Submarine pipelines are important resource delivery devices between land and ocean. For safety reasons, pipelines are often embedded beneath the seabed at a certain depth, to reduce the risk of direct damage to the pipeline. In the past, various kinds of detection equipment have been used for pipeline inspection, to ensure the normal operation of pipelines in practical applications. Acoustic detection technology is the dominant method to monitor buried submarine pipelines. Extracting and integrating the information in acoustic images, such as the route and burial depth, can help to monitor the status of a pipeline. However, most of the existing methods are based on limited parameters, and they cannot be used to precisely detect and locate a submarine pipeline under complex conditions. In this study, a multi-sensor surveying system was used, which integrates a sub-bottom profiler (SBP) and the Shipborne Over-and Under-Water Integrated Mobile Mapping System (SiOUMMS) on the same ship. The data acquired in this system include acoustic profile images and the over-and under-water topography of the pipeline route area. We also designed a position deviation correction method to improve the accuracy of the pipeline detection positioning, i.e., pipeline positioning correction in the real-time kinematic (RTK) positioning data and pipeline horizontal route correction in the integrated data. Compared with the uncorrected pipeline detection positioning result, the reliability of the pipeline inspection result is greatly improved, and the effectiveness and merit of the proposed method are clearly demonstrated. Finally, we conducted a buried pipeline safety assessment for the installation of newly designed wharf piles at Mawan Port of Shenzhen, China, where the results showed that one of the first rows of wharf piles would collide with the sewage pipeline.

Evaluation of the spatial distribution of urban emergency shelters can effectively identify defects in the current distribution of urban emergency shelters and weaknesses in the overall evacuation service capacity of the city and provide reference for improving the level of urban emergency shelters and evacuation and disaster relief capacity. At present, evaluation of the spatial distribution of urban emergency shelters is mainly carried out on three aspects: effectiveness, accessibility, and safety. However, there are problems, such as individual evaluation scales and incomplete indicator systems, unreasonable allocation of indicator weights, and ignoring the influence of fuzzy incompatibility between different indicator attributes on the evaluation results. In this paper, we start from two scales, the individual emergency shelter and the regional groups of emergency shelters. Based on the five criteria of effectiveness, accessibility, safety, suitability, and fairness, the evaluation indicator system of the spatial distribution of urban emergency shelters was constructed. It was combined with AHP, CRITIC, the optimal weight coefficient solution method based on the maximum deviation sum of squares theory, and fuzzy optimization theory to construct a multi-indicator evaluation model. Further, the spatial distribution condition of the existing emergency shelter in Shanghai was evaluated. The results show that: among the existing ninety-one emergency shelters in Shanghai, there are nine places with unreasonable spatial distribution; nineteen places are comparatively unreasonable. From the scale of regional groups, there is one district (Pudong New District) with unreasonable spatial distribution: its relative superiority value is far lower than other districts, and there are three districts that are comparatively unreasonable. Further, the evaluation scores of the spatial distribution reasonableness of emergency shelters in each region of Shanghai show a high–low–middle distribution from the downtown area of Shanghai outward. The evaluation indicator system and evaluation method used in this paper can effectively reflect the deficiencies in the spatial distribution of urban emergency shelters, thus providing a reference for the relevant departments to improve and plan emergency shelters.

Water depth measurement requires the establishment of one or more tidal stations in the survey area for synchronous water level observation, and finally the water depth is estimated to the depth datum. The non-tidal observation measuring has high efficiency and avoids the water level correction error caused by tidal observation in traditional sounding. Therefore, non-tidal observation measuring has become an effective water depth measurement method in offshore and inland water. However, datum conversion in non-tide operation is mostly based on the polynomial fitting method. The accuracy of this method is influenced by the distribution of datum control points, topographic relief and operation ranges. In this paper, we present a method to construct a depth datum geodesic height model, which can directly obtain a bathymetric database of depth data in a GNSS bathymetric survey. The model incorporates the continuous depth datum and the mean sea level of geodetic height in the same area. Through the numerical simulation of tidal wave motion in regional water, the tidal model is obtained. Based on the grid model, the tidal level is extracted from the tidal model for harmonic analysis, and a continuous depth datum model is established. Mean sea level geodetic height is from the CNES-CLS2015 Average Sea Surface Model. In this paper, the model is confirmed in the South Yellow Sea area. The results show that the accuracy of the depth datum model, and the depth datum geodetic height model meets the accuracy requirements of the datum.