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Justin Morgenroth

Researcher at University of Canterbury

Publications -  68
Citations -  1731

Justin Morgenroth is an academic researcher from University of Canterbury. The author has contributed to research in topics: Urban forest & Land cover. The author has an hindex of 21, co-authored 65 publications receiving 1251 citations.

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Developments in Landsat Land Cover Classification Methods: A Review

Darius Phiri, +1 more
- 19 Sep 2017 - 
TL;DR: It is suggested that the development of land cover classification methods grew alongside the launches of a new series of Landsat sensors and advancements in computer science, and many advancements in specific classifiers and algorithms have occurred in the last decade.
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The 2010–2011 Canterbury Earthquake Sequence: Environmental effects, seismic triggering thresholds and geologic legacy

TL;DR: The 2010-2011 Canterbury Earthquake Sequence (CES) as discussed by the authors is one of the best recorded historical earthquake sequences, including the moment magnitude (M w ) 7.1 Darfield earthquake and M w 6.2, 6.0, 5.9 and 5.8 aftershocks.
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Urban Tree Diversity - Taking stock and looking ahead

TL;DR: The first International Conference on Urban Tree Diversity as mentioned in this paper highlighted the need for a better understanding of the current state of urban tree diversity and highlighted the importance of tree diversity in ecosystem service provision and ecosystem stability.
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Diversification of the urban forest—Can we afford to exclude exotic tree species?

TL;DR: In this article, the authors present a set of necessary considerations for current and future discussions on native and non-native plant material in sustainable urban development using examples from Northern and Central Europe and illustrate that in some regions the catalogue of native tree species may be too limited to fulfil ecosystem services and resilience in harsh urban environments.
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3D modelling of individual trees using a handheld camera: Accuracy of height, diameter and volume estimates

TL;DR: In this paper, a multiview stereo-photogrammetry (SfM-MVS) was used to estimate 2D and 3D tree metrics with accuracy comparable to that of LiDAR.