Title
A strategy for analyzing urban forest using Landsat ETM+ imagery
Abstract
Urban forest is of great interest to a variety of scientific and urban planning applications. This paper presents a strategy for calculating tree canopy density in urban areas using Landsat ETM+ imagery and calculating its ecological value. The strategy consists of two key steps: one is to extract urban tree canopy area from remote sensing images; the other is to calculate the ecological value of urban forest. The extraction of tree canopy area from remote sensing imagery is carried out using classification models, which are based on empirical relationships between forest coverage and the spectrum on Landsat imagery, and are generated using regression tree techniques. The calculation about urban forest is carried out introducing CITYgreen model. In the analysis, the zone inside the 4th Ring Road in Beijing is chosen as study area; and a Landsat ETM+ image taken in 2001 is used applying this strategy to analyze the urban forest. In the following part, the results of the analysis are presented. At the end, the accuracy of tree canopy density is reviewed, and some possible reasons for the error are discussed, as well as the advantages and disadvantages of this strategy.
Year
DOI
Venue
2007
10.1109/IGARSS.2007.4423219
IGARSS
Keywords
Field
DocType
urban forest coverage,remote sensing,classification models,urban forest,beijing,4th ring road,urban planning applications,citygreen model,cltygreen,urban tree canopy area extraction,regression tree,feature extraction,image classification,citygreen,landsat etm+ imagery,ecological value,tree canopy density,remote sensing images,atmospheric boundary layer,ad 2001,regression tree techniques,vegetation,spectrum,urban planning,satellites,space technology,image analysis,educational technology
Tree canopy,Decision tree,Vegetation,Computer science,Remote sensing,Feature extraction,Urban planning,Urban forest,Contextual image classification,Beijing
Conference
Volume
Issue
ISSN
null
null
2153-6996
ISBN
Citations 
PageRank 
978-1-4244-1212-9
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Chudong Huang101.35
Yun Shao212130.47
Jinsong Chen34911.29
Jinghui Liu401.35
Jieqiong Chen500.34
Jing Li600.34