DOI: 10.1016/j.jag.2013.01.003
Scopus记录号: 2-s2.0-84880301950
论文题名: Analyzing fine-scale wetland composition using high resolution imagery and texture features
作者: Szantoi Z ; , Escobedo F ; , Abd-Elrahman A ; , Smith S ; , Pearlstine L
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2013
卷: 23, 期: 1 起始页码: 204
结束页码: 212
语种: 英语
英文关键词: High resolution imagery
; Image texture
; Support vector machine
; Wetland mapping
Scopus关键词: accuracy assessment
; algorithm
; image analysis
; image classification
; image resolution
; mapping
; maximum likelihood analysis
; NDVI
; wetland
; Everglades National Park
; Florida [United States]
; United States
英文摘要: In order to monitor natural and anthropogenic disturbance effects to wetland ecosystems, it is necessary to employ both accurate and rapid mapping of wet graminoid/sedge communities. Thus, it is desirable to utilize automated classification algorithms so that the monitoring can be done regularly and in an efficient manner. This study developed a classification and accuracy assessment method for wetland mapping of at-risk plant communities in marl prairie and marsh areas of the Everglades National Park. Maximum likelihood (ML) and Support Vector Machine (SVM) classifiers were tested using 30.5 cm aerial imagery, the normalized difference vegetation index (NDVI), first and second order texture features and ancillary data. Additionally, appropriate window sizes for different texture features were estimated using semivariogram analysis. Findings show that the addition of NDVI and texture features increased classification accuracy from 66.2% using the ML classifier (spectral bands only) to 83.71% using the SVM classifier (spectral bands, NDVI and first order texture features). © 2013 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79826
Appears in Collections: 气候变化事实与影响
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作者单位: School of Forest Resources and Conservation - Geomatics Program, University of Florida, Gainesville, FL, United States; School of Forest Resources and Conservation, University of Florida, Gainesville, FL, United States; Everglades and Dry Tortugas National Parks, Homestead, FL, United States
Recommended Citation:
Szantoi Z,, Escobedo F,, Abd-Elrahman A,et al. Analyzing fine-scale wetland composition using high resolution imagery and texture features[J]. International Journal of Applied Earth Observation and Geoinformation,2013-01-01,23(1)