. It provided high spacial resolution (1-5 cm) for detection of small objects buried in the sediments due to narrow (4 degree) acoustic beam, short pulse width (0.07-1 ms), high ping rate (up to 40/sec) and high bandwidth (2-22 kHz). The SBES was also equipped with a sound velocity sensor and heading pitch and roll sensors. Both acoustic systems received precision position data from Hemishpere Vecto VS330 GNSS Compass differential global positioning system.

本数据集系列为开发用于估算库克湾西部竹蛏（razor clam）丰度的遥感方法而构建，数据围绕三大目标展开。
目标1：水力采样。2017年6月22日至27日的低潮时段，我们在新月河沙洲南侧的9个采样点使用水力泵开展采样。每个采样点处，以1~2米的间距布设25~136个0.5平方米的样方，利用水力泵从底质中采集竹蛏样本。该部分数据包含两个空格分隔文件："Lengths.prn"包含日期（格式为mdd）、时间（上午/下午）、LOCT（采样位置）、FSLM（竹蛏体长，单位：毫米）及年龄信息；"Counts.prn"包含日期（格式为mdd）、时间（上午/下午）、潮位（单位：英尺）、LOCT（采样位置及象限）、LTDG（纬度度数）、LTMN（纬度分秒）、LGDG（经度度数）、LGMN（经度分秒）、RCNT（竹蛏计数）、BCNT（黄油蛤计数）、LCNT（鸟蛤计数）及NCNT（海蜷属蛤类计数）。
目标2：多波束声呐系统（Multi-beam Echo Sounder, MBES）数据。2017年6月24日（16:20~17:30）、6月26日（19:30~21:00）及6月27日（05:40~07:10），在新月河沙洲的拖曳测量区域内，沿等距平行测线采集多波束声呐数据。两套传感器均安装于10米铝制船体的杆架上，测线航行速度为2米/秒。多波束声呐系统安装于左舷，单波束声呐系统（Single-beam Echo Sounder, SBES）安装于右舷，由于两套系统间存在串扰，无法同时运行。MBES系统采用康斯伯格（Kongsberg）GeoSwath Plus紧凑型浅水区多波束声呐（250 kHz），可在船体两侧各20米宽的海底覆盖范围内采集沉积物数据。该系统配备声速传感器（mini-SVS）及康斯伯格MRU-H运动参考单元，用于系统校准。在测量区域西南约2公里处开展了斑块测试，该区域拥有清晰的水深地形特征，可用于校准导航延迟与角度偏移量。为实现精准的水深地形估算，采用HOBO U20型号压力传感器（精度±1.5厘米）监测当地水位变化。多波束声呐数据的后处理工作通过康斯伯格GeoAcoustics GS4软件完成。
目标3：浅地层剖面声呐。2017年6月24日（16:20~17:30）、6月26日（19:30~21:00）及6月27日（05:40~07:10），在新月河沙洲南侧的两个测量区域内，沿间距40~50米的平行测线采集单波束声呐声学数据。SBES系统采用因诺玛（Innomar）SES-2000紧凑型浅地层剖面仪，配备低频回声测深仪（15 kHz）以采集海底下方的声学数据，及高频回声测深仪（100 kHz）以测量海底深度。该系统的声束无旁瓣，可有效减少杂散信号。得益于4°的窄声束、0.07~1毫秒的短脉冲宽度、最高40次/秒的高ping率及2~22 kHz的宽带宽，该系统可实现1~5厘米的高空间分辨率，精准探测埋藏于沉积物中的小型目标物。SBES系统还配备了声速传感器及航向、俯仰与横滚传感器。两套声学系统均通过半球（Hemishpere）Vecto VS330 GNSS罗盘差分全球定位系统获取高精度位置数据。