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干旱区地理 ›› 2012, Vol. 35 ›› Issue (04): 599-606.

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基于地理信息技术油松(Pinus tabuliformis)根长密度估算及空间分布特征分析

荐圣淇1,赵传燕1,方书敏1,余凯2,彭守璋1,柳逸月1,李彦甫2   

  1. 1兰州大学干旱与草地生态教育部重点实验室,甘肃兰州730000;2兰州大学西部环境教育部重点实验室,甘肃兰州730000
  • 收稿日期:2011-12-17 修回日期:2012-02-13 出版日期:2012-07-25
  • 通讯作者: 荐圣淇
  • 作者简介:荐圣淇(1987-),男,硕士研究生,主要从事生态水文与GIS方面的研究
  • 基金资助:

    国家自然科学基金(91025015和30770387 );国家环境保护公益性资助项目(NEPCP 200809098)资助

Estimating the root length density of Pinus tabuliformis based on image processing technology and analyzing its spatial distribution

JIAN Shengqi1,ZHAO Chuanyan1,FANG Shumin1,YU Kai2,PENG Shouzhang1,LIU Yiyue1,LI Yanfu2   

  1. 1Key Laboratory of Arid and Grassland Ecology with the Ministry of Education, Lanzhou University, Lanzhou 730000, Gansu,China; 2National Laboratory of Western China’s Environmental System, Lanzhou University, Lanzhou 730000, Gansu,China.
  • Received:2011-12-17 Revised:2012-02-13 Online:2012-07-25
  • Contact: JIAN Shengqi

摘要: 定量研究植物根系的生长发育及时空分布特征是构建根系吸水模型、计算根系吸水量的基础。选择陇中黄土高原定西安家沟流域为研究区,对研究区内的油松(Pinus tabuliformis)吸水根系空间分布特征进行研究。利用剖面法获取不同空间点上的吸水根系,基于地理信息系统技术估算油松吸水根系的根长密度。结果表明:在水平方向上,油松根长密度呈二次曲线分布,吸水根系主要集中在0~400 cm范围内;在垂直方向上,油松吸水根系呈对数分布,吸水根系主要集中在0~100 cm范围内。并构建了油松吸水根系的二维空间分布方程。

关键词: 油松, 地理信息系统技术, 根长密度, 安家沟

Abstract: The study of the spatial distribution pattern of plant fine roots is the basis to develop the models of plant roots. At present, the main method includes direct measurement and proper gird measurement. These methods have a lot of limitation, due to human factors, having much error and low efficiency. This paper aims to use remote sensing image processing technology for estimating the root length density of Pinus tabuliformis, with convenient, quick, batch process, and high precision. The Anjiagou catchment in the Longzhong Loess Plateau was selected. The spatial distribution pattern of Pinus tabuliformis fine roots was studied. Fine root samples were obtained in soil profiles. Picking up the fine roots from the soil samples, cleaning up and dry them. Scanning the roots from each sample, and then importing the images into ArcGIS. First, we should observe the grid values by identification, the values of the roots are 120. Then setting the roots 1, others 0 by raster calculator. When measuring the length by ArcGIS, we should use vector data, so needing to change the grid data to vector data. After that, the jagged line will appear, leading to the result bigger than real length. In order to improve the accuracy, we should smooth the vector data. At last, building model by the tools of the above in the ArcGIS, and carrying on batch process to each sample. We can get the result fast and accurately. The root length density of Pinus tabuliformis fine roots was estimated based on remote sensing image processing technology. Absolute error is from 2.2 mm to 4.6 mm, accuracy is 98%. So this shows that calculating root length by geographic information system technology is with high accuracy. The density distribution of fine roots of Pinus tabulaeformis was analyzed and simulated. Both 1D function (including in vertical and horizontal directions) and 2D function of the root length density were established. In vertical direction, the root length density of Pinus tabulaeformis mainly distribute in the 0-100 cm soil layers with logarithm distribution, which makes up 91.9% of whole roots; In the horizontal direction, the root length density augments with the increase of distance to tree from 0 to 240 cm, and decreases with increase of distance to tree from 240 to 500 cm. The distribution of fine roots is mostly crowded in the soil layers from 150 to 300 cm, making up 46.5% of the total roots. Most of the functions of root length density were simulated with function of eexponent, and R2 are 0.94 and 0.804, respectively. The result is helpful to theoretical research in SPAC (Soil-Plant-Atmosphere Continuum) system of Pinus tabulaeformis, at the same time this method can be applied in the extensive research.

Key words: Pinus tabuliformis, image processing technology, roots length density, Anjiagou

中图分类号: 

  • Q944.54