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Testing the consistency for mapping urban vegetation with high-altitude aerial photographs and landsat MSS data

Remote Sensing of Environment

By:
, , and
DOI: 10.1016/0034-4257(87)90050-2

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Abstract

Two methods of analysis were evaluated for mapping urban vegetation on high-altitude, color-infrared aerial photographs and Landsat MSS data of Syracuse, NY. The first method consisted of defining the spatial patterns (strata) of urban vegetation occurrence. The second method discriminated woody and herbaceous vegetation classes within defined strata. Emphasis was placed on evaluating the consistency of each method. Results indicate that consistent spatial patterns of urban vegetation strata were not achieved on either of the two data types tested due to the spatial complexity of the urban vegetation. However, for discriminating woody and herbaceous vegetation classes within defined strata, good consistency was noted among the interpreters of the high-altitude aerial photographs. The coarse spatial resolution of the Landsat MSS data resulted in low precision for identifying these two vegetation classes in this highly urbanized area. Where photointerpretation efforts are intended for mapping vegetation within numerous urban areas, the estimation of proportions of vegetation classes within defined strata should be a data analysis procedure more objective and consistently repeatable than is the delineation of vegetation patterns. 

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Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Testing the consistency for mapping urban vegetation with high-altitude aerial photographs and landsat MSS data
Series title:
Remote Sensing of Environment
DOI:
10.1016/0034-4257(87)90050-2
Volume
21
Issue:
2
Year Published:
1987
Language:
English
Publisher:
Elsevier
Contributing office(s):
Earth Resources Observation and Science (EROS) Center (Geography)
Description:
13 p.
First page:
129
Last page:
141
Country:
United States
State:
New York
County:
Syracuse
Online Only (Y/N):
N
Additional Online Files(Y/N):
N