DOI: 10.1016/j.jag.2015.12.005
Scopus记录号: 2-s2.0-84988736499
论文题名: Estimation of canopy attributes in beech forests using true colour digital images from a small fixed-wing UAV
作者: Chianucci F ; , Disperati L ; , Guzzi D ; , Bianchini D ; , Nardino V ; , Lastri C ; , Rindinella A ; , Corona P
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2016
卷: 47 起始页码: 60
结束页码: 68
语种: 英语
英文关键词: Cover photography
; Drone
; Fagus sylvatica
; Hemispherical photography
; Leaf area index
; Sensefly eBee
Scopus关键词: digital image
; estimation method
; forest canopy
; forest cover
; leaf area index
; photography
; remote sensing
; unmanned vehicle
; Fagus
; Fagus sylvatica
英文摘要: Accurate estimates of forest canopy are essential for the characterization of forest ecosystems. Remotely-sensed techniques provide a unique way to obtain estimates over spatially extensive areas, but their application is limited by the spectral and temporal resolution available from these systems, which is often not suited to meet regional or local objectives. The use of unmanned aerial vehicles (UAV) as remote sensing platforms has recently gained increasing attention, but their applications in forestry are still at an experimental stage. In this study we described a methodology to obtain rapid and reliable estimates of forest canopy from a small UAV equipped with a commercial RGB camera. The red, green and blue digital numbers were converted to the green leaf algorithm (GLA) and to the CIE L*a*b* colour space to obtain estimates of canopy cover, foliage clumping and leaf area index (L) from aerial images. Canopy attributes were compared with in situ estimates obtained from two digital canopy photographic techniques (cover and fisheye photography). The method was tested in beech forests. UAV images accurately quantified canopy cover even in very dense stand conditions, despite a tendency to not detecting small within-crown gaps in aerial images, leading to a measurement of a quantity much closer to crown cover estimated from in situ cover photography. Estimates of L from UAV images significantly agreed with that obtained from fisheye images, but the accuracy of UAV estimates is influenced by the appropriate assumption of leaf angle distribution. We concluded that true colour UAV images can be effectively used to obtain rapid, cheap and meaningful estimates of forest canopy attributes at medium-large scales. UAV can combine the advantage of high resolution imagery with quick turnaround series, being therefore suitable for routine forest stand monitoring and real-time applications. © 2015 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/80138
Appears in Collections: 气候变化事实与影响
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作者单位: Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria—Forestry Research Centre, viale Santa Margherita 80, Arezzo, Italy; Università di Siena, Centro di GeoTecnologie, via Vetri Vecchi 34, San Giovanni Valdarno, Italy; Consiglio Nazionale delle Ricerche, via Madonna del Piano 10, Sesto Fiorentino, Italy; Menci Software, Loc. Tregozzano 87, Arezzo, Italy; Università di Siena, Dipartimento di Scienze Fisiche, della Terra e dell'Ambiente, Strada Laterina, 8, 53100, Siena, Italy
Recommended Citation:
Chianucci F,, Disperati L,, Guzzi D,et al. Estimation of canopy attributes in beech forests using true colour digital images from a small fixed-wing UAV[J]. International Journal of Applied Earth Observation and Geoinformation,2016-01-01,47