DOI: 10.1016/j.jag.2016.06.020
Scopus记录号: 2-s2.0-84997701977
论文题名: Performance of vegetation indices from Landsat time series in deforestation monitoring
作者: Schultz M ; , Clevers J ; G ; P ; W ; , Carter S ; , Verbesselt J ; , Avitabile V ; , Quang H ; V ; , Herold M
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2016
卷: 52 起始页码: 318
结束页码: 327
语种: 英语
英文关键词: Accuracy assessment
; BFAST monitor
; Deforestation
; Landsat
; Time series analysis
; Vegetation indices
Scopus关键词: accuracy assessment
; deforestation
; Landsat
; monitoring
; NDVI
; performance assessment
; remote sensing
; time series
; time series analysis
; vegetation index
英文摘要: The performance of Landsat time series (LTS) of eight vegetation indices (VIs) was assessed for monitoring deforestation across the tropics. Three sites were selected based on differing remote sensing observation frequencies, deforestation drivers and environmental factors. The LTS of each VI was analysed using the Breaks For Additive Season and Trend (BFAST) Monitor method to identify deforestation. A robust reference database was used to evaluate the performance regarding spatial accuracy, sensitivity to observation frequency and combined use of multiple VIs. The canopy cover sensitive Normalized Difference Fraction Index (NDFI) was the most accurate. Among those tested, wetness related VIs (Normalized Difference Moisture Index (NDMI) and the Tasselled Cap wetness (TCw)) were spatially more accurate than greenness related VIs (Normalized Difference Vegetation Index (NDVI) and Tasselled Cap greenness (TCg)). When VIs were fused on feature level, spatial accuracy was improved and overestimation of change reduced. NDVI and NDFI produced the most robust results when observation frequency varies. © 2016 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/80014
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, Droevendaalsesteeg 3, Wageningen, Netherlands; Forest Inventory and Planning Institute, Ministry of Agriculture and Rural Development, Vinh Quynh—Thanh Tri, Ha Noi, Viet Nam
Recommended Citation:
Schultz M,, Clevers J,G,et al. Performance of vegetation indices from Landsat time series in deforestation monitoring[J]. International Journal of Applied Earth Observation and Geoinformation,2016-01-01,52