文章基本信息

标题：Evaluating the capability of Worldview-2 imagery for mapping alien tree species in a heterogeneous urban environment
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作者：Simbarashe Jombo ; Elhadi Adam ; Marcus J. Byrne 等
期刊名称：Cogent Social Sciences
电子版ISSN：2331-1886
出版年度：2020
卷号：6
期号：1
页码：1-19
DOI：10.1080/23311886.2020.1754146
出版社：Taylor and Francis Ltd
摘要：Street trees in urban planning have a long history as providers of an amicable environment for urban dwellers. Nevertheless, street trees are not always without a challenge, their ecosystem disservices include, inter alia, cracking pavements and foundations due to wandering tree roots that destroy concrete or asphalt surfaces. Thus, effective mapping of street trees assists in planning a suitable urban environment to improve city life. The traditional method for urban tree mapping is costly, time-consuming and labour intensive. However, commercially operated multi-spectral sensors, such as WorldView (WV) provide a more viable way to map trees at the species level. This study investigates the use of WV-2 imagery in the classification and mapping of five common alien street trees in a complex urban environment. It also examined the feasibility of Random Forest (RF) and Support Vector Machines (SVM) classifiers in mapping street trees in a heterogeneous urban environment. The classifiers produced an overall accuracy of 84.2 % for RF and 81.2 % for SVM. This study provides a detailed understanding of urban tree species to the municipality of Johannesburg and offers environmental managers an insight of classification methods for mapping trees using satellite imagery to comprehend their spatial distribution.
关键词：Urban alien tree species; random forest; support vector machines; accuracy assessment; City of Johannesburg