NDLI: Toward automatic estimation of urban green volume using airborne LiDAR data and high resolution Remote Sensing images

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Toward automatic estimation of urban green volume using airborne LiDAR data and high resolution Remote Sensing images

Content Provider	Springer Nature Link
Author	Huang, Yan Yu, Bailang Zhou, Jianhua Hu, Chunlin Tan, Wenqi Hu, Zhiming Wu, Jianping
Copyright Year	2012
Abstract	Urban green volume is an important indicator for analyzing urban vegetation structure, ecological evaluation, and green-economic estimation. This paper proposes an object-based method for automated estimation of urban green volume combining three-dimensional (3D) information from airborne Light Detection and Ranging (LiDAR) data and vegetation information from high resolution remotely sensed images through a case study of the Lujiazui region, Shanghai, China. High resolution airborne near-infrared photographs are used for identifying the urban vegetation distribution. Airborne LiDAR data offer the possibility to extract individual trees and to measure the attributes of trees, such as tree height and crown diameter. In this study, individual trees and grassland are identified as the independent objects of urban vegetation, and the urban green volume is computed as the sum of two broad portions: individual trees volume and grassland volume. The method consists of following steps: generating and filtering the normalized digital surface model (nDSM), extracting the nDSM of urban vegetation based on the Normalized Difference Vegetation Index (NDVI), locating the local maxima points, segmenting the vegetation objects of individual tree crowns and grassland, and calculating the urban green volume of each vegetation object. The results show the quantity and distribution characteristics of urban green volume in the Lujiazui region, and provide valuable parameters for urban green planning and management. It is also concluded from this paper that the integrated application of LiDAR data and image data presents an effective way to estimate urban green volume.
Starting Page	43
Ending Page	54
Page Count	12
File Format	PDF
ISSN	20950195
Journal	Frontiers of Earth Science in China
Volume Number	7
Issue Number	1
e-ISSN	20950209
Language	English
Publisher	SP Higher Education Press
Publisher Date	2012-10-02
Publisher Institution	Chinese Universities
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	urban green volume LiDAR remote sensing image object-based method automatic estimation Earth Sciences
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences

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