Abstract. Urban heat island (UHI) is considered a serious environmental issue in highly urbanized cities such as Singapore. To better quantify the UHI intensity, the local climate zones (LCZ) classification scheme was adopted to characterize land covers, and describe and compare their thermal performance. There are three commonly used LCZ classification approaches: manual sampling,World Urban Database and Access Portal Tools (WUDAPT) processing method using remote sensing, and geographical information system (GIS)-based method. Based on the current implementation of WUDAPT Level 0 method in the classification work in Singapore, the principal limitations are expounded. To overcome the deficiencies, street view imagery (SVI), which carries substantial urban spatial information, is regarded as a promising data source. This paper reviews the potential of SVI to better estimate certain LCZrelated properties, such as sky view factor (SVF). As it allows a detailed view on the ground objects, SVI opens up the possibility of identifying surface properties such as albedo, as well as anthropogenic heat sources. Although it is not a novel idea, there has been a lack of a comprehensive use of SVI in assisting LCZ classification from the ground up, especially in a high-density city such as Singapore. This paper overviews potential ways to incorporate SVI and identifies challenges such as coarse temporal resolution and spatial coverage constrained to drivable roads.
A nominally circular 2-D broadband acoustic array of 1.3-m diameter, comprising 508 sensors and associated electronics, was designed, built, and tested for ambient noise imaging (ANI) potential in Singapore waters. The system, named Remotely Operated Mobile Ambient Noise Imaging System (ROMANIS), operates over 25-85 kHz, streaming real-time data at 1.6 Gb/s over a fiber optic link. By using sensors that are much larger than halfwavelength at the highest frequency of interest, so with some directionality, good beamforming performance is obtained with a small number of sensors compared to a conventional half-wavelength-spaced array. A data acquisition system consisting of eight single-board computers enables synchronous data collection from all 508 sensors. A dry-coupled neoprene cover is used to encapsulate the ceramic elements as an alternative to potting or oil filling, for easier maintenance. Beamforming is performed in real-time using parallel computing on a graphics processing unit (GPU). Experiments conducted in Singapore waters yielded images of underwater objects at much larger ranges and with better resolution than any previous ANI system. Although ROMANIS was designed for ANI, the array may be valuable in many other applications requiring a broadband underwater acoustic receiving array.Index Terms-Ambient noise imaging (ANI), broadband array design, underwater acoustics, data acquisition.
With the ever-increasing number of underwater assets and structures driven by the energy industry's shift to renewables, the need for reliable long-term remote monitoring solutions for both environments and assets is growing. Such solutions typically consist of a suite of sensors, the data transfer mechanism, and data analytics and visualization. Underwater wireless technology is the key enabler for such a holistic monitoring solution that can be used for a variety of applications. However, many commercial operations are designed around the assumption that underwater wireless technology is not yet suitable for today's operational needs. While there are several advancements in the domain of underwater wireless systems in recent times, they have not made it to operational commercial systems. In this paper, we look at the example of Acoustic Doppler Current Profilers (ADCPs), where a typical operation relies on either offline data download or using a cable to perform real-time data transfer. We then illustrate how such an operation can be transformed by integrating a smart modem that packs technologies such as software-defined design, edge computing, and machine learning along with robust and reliable high-speed underwater wireless communications to an ADCP to achieve flexible and reliable wireless data transfer. The software-defined design aspect allows easy integration to a variety of sensors, in this example an ADCP. The edge computing and machine learning aspects allow the modems to optimize the data for a high-speed acoustic link that supports adaptive modulation and automatic retransmission to avoid data loss. Smart scheduling techniques are incorporated into the solution to support extremely low-power modes to enable long-term deployments. An application-specific web-based user interface (UI) provides a seamless user experience during the whole operation. Integrating such innovations to form a holistic solution for long-term monitoring can drive down overall costs and improve operational safety.
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