DOI: 10.1016/j.jag.2013.03.004
Scopus记录号: 2-s2.0-84883806914
论文题名: Remote sensing as a tool for monitoring plant invasions: Testing the effects of data resolution and image classification approach on the detection of a model plant species Heracleum mantegazzianum (giant hogweed)
作者: Müllerová J ; , Pergl J ; , Pyšek P
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2013
卷: 25, 期: 1 起始页码: 55
结束页码: 65
语种: 英语
英文关键词: Accuracy assessment Historical aerial VHR photography
; Invasion progress
; Object-based
; Pixel-based classification
; Rapid Eye
Scopus关键词: accuracy assessment
; biodiversity
; biomonitoring
; ecosystem function
; image classification
; image processing
; image resolution
; invasive species
; landscape
; pixel
; plant
; remote sensing
; satellite data
; spatial resolution
; Heracleum
; Heracleum mantegazzianum
; Heracleum sphondylium
英文摘要: Plant invasions represent a threat not only to biodiversity and ecosystem functioning but also to the character of traditional landscapes. Despite the worldwide efforts to control and eradicate invasive species, their menace grows. New techniques enabling fast and precise monitoring and providing information on spatial structure of invasions are needed for efficient management strategies to be implemented. We present remote sensing assessment of a noxious invasive species Heracleum mantegazzianum (giant hogweed) that integrates different data sources, spatial and spectral resolutions, and image processing techniques. Panchromatic, multispectral and color very high spatial resolution (VHR) aerial photography (1947-2006, resolution 0.5 m), and medium spatial resolution satellite data (Rapid Eye 2010, resolution 5 m) were analyzed to assess their potential for hogweed monitoring by using pixel-(both supervised and unsupervised) and object-based image analysis (OBIA, automated hierarchical, iterative, and rule-based). Both point and grid based accuracy assessment was carried out. Described methods of object-based image analysis of VHR data enabled monitoring of hogweed at high classification accuracies measured by various means, regardless of the spectral resolution of the data provided that the data came from the species flowering period. Although the proposed automated processing of VHR data is relatively time-effective and standardized, application over large areas would be rather demanding due to the size of datasets, and multispectral satellite data of medium spatial resolution (lower than the size of individuals) was therefore tested. On such imagery, only larger stands could be identified but still the pixel-based supervised classification achieved moderate accuracy. Depending on the size of the area of interest and the detail needed the very high or medium spatial resolution data (acquired at the species flowering period) are to be used. High accuracies achieved for VHR data indicate the possible application of described methodology for monitoring invasions and their long-term dynamics elsewhere, making management measures comparable precise, fast and efficient. © 2013 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79850
Appears in Collections: 气候变化事实与影响
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作者单位: Institute of Botany, Academy of Sciences of the Czech Republic, CZ-252 43 Průhonice, Czech Republic; Department of Ecology, Faculty of Science, Charles University, Viničná 7, CZ-128 01 Praha, Czech Republic; Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, Matieland 7602, South Africa
Recommended Citation:
Müllerová J,, Pergl J,, Pyšek P. Remote sensing as a tool for monitoring plant invasions: Testing the effects of data resolution and image classification approach on the detection of a model plant species Heracleum mantegazzianum (giant hogweed)[J]. International Journal of Applied Earth Observation and Geoinformation,2013-01-01,25(1)