Urban vegetation monitoring in Hong Kong using high resolution multispectral images

$61.20 plus tax (Refund Policy)

Buy Article:


Very high resolution (VHR) satellite remote sensing systems are now capable of providing imagery with similar spatial detail to aerial photography, but with superior spectral information. This research investigates the hypothesis that it should be possible to use multispectral IKONOS images to quantify urban vegetation, obtaining similar accuracy to that achieved from false colour aerial photographs. Two parameters, vegetation cover and vegetation density are used to represent biomass in the study area (Kowloon, Hong Kong), for which data is collected for 41 field quadrats. Regression equations relating the field measurements of vegetation density to image wavebands obtained similar high correlations for both image types and lower but significant correlations for vegetation cover. Vegetation density is a quantifiable measure of vegetation in multiple layers above ground, representing the total amount of biomass and is thus well able to indicate the diverse structural types of vegetation found in urban areas. Furthermore it can be accurately measured using the IKONOS green/red ratio (Chlorophyll Index). The superiority of the latter to the more commonly used Normalized Difference Vegetation Index (NDVI), is attributed to the sub-optimal timing of the imagery during the dry season, and its greater sensitivity to multiple layering within the vegetation canopy. A time and cost comparison between the two image types suggests that the use of IKONOS images is much more cost effective than aerial photographs for urban vegetation monitoring.

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/01431160412331291198

Affiliations: Department of Land Surveying and Geo‐Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong

Publication date: March 1, 2005

More about this publication?
Related content

Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more