摘要
利用LandsatTM5数据，结合地面调查，对我国鲁西黄泛平原典型地区菏泽市的杨树人工林碳储量进行测算。结果表明：单木生物量模型lnB=2．4861nD-2．415（R2=0．879，P〈0．05），拟合效果较好；基于TM5影像提取的包括6个原始波段（TMl～TM5、TM7）的光谱反射率、归一化植被指数NDVI、差值植被指数DVI、比值植被指数RVI、主成分变换得到的3个主分量及缨帽变换得到的亮度、绿度和湿度等在内的15个参数，及单波段反射率线性或非线性变换后产生的11个新参数，通过多元回归分析建立生物量遥感回归模型B=1765．412＋7378．8841n ρ4＋2113．781×1／ρ4＋14．541×1/ρ1（R2=0．754，P〈0．01），检验结果表明模拟值与实测值平均相对误差为7．65％，预测精度较高。据该生物量遥感回归模型估算得出菏泽市杨树人工林碳储量为13．93Tg，占山东省森林植被总碳储量的25．39％；林木碳密度为43．82t／hm2，比全国杨树林平均碳密度高21．82％。菏泽市73．22％的杨树人工林碳密度小于57t／hm2，固碳增汇潜力巨大。
In this study, the carbon storage of poplar plantations in Heze, Shandong Province was estimated based on Landsat TM5 data. Firstly, based on field survey data, the tree biomass estimation model was built before calculating biomass in plot level with DBH as an input variable. Then, on the basis of correlations between forest biomass and remote sensing data, a multiple regression model was built. The derived model for tree biomass estimation was lnB = 2. 4861nD - 2. 415, and its multiple correlation coefficient was 0. 879 （ P 〈 0.05）. Model B = 1 765. 412 ＋ 7 378. 884 ln ρ4 ＋ 2 113. 781 ×1/ρ4 ＋ 14. 541× 1/ρ1 was appropriate for estimating biomass of poplars in the target area, with its multiple correlation coefficient was 0. 754（P 〈0.01 ）. Carbon storage of poplar plantations was 13.93 Tg, which accounted for 25.39% of carbon storage of forest vegetation in Shandong Province. The carbon density was 43.82 t/ hm2, as much as 21.82% more than the national average level. The area of poplar plantations had reached 3. 179 ×105 hm2. In addition, 73.22% of poplar carbon density was lower than 57 t/hm2 , and it presented a homogeneity in spatial distribution. In sum, poplar plays an important role in carbon sequestration for Heze City of Shandong Province, eastern China.
出处
《北京林业大学学报》
CAS
CSCD
北大核心
2013年第6期36-41,共6页
Journal of Beijing Forestry University
基金
"十一五"国家科技支撑计划课题(2008BAD95B07)
林业公益性行业科研专项(201004004)
关键词
TM数据
生物量模型
碳密度
碳汇
TM data
biomass model
carbon density
carbon sink
