[1]余 超,宋立奕,李明阳 *,等.河南西峡县森林地上生物量时空动态分析[J].南京林业大学学报(自然科学版),2017,41(06):093-101.[doi:10.3969/j.issn.1000-2006.201605014]
 YU Chao,SONG Liyi,LI Mingyang*,et al.Spatio-temporal dynamics of forest aboveground biomass in Xixia County, Henan Province, China[J].Journal of Nanjing Forestry University(Natural Science Edition),2017,41(06):093-101.[doi:10.3969/j.issn.1000-2006.201605014]
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河南西峡县森林地上生物量时空动态分析
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《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

卷:
41
期数:
2017年06期
页码:
093-101
栏目:
研究论文
出版日期:
2017-11-30

文章信息/Info

Title:
Spatio-temporal dynamics of forest aboveground biomass in Xixia County, Henan Province, China
文章编号:
1000-2006(2017)06-0093-09
作者:
余 超1宋立奕2李明阳 1*Omidreza Shobairi SEYED 1张向阳3
1. 南京林业大学林学院, 江苏 南京 210037; 2.贵州省林业调查规划院,贵州 贵阳 550003; 3. 河南省林业调查规划院,河南 郑州 450045
Author(s):
YU Chao1 SONG Liyi2 LI Mingyang1* Omidreza Shobairi SEYED1 ZHANG Xiangyang3
1. College of Forestry, Nanjing Forestry University, Nanjing 210037, China; 2. Forest Inventory and Planning Institute of Guizhou Province, Guiyang 550003, China; 3. Forest Inventory and Planning Institute of Henan Province, Zhengzhou 450045, China
关键词:
森林生物量 时空动态 连清数据 西峡县
Keywords:
Keywords:forest aboveground biomass spatio-temporal dynamics continuous forest inventory data Xixia County
分类号:
S757
DOI:
10.3969/j.issn.1000-2006.201605014
文献标志码:
A
摘要:
【目的】森林生物量大小与森林生产力水平的高低密切相关,是反映森林生态系统功能的基本数据。【方法】以河南省西峡县为研究区域,以研究区1993—2013年5期森林资源连续清查固定样地数据,1993年、1998年、2003年、2008年、2013年Landsat TM/ETM+/OLI遥感图像为主要信息源,通过建立4种遥感估测模型,对研究区域1993—2013年的森林地上部分生物量进行时空动态分析。【结果】①随机森林遥感估测模型综合性能最高,k最邻近算法与装袋算法居中,多元线性回归最低; ②海拔、坡度、亮度指数、湿度指数、垂直植被指数和有效叶面积指数这6个因子是影响研究区域森林地上部分生物量大小的重要环境因子; ③1993—2013年期间,研究区域单位面积森林生物量经历了先从1993年34.68 Mg/hm2下降到2003年32.59 Mg/hm2、然后上升到2013年44.65 Mg/hm2的复杂变化历程; ④1993—2013年期间,表征空间自相关程度的全局Moran'I 指数不断降低,表明研究区域森林地上部分生物量的空间聚集性呈持续下降趋势。【结论】乱砍滥伐、毁林开荒行为,退耕还林、天然林保护政策,以及生态廊道、村镇绿化工程建设,是研究区森林地上生物量发生时空变化的主要驱动因素。
Abstract:
【Objective】Forest biomass is closely related to forest production, and it is also the basic data reflecting forest ecological system function. 【Method】In this study, Xixia County in Henan Province, China, was selected as the study area, while Landsat TM/ETM+/OLI imagery in 1993, 1998, 2003, 2008, 2013 and fixed plot data from continuous forest inventory in the same five years were collected as the main information to build four remote sensing based models to predict the spatio-temporal dynamics of forest aboveground biomass during 1993-2013. 【Result】① The prediction accuracy of random forest is the highest, k-NN and bagging remain medium, while the accuracy of MLR is the lowest; ② Elevation, slope, brightness, wetness, vertical vegetation index and effective leaf area index are the key factors affecting forest aboveground biomass in the study area; ③ During 1993-2013, the unit forest biomass in the study area first decreased from 34.68 Mg/hm2 in 1993 to 32.59 Mg/hm2 in 2003, then increased to 44.65 Mg/hm2 in 2013; ④ The global Moran' I index, which characterizes the degree of spatial autocorrelation, decreased continuously from 1993 to 2013, indicating that the spatial distribution pattern of forest aboveground biomass had changed from high aggregation to fragmentation. 【Conclusion】 Forest clearance for farmland, deforestation, returning farmland to forest, natural forest protection policy, as well as construction of ecological corridor and village greening project, are the main driving factors of spatio-temporal dynamics of forest aboveground biomass in the study area.

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备注/Memo

备注/Memo:
基金项目:国家自然科学基金项目(31770679) 第一作者:余超(313749706@qq.com)。*通信作者:李明阳(lmy196727@126.com),教授。
更新日期/Last Update: 1900-01-01