Urban Remote Sensing. Группа авторов

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Urban Remote Sensing - Группа авторов


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users can have more direct control of the geographic extent of an area of interest (AOI), the spatial resolution of the image data, and the temporal resolution of the datasets by creating predefined flight missions. These variables can be influenced by adjusting the flight height and temporal intervals between multiple flight missions, respectively (Singh and Frazier, 2018). In this way, researchers can collect data only in the AOI with the desired resolution that can capture the variation of a phenomenon without getting needlessly too detailed (or needlessly taking too long). Many efforts have been made to improve urban mapping using active remote sensing through platforms mounted with high accuracy sensors, such as radar or light detection and ranging (LiDAR) sensors (Tison et al., 2004; Gonzalez‐Aguilera et al., 2012; Ban et al., 2015; Wurm et al., 2017). Due to advancements in photogrammetry, both spectral information and elevational information can be derived from UAS images. By mounting different sensors or cameras, UAS can also capture multi‐sourced information including hyperspectral information, thermal information, and laser scanning images in the same flight period, which can greatly very valuable for urban remote sensing. In addition to still imagery, UAS is also capable of recording videos, which can provide important geographic and environmental information of an AOI.

      This chapter discusses both the opportunities and challenges of UAS in urban applications. It is organized into five sections covering the advantages of UAS in urban remote sensing, common UAS models and camera types, UAS data collection and data processing, urban applications using UAS, major challenges and possible solutions, and conclusion and prospects.

      3.2.1 COMMON MODELS

      In recent years, there has been dramatic technological development in the UAS models available for remote sensing applications. In addition to a notable increase in publications over the last decade regarding high‐accuracy remote sensing applications with UAS for aerial photogrammetry and three‐dimensional (3D) modeling (e.g. Remondino et al., 2011; Colomina and Molina, 2014; Toth et al., 2015; Agüera‐Vega et al., 2017; Erenoglu et al., 2018), there has also been an increase in the development of unique UAS platform designs for specific environmental settings (such as urban versus rural) (Chauhan, 2019; Yao et al., 2019). As more industries and disciplines are adopting the technology for their own purposes, more unique and specialized UAS models are being developed to meet the needs. Industries that operate in urban environments are developing UAS that can meet their unique environmental challenges, such as operations over tall buildings, power lines, high traffic, and groups of people, whereas other industries that operate in more rural settings might be focusing on other factors, such as covering large areas efficiently, flight length, and accessibility to the site of analysis. Although there are a wide variety of highly specialized UAS platforms available, most of them can be generally classified into either fixed‐wing or multi‐rotor systems (Saeed et al., 2018).

      Multi‐rotor UAS, on the other hand, are configured with multiple propellers in a symmetrical distribution around a central hub that allows positioning very precisely while the platform is in the air (Sámano et al., 2013). As Nascimento and Saska (2019) noted, there has been significant technological growth in multi‐rotor platforms over the last two decades. More specifically, the core components necessary for multi‐rotor designs to function in an efficient manner have improved in their technological capabilities, which has encouraged the large growth of the commercial UAS market. This technological growth can be seen in the surge of relatively low‐cost, yet high‐quality multi‐rotor platforms becoming more widely available for both research and commercial purposes since 2010 (Norouzi Ghazbi et al., 2016; Yao et al., 2019). Since a multi‐rotor UAS has multiple propellers operating at the same time, the flight times tend to be much shorter in duration compared to fixed‐wing platforms. The multiple propellers are in constant motion which generates vertical lift for the UAS, thus enabling the platform to hover in place. The ability to hover in place is what arguably makes multi‐rotor platforms more user‐friendly for less experienced UAS operators, as well as allow operators to conduct flights in more crowded areas. The ability to change direction with multi‐rotor UAS is enabled by varying each individual propeller’s thrust and torque, all of which are controlled by an onboard autopilot system that assists the pilot in controlling the positioning of the UAS so the pilot does not have to control each individual propeller. Due to the user‐friendliness, the ability for precision positioning and to carry heavier payloads a multi‐rotor frequently becomes the preferred platform for urban applications (González‐Jorge et al., 2017; Singh and Frazier, 2018; Watkins et al., 2020).

      There are other UAS models beyond the above two categories, which are much less commonly used in aerial remote sensing. These models are hybridized platforms that maintain certain characteristics of both fixed‐wing and multi‐rotor models. Hybrid platforms typically maintain the aerodynamic design of a fixed‐wing platform (large wingspan, lightweight) but can perform vertical take‐off and landing (VTOL) operations, much like a multi‐rotor platform. The ability for VTOL operations enables these platforms to be used in environments that generally do not allow for fixed‐wing UAS to safely take‐off and land in. Although these hybrid platforms are still less common than their fixed‐wing and multi‐rotor counterparts, we have witnessed a surge in developing more commercially viable systems that can meet unique industry demands using these hybridized designs (Floro da Silva and Branco, 2013; Thamm et al., 2015; Aktas et al., 2016; Hu and Lanzon, 2018; Joshi et al., 2019), which suggests a trend of hybrid models being more common and potentially more viable for commercial purposes as well.

      3.2.2 CAMERAS AND SENSORS


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