基于野外样点实测数据,根据火烧迹地各组分生物量,构建了火烧烈度的量化指标:火烧烈度指数(Fire Severity Index,FSI)。依据构建的FSI,对过火林分的火烧烈度进行了量化分级,并通过野外记录的综合火烧指数(Composite Burn Index,CBI),对FSI进行验证分析。结果表明:FSI能够直接量化火烧烈度严重性,可准确地揭示不同火烧烈度对林分生物量和碳储量的影响程度。
Based on the field inventory data,the quantitative index of fire severity(Fire Severity Index,FSI)was established.The grading of fire severity was conducted by means of FSI.According to CBI (composite burn index)from fieldwork,verification of FSI was put in effect.The results showed that FSI could directly quantify fire severity and accurately reveal effect of different fire severities on forest biomass and carbon storage.
[1] 王晓莉,王文娟,常禹,等.基于NBR指数分析大兴安岭呼中森林过火区的林火烈度[J].应用生态学报,2013,24(4):967-974.
[2] 常禹,陈宏伟,胡远满,等.林火烈度评价及其空间异质性研究进展[J].自然灾害学报,2012,21(2):28-34.
[3] Lentile L B,Smith F W,Shepperd W D.Influence of topography and forest structure on patterns of mixed severity fire in ponderosa pine forests of the South Dakota Black Hills,USA[J].International Journal of Wildland Fire,2006,15(4):557-566.
[4] Barrett K,Kasischke E S,McGuire A D,et al.Modeling fire severity in black spruce stands in the Alaskan boreal forest using spectral and non-spectral geospatialdata[J].Remote Sensing of Environment,2010,114(7):1494-1503.
[5] Soverel N O,Perrakis D D B,Coops N C.Estimating burn severity from Landsat dNBR and RdNBR indices across western Canada[J].Remote Sensing of Environment,2010,114(9):1896-1909.
[6] Escuin S,Navarro R,Fernandez P.Fire severity assessment by using NBR (Normalized Burn Ratio)and NDVI (Normalized Difference Vegetation Index)derived from LANDSAT TM/ETM images[J].International Journal of Remote Sensing,2008,29(4):1053-1073.
[7] Allen J L,Sorbel B.Assessing the differenced Normalized Burn Ratio’s ability to map burn severity in the boreal forest and tundra ecosystems of Alaska’s national parks[J].International Journal of Wildland Fire,2008,17(4):463-475.
[8] Miller J D,Thode A E.Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR)[J].Remote Sensing of Environment,2007,109(1):66-80.
[9] Miller J D,Knapp E E,Key C H,et al.Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR)to three measures of fire severity in the Sierra Nevada and Klamath Mountains,California,USA[J].Remote Sensing of Environment,2009,113(3):645-656.
[10] Wu Z,He H S,Liang Y,et al.Determining relative contributions of vegetation and topography to burn severity from LANDSAT imagery[J].Environ Manage,2013,52(4):821-836.
[11] Epting J,Verbyla D,Sorbel B.Evaluation of remotely sensed indices for assessing burn severity in interior Alaska using Landsat TM and ETM+[J].Remote Sensing of Environment,2005,96(3):328-339.
[12] Hoy E E,French N H F,Turetsky M R,et al.Evaluating the potential of Landsat TM/ETM+imagery for assessing fire severity in Alaskan black spruce forests[J].International Journal of Wildland Fire,2008,17(4):500-514.
[13] 刘志华,常禹,胡远满,等.呼中林区与呼中自然保护区森林粗木质残体储量的比较[J].植物生态学报,2009,33(6):1075-1083.
[14] Waddell K L.Sampling coarse woody debris for multiple attributes in extensive resource inventories[J].Ecological indicators,2002,1(3):139-153.
[15] 王晓莉,常禹,陈宏伟,等.黑龙江省大兴安岭森林生物量空间格局及其影响因素[J].应用生态学报,2014,25(4):974-982.
[16] 闫平,高述超,刘德晶.兴安落叶松林3个类型生物及土壤碳储量比较研究[J].林业资源管理,2008(3):77-81.