2021
DOI: 10.3390/rs13234889
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Remotely Sensed Tree Characterization in Urban Areas: A Review

Abstract: Urban trees and forests provide multiple ecosystem services (ES), including temperature regulation, carbon sequestration, and biodiversity. Interest in ES has increased amongst policymakers, scientists, and citizens given the extent and growth of urbanized areas globally. However, the methods and techniques used to properly assess biodiversity and ES provided by vegetation in urban environments, at large scales, are insufficient. Individual tree identification and characterization are some of the most critical… Show more

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Cited by 12 publications
(6 citation statements)
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References 122 publications
(331 reference statements)
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“…Furthermore, it is feasible to combine high-resolution LiDAR data in conjunction with historical aerial photographs to detect tree canopy cover changes over longer time scales and over small urban forest areas when inconsistent data types are available between the two time periods [ 104 , 123 ]. Overall, we need to adopt and apply technological advancements made in the fields of precision forestry, data science, and remote sensing to improve our further understanding of the influence of urban forests and residential property values [ 43 ]. Below we provide some specific recommendations for future research based on our review of the literature.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Furthermore, it is feasible to combine high-resolution LiDAR data in conjunction with historical aerial photographs to detect tree canopy cover changes over longer time scales and over small urban forest areas when inconsistent data types are available between the two time periods [ 104 , 123 ]. Overall, we need to adopt and apply technological advancements made in the fields of precision forestry, data science, and remote sensing to improve our further understanding of the influence of urban forests and residential property values [ 43 ]. Below we provide some specific recommendations for future research based on our review of the literature.…”
Section: Discussionmentioning
confidence: 99%
“…Remote sensing offers an opportunity for better spatial and temporal analyses of forest metrics, vegetation indices, and forest regeneration over larger areas [ 6 , 10 , 43 ]. The accuracy of remote sensing-derived forest, tree and vegetation metrics have been improving with the advancements in machine learning algorithms combined with multi-temporal LiDAR (Light Detection and Ranging) point clouds and UAV (Unmanned Aerial Vehicles) images.…”
Section: Introductionmentioning
confidence: 99%
“…There have been other automatic tree indexing attempts on RGB data using machine learning models. For instance, transfer learning methods are combined with more traditional object detection architectures like R-CNN, along with triangulating coordinates from ground-level images with the aid of YOLO (Velasquez-Camacho et al, 2023). There have even been non-deep learning configurations attempting crown delineation with unsupervised algorithms like k-means (Moussaid et al, 2021).…”
Section: Introductionmentioning
confidence: 99%
“…Over the last decade, many researchers and professionals have increasingly recognized the applicability of unmanned aerial vehicles (UAVs), also known as drones, to mapping of vegetation species and communities [10][11][12][13]. Specifically, UAVs have gained popularity for vegetation mapping due to their versatility, cost-effectiveness, and ability to capture high-resolution imagery and data in a noninvasive manner [14][15][16].…”
Section: Introductionmentioning
confidence: 99%