| 近30a安吉县毛竹林动态遥感监测及碳储量变化 |
| |
| 引用本文： | 崔瑞蕊,杜华强,周国模,徐小军,董德进,吕玉龙.近30a安吉县毛竹林动态遥感监测及碳储量变化[J].浙江林学院学报,2011,28(3):422-431. |
| |
| 作者姓名： | 崔瑞蕊 杜华强 周国模 徐小军 董德进 吕玉龙 |
| |
| 作者单位： | 1. 浙江农林大学浙江省森林生态系统碳循环与固碳减排重点实验室,浙江临安,311300;浙江农林大学环境与资源学院,浙江临安,311300
2. 浙江省安吉县林业局,浙江安吉,313300 |
| |
| 基金项目： | 国家自然科学基金资助项目，国家林业局引进国际先进农业科学技术计划("948"计划)项目，浙江农林大学研究生科研创新基金资助项目 |
| |
| 摘 要： | 通过最大似然分类法从不同时期陆地资源卫星Landsat-5 TM影像中提取毛竹Phyllostachys pubescens林信息,利用变化幅度和动态度2个指标对浙江省安吉县近30 a毛竹林面积时空动态特征进行了监测、评价与分析,并初步估算了各时期竹林地上总碳储量变化情况。结果表明：①各个时期影像分类总体精度和毛竹林信息提取的精度比较好,其中总体分类精度都在85%以上,而毛竹林Kappa系数为0.80~0.95。遥感估算的毛竹林面积与森林资源清查结果相吻合,两者决定系数（R2）达到0.981;②1986-2008年期间,除昆铜乡毛竹林面积呈负增长外（变化幅度为-8.49%）,其他各乡镇的毛竹林面积呈上升趋势,变化幅度为14%~86%,以孝丰镇增长幅度最大,天荒坪镇增长幅度最小;③针叶林、阔叶林以及农业用地的变化对毛竹林总面积增加的贡献最大;④根据毛竹林动态监测结果和毛竹林地上碳密度（20.297 Mg.hm-2）估算得到1986,1991,1998,2004和2008年5个时期安吉县竹林地上碳储总量分别为1.106,1.213,1.327,1.413和1.466 Tg,呈逐渐增加趋势。图2表4参31
|
| 关 键 词： | 森林生态学 毛竹林 遥感 动态监测 碳储量 |
Remote sensing-based dynamic monitoring of moso bamboo forest and its carbon stock change in Anji County |
| |
| CUI Rui-rui,DU Hua-qiang,ZHOU Guo-mo,XU Xiao-jun,DONG De-jin,Lü Yu-long.Remote sensing-based dynamic monitoring of moso bamboo forest and its carbon stock change in Anji County[J].Journal of Zhejiang Forestry College,2011,28(3):422-431. |
| |
| Authors: | CUI Rui-rui DU Hua-qiang ZHOU Guo-mo XU Xiao-jun DONG De-jin Lü Yu-long |
| |
| Institution: | CUI Rui-rui ,DU Hua-qiang,ZHOU Guo-mo,XU Xiao-jun ,DONG De-jin,L Yu-long(1.Zhejiang Provincial Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration,Zhejiang A ＆ F University,Lin＇an 311300,Zhejiang,China;2.School of Environmental Sciences and Resources,Zhejiang A ＆ F University,Lin＇an 311300,Zhejiang,China;3.Forest Enterprise of Anji County,Anji 313300,Zhejiang,China) |
| |
| Abstract: | Maximum likelihood classification method was used to extract moso bamboo(Phyllostachys pubescens) forest from multitemporal Landsat-5 Thematic Mapper(TM) images.The dynamic change of bamboo forest areas in Anji County,Zhejiang Province in the past 30 years was conducted.Meanwhile,total aboveground carbon stock of bamboo forest was estimated.The results showed that(1) overall classification accuracy for each TM image was over 85%,and Kappa coefficient for moso bamboo forest ranged from 0.80 to 0.95.The relat... |
| |
| Keywords: | forest ecology moso bamboo forest remote sensing dynamic monitoring carbon stock |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
