Comparing leaf area index estimates in a Mediterranean forest using field measurements, Landsat 8, and Sentinel-2 data  

作　　者：Alessandro Sebastiani Riccardo Salvati Fausto Manes 

机构地区：[1]Research Centre for Forestry and Wood(FL),Council for Agricultural Research and Economics(CREA),Via Valle Della Quistione 27,00166 Rome,Italy [2]Research Institute On Terrestrial Ecosystems(IRET),National Research Council of Italy(CNR),Strada Provinciale 35d,9,00015 Monterotondo(RM),Italy [3]Presidential Estate of Castelporziano,Via Pontina 690,00128 Rome,Italy [4]Department of Environmental Biology,Sapienza University of Rome,P.Le Aldo Moro,5,00185 Rome,Italy

出　　处：《Ecological Processes》2023年第1期402-414,共13页生态过程（英文）

基　　金：Servizi Ecosistemici e Infrastrutture Verdi urbane e peri-urbane nell’area Metropolitana Romana:stima del contributo delle foreste naturali di Castelporziano nel miglioramento della qualitàdell’aria della cittàdi Roma;Accademia Nazionale delle Scienze detta dei XL,in collaborazione con Segretariato Generale della Presidenza della Repubblica;PRO-ICOS_MED Potenziamento della Rete di Osservazione ICOS-Italia nel Mediterraneo-Rafforzamento del capitale umano”funded by the Ministry of Research;PNRR,Missione 4,Componente 2,Avviso 3264/2021,IR0000032-ITINERIS-Italian Integrated Environmental Research Infrastructures System CUP B53C22002150006。

摘　　要：Background Leaf area index(LAI)is a key indicator for the assessment of the canopy’s processes such as net primary production and evapotranspiration.For this reason,the LAI is often used as a key input parameter in ecosystem services’modeling,which is emerging as a critical tool for steering upcoming urban reforestation strategies.However,LAI field measures are extremely time-consuming and require remarkable economic and human resources.In this context,spectral indices computed using high-resolution multispectral satellite imagery like Sentinel-2 and Landsat 8,may represent a feasible and economic solution for estimating the LAI at the city scale.Nonetheless,as far as we know,only a few studies have assessed the potential of Sentinel-2 and Landsat 8 data doing so in Mediterranean forest ecosystems.To fill such a gap,we assessed the performance of 10 spectral indices derived from Sentinel-2 and Landsat 8 data in estimating the LAI,using field measurements collected with the LI-COR LAI 2200c as a reference.We hypothesized that Sentinel-2 data,owing to their finer spatial and spectral resolution,perform better in estimating vegetation’s structural parameters compared to Landsat 8.Results We found that Landsat 8-derived models have,on average,a slightly better performance,with the best model(the one based on NDVI)showing an R^(2) of 0.55 and NRMSE of 14.74%,compared to R^(2) of 0.52 and NRMSE of 15.15%showed by the best Sentinel-2 model,which is based on the NBR.All models were affected by spectrum saturation for high LAI values(e.g.,above 5).Conclusion In Mediterranean ecosystems,Sentinel-2 and Landsat 8 data produce moderately accurate LAI estimates during the peak of the growing season.Therefore,the uncertainty introduced using satellite-derived LAI in ecosystem services’assessments should be systematically accounted for.

关 键 词：Mediterranean forest Leaf area index Field measurement Multispectral satellite imagery Sentinel-2 Landsat 8 Spectral vegetation index Global change 

分 类 号：S758[农业科学—森林经理学]