# Remote Sensing in Urban Forestry:
## 1 Introduction  
The world is experiencing accelerated urbanisation and growth of cities [1, 2], which have dramatically changed the urban landscape [3, 4, 5]. Though frequently escaping our notice, a mosaic of fragmented habitats exists, ranging from remnant natural, modified natural, semi-natural, emulated natural or entirely human-created, where diverse trees and other vegetation thrive [6, 7]. Collectively, all woods and trees within a city boundary are defined as an urban forest, including individual trees, forest stands, and their associated biotic and abiotic components [8, 9, 10, 11]. Complex forest patches are a critical component of urban ecosystems. They provide a full spectrum of ecosystem services, referring to the benefits that human populations obtain directly or indirectly [7, 12, 13] from natural ecosystems [14, 15], which serve as the basis of economic development and social wellbeing [16, 17, 18]. Some well-recognised and well-studied examples of urban forest ecosystem services include alleviating summer heat through evaporation and shading [19, 20], reducing stormwater runoff by intercepting and absorbing water and improving infiltration [21, 22], enhancing air quality by removing gaseous pollutants and particulate matter [23], reducing greenhouse gas emissions by storing and sequestering a considerable amount of carbon [24, 25, 26, 27]; addressing food security by supplying food, medicine and materials [28], pollination [29, 30, 31], outdoor recreation opportunities [1, 32], as well as serving as important places for aesthetics and spirituality [33, 34]. In line with the increasing recognition of the importance of urban forest ecosystem services, there are calls around the world for the adequate installation and sustainable management of urban forests to maintain environmental health, improve the resilience of urban ecosystems, and enhance the quality of urban life [2; 35; 36]. Given their great socio-ecological complexity and dynamics, urban forests are by no means stationary [4; 11; 37]. The successful management of urban forests for the steady and sustainable provision of a full spectrum of ecosystem services requires timely and accurate information on the status, trends, and information about interactions between socioeconomic and ecological processes pertaining to urban forests occurring at multiple temporal and spatial scales [2; 35; 38; 39]. Traditionally, such information has been obtained by random field sampling and visual interpretation of aerial photos, which are expensive, generally labour-intensive and time-consuming, and usually cannot provide complete coverage of relatively large areas of interest [40; 41; 42]. These traditional approaches have curtailed the accurate, consistent, replicable, and spatially explicit measurement of spatiotemporal changes of urban forests and the associated evaluation of ecosystem service provision [43; 44]. Consequently, research faces challenges due to non-uniform and multifunctional approaches, different methodologies, and a lack of relevant information [27]. Fortunately, remote sensing, especially the latest advanced techniques and sensors (e.g., light detection and ranging LiDAR technology, hyperspectral imagery, high spatial resolution satellite imagery), has emerged as a premier and useful observational and analytical tool that offers a fast, replicable, objective, efficient, scalable, and cost-effective way to assess and quantify urban forest dynamics at varying spatiotemporal scales [5; 43; 45]. For instance, the structural (3D arrangement of vegetation, such as tree height, volume and size of foliage and stems), compositional (species richness and diversity), and functional (ecological processes) characteristics of an individual tree, urban forest patch, or all urban forests in large areas can be detected, measured, mapped, inventoried, classified, monitored, modelled, and evaluated using remote sensing techniques [35; 46].