DOI: 10.1016/j.jag.2016.07.008
Scopus记录号: 2-s2.0-84996587387
论文题名: Above ground biomass and tree species richness estimation with airborne lidar in tropical Ghana forests
作者: Vaglio Laurin G ; , Puletti N ; , Chen Q ; , Corona P ; , Papale D ; , Valentini R
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2016
卷: 52 起始页码: 371
结束页码: 379
语种: 英语
英文关键词: Biomass
; Carbon monitoring
; Lidar
; Species richness
; Tropical forests
; West Africa
英文摘要: Estimates of forest aboveground biomass are fundamental for carbon monitoring and accounting; delivering information at very high spatial resolution is especially valuable for local management, conservation and selective logging purposes. In tropical areas, hosting large biomass and biodiversity resources which are often threatened by unsustainable anthropogenic pressures, frequent forest resources monitoring is needed. Lidar is a powerful tool to estimate aboveground biomass at fine resolution; however its application in tropical forests has been limited, with high variability in the accuracy of results. Lidar pulses scan the forest vertical profile, and can provide structure information which is also linked to biodiversity. In the last decade the remote sensing of biodiversity has received great attention, but few studies focused on the use of lidar for assessing tree species richness in tropical forests. This research aims at estimating aboveground biomass and tree species richness using discrete return airborne lidar in Ghana forests. We tested an advanced statistical technique, Multivariate Adaptive Regression Splines (MARS), which does not require assumptions on data distribution or on the relationships between variables, being suitable for studying ecological variables. We compared the MARS regression results with those obtained by multilinear regression and found that both algorithms were effective, but MARS provided higher accuracy either for biomass (R2 = 0.72) and species richness (R2 = 0.64). We also noted strong correlation between biodiversity and biomass field values. Even if the forest areas under analysis are limited in extent and represent peculiar ecosystems, the preliminary indications produced by our study suggest that instrument such as lidar, specifically useful for pinpointing forest structure, can also be exploited as a support for tree species richness assessment. © 2016 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/80037
Appears in Collections: 气候变化事实与影响
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作者单位: Department for Innovation in Biological, Agro-Food and Forest Systems (DIBAF), University of TusciaViterbo, Italy; Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria, Forestry Research Centre (CREA-SEL), Viale Santa Margherita 80, Arezzo, Italy; Department of Geography, University of Hawai‘i at Mānoa, 422 Saunders Hall, 2424 Maile Way, Honolulu, HI, United States; Impacts of Agriculture, Forests and Ecosystem Services Division, Euro-Mediterranean Center on Climate Change (IAFES-CMCC), via Pacinotti 5Viterbo, Italy
Recommended Citation:
Vaglio Laurin G,, Puletti N,, Chen Q,et al. Above ground biomass and tree species richness estimation with airborne lidar in tropical Ghana forests[J]. International Journal of Applied Earth Observation and Geoinformation,2016-01-01,52