DOI: 10.1016/j.jag.2014.03.004
Scopus记录号: 2-s2.0-84904468054
论文题名: Object based change detection of central Asian Tugai vegetation with very high spatial resolution satellite imagery
作者: Gärtner P ; , Förster M ; , Kurban A ; , Kleinschmit B
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 31, 期: 1 起始页码: 110
结束页码: 121
语种: 英语
英文关键词: Populus euphratica
; Quickbird
; Riparian forest
; Tree crown delineation
; Tree detection
; Worldview2
Scopus关键词: deciduous tree
; detection method
; NDVI
; QuickBird
; restoration ecology
; riparian forest
; satellite imagery
; spatial resolution
; tree
; Central Asia
英文摘要: Ecological restoration of degraded riparian Tugai forests in north-western China is a key driver to com-bat desertification in this region. Recent restoration efforts attempt to recover the forest along with its most dominant tree species, Populus euphratica. The present research observed the response of natural vegetation using an object based change detection method on Quick Bird (2005) and WorldView2 (2011) data. We applied the region growing approach to derived Normalized Difference Vegetation Index (NDVI) values in order to identify single P. euphratica trees, delineate tree crown areas and quantify crown diam-eter changes. Results were compared to 59 reference trees. The findings confirmed a positive tree crown growth and suggest a crown diameter increase of 1.14 m, on average. On a single tree basis, tree crown diameters of larger crowns were generally underestimated. Small crowns were slightly underestimated in QuickBird and overestimated in Worldview2 images. The results of the automated tree crown delin-eation show a moderate relation to field reference data with R2 2005: 0.36 and R2 2011: 0.48. The object based image analysis (OBIA) method proved to be applicable in sparse riparian Tugai forests and showed great suitability to evaluate ecological restoration efforts in an endangered ecosystem. © 2014 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79700
Appears in Collections: 气候变化事实与影响
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作者单位: Geoinformation in Environmental Planning Lab, Technische Universität Berlin, Berlin 10623, Germany; Xinjiang Institute of Ecology and Geography, Chinese Academy of Science, Urumqi 830046, China
Recommended Citation:
Gärtner P,, Förster M,, Kurban A,et al. Object based change detection of central Asian Tugai vegetation with very high spatial resolution satellite imagery[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,31(1)