中国森林植被生物量空间网格化估计

doi:10.31497/zrzyxb.20170802

自然资源学报 ›› 2018, Vol. 33 ›› Issue (10): 1725-1741.doi: 10.31497/zrzyxb.20170802

中国森林植被生物量空间网格化估计

徐伟义^1,2,3, 金晓斌^1,3,4,*, 杨绪红^1,3, 王志强², 刘晶^1,3, 王丹⁵, 单薇¹, 周寅康^1,3,4

1. 南京大学地理与海洋科学学院,南京 210023;
2. 湖南科技大学资源环境与安全工程学院,湖南湘潭 411100;
3. 国土资源部海岸带开发与保护重点实验室,南京 210023;
4. 南京大学自然资源研究中心,南京 210023;
5. 江苏师范大学地理测绘与城乡规划学院,江苏徐州 221116

收稿日期:2017-08-07 修回日期:2017-12-25 出版日期:2018-10-20 发布日期:2018-10-20
通讯作者: 金晓斌（1974- ）,男（汉族）,甘肃兰州人,博士,教授,博士生导师,研究方向为土地资源管理。E-mail: jinxb@nju.edu.cn
作者简介:徐伟义（1992- ）,男（汉族）,安徽黄山人,博士研究生,研究方向为土地利用变化过程与效应。E-mail:xuweiyilj@126.com
基金资助:
国家自然科学基金资助项目（41671082）

The Estimation of Forest Vegetation Biomass in China in Spatial Grid

XU Wei-yi^1,2,3, JIN Xiao-bin^1,3,4, YANG Xu-hong^1,3, WANG Zhi-qiang², LIU Jing^1,3, WANG Dan⁵, SHAN Wei¹, ZHOU Yin-kang^1,3,4

1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China;
2. School of Resource Environment and Safety Engineering, Hunan University of Science and Technology, Xiangtan 411100, China;
3. The Key Laboratory of the Coastal Zone Exploitation and Protection, Ministry of Land and Resources, Nanjing 210023, China;
4. Natural Resources Research Center, Nanjing University, Nanjing 210023, China;
5. School of Geography Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China

Received:2017-08-07 Revised:2017-12-25 Online:2018-10-20 Published:2018-10-20
Supported by:
National Natural Science Foundation of China, No. 41671082.

摘要/Abstract

摘要： 森林是陆地生态系统的重要碳库之一,在全球碳循环中发挥着巨大作用。森林生物量是核算森林碳储量的主要因子,其数量及空间分布是评估森林生态系统碳汇潜力的重要参数。论文以中国第8次森林资源清查资料为基础,以影响森林生物量空间分布的气候（气温、降水）、地形（高程、坡度）和植被因子（NDVI）为辅助,利用降尺度方法估算了1 km×1 km格网分辨率下的中国森林生物量,并从不同空间尺度对研究结果进行了验证。结果表明：1）中国森林生物量总量约为13.56 Pg,平均生物量密度为65.3 t/hm²,各省森林生物量总量差异较大,总量较高省份主要集中于西南和东北内蒙古地区,其中西南地区（西藏、四川、云南）最高,为4.5 Pg,占总量的33%;东北内蒙古地区（黑龙江、吉林、辽宁、内蒙古）次之,为3.58 Pg,占总量的26%;2）在省级尺度构建的森林生物量与相关影响因子的回归关系可用于栅格尺度下森林生物量的降尺度估算,多尺度验证分析表明网格化估算结果基本合理;3）中国森林生物量空间格局区域分异规律明显,大致以东北至西南为界,与水热条件空间分布格局基本一致,生物量高值区主要集中于东北地区（大小兴安岭、长白山地区）、西南地区（横断山脉）、新疆山区（阿尔泰山、天山、昆仑山）、秦岭和东南武夷山等地区。

关键词: 降尺度, 空间网格化, 森林, 生物量, 中国

Abstract: Forest is a major carbon pool for terrestrial ecosystems, and it plays a very important role in global carbon cycle. Forest biomass is a key factor in estimating forest carbon storage, and its magnitude and spatial distribution are important parameters for assessing carbon sequestration potential of forest ecosystems. Scholars in the field have used different methods to study many aspects of forest biomass in China. Due to the spatial heterogeneity of forest biomass and differences in research methods and data, different scholars got different results. Three traditional methods have been used in biomass research: on-the-spot sampling, model method and remote sensing. Currently, statistical downscaling technique is a statistical method widely used in the study of ecosystem carbon cycle which transforms large-scale, low-resolution information into regional-scale, high-resolution information. This paper is based on the eighth China forest inventory data set, along with the impact factors of forest biomass, including the vegetation factor (NDVI), climatic factors (temperature, precipitation), and terrain factors (elevation, slope). We quantitatively estimate the forest biomass (1 km resolution) using the spatial downscaling technique, and the results of the study are verified on multiple scales. The results of this study are as follows: 1) The total stock of forest biomass is 13.56 Pg in China, with an average biomass of 65.3 t/hm². The total amount of forest biomass is quite different in different provinces. The provinces with higher volume are concentrated in the southwest and the northeast, and the maximum biomass is 4.5 Pg in the southwest, accounting for 33% of the total biomass in China. The forest biomass is 3.58 Pg in the northeast, accounting for 26% of the total biomass in China. 2) The regression relationship between forest biomass and related factors at the provincial scale can be used for the estimation of forest biomass at the grid scale by downscaling technique, and the multi-scale verification analysis shows that the estimation results are reasonable. 3) The spatial pattern of forest biomass is consistent with the spatial distribution of hydrothermal condition. Taking the line from the northeast to the southwest as the boundary, China’s biomass is primarily in the Da Xing’an Mountains, Xiao Xing’an Mountains and Changbai Mountain in the Northeast China, the Hengduan Mountains in the Southwest China, the Qinling Mountains, and the Wuyi Mountains in the Southeast China.

Key words: biomass, China, downscaling, forest, spatial grid

中图分类号:

S718.5

徐伟义, 金晓斌, 杨绪红, 王志强, 刘晶, 王丹, 单薇, 周寅康. 中国森林植被生物量空间网格化估计[J]. 自然资源学报, 2018, 33(10): 1725-1741.

XU Wei-yi, JIN Xiao-bin, YANG Xu-hong, WANG Zhi-qiang, LIU Jing, WANG Dan, SHAN Wei, ZHOU Yin-kang. The Estimation of Forest Vegetation Biomass in China in Spatial Grid[J]. JOURNAL OF NATURAL RESOURCES, 2018, 33(10): 1725-1741.

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中国森林植被生物量空间网格化估计

The Estimation of Forest Vegetation Biomass in China in Spatial Grid

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