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林业科学 ›› 2014, Vol. 50 ›› Issue (1): 88-96.doi: 10.11707/j.1001-7488.20140114

• 论文与研究报告 • 上一篇    下一篇

基于CBERS数据的亚热带森林地上碳储量估算

王长委1, 胡月明1, 沈德才2, 黄胜利3, 朱剑云2, 王璐1   

  1. 1. 华南农业大学信息学院 广州 510642;
    2. 东莞市林业科学研究所 东莞 523106;
    3. 美国地质勘探局地球资源观测和科学数据中心 苏福尔斯 57198
  • 收稿日期:2013-02-04 修回日期:2013-06-13 出版日期:2014-01-25 发布日期:2014-01-25
  • 基金资助:

    “十一五”科技支撑项目(2009BAD2B06);林业公益性行业专项(201104006);林业公益性行业专项重大项目(200804001);国家自然科学基金项目(41001310)。

Assessing the Capability of CBERS-02 B CCD for Estimating Subtropical Forest above Ground Carbon Storage

Wang Changwei1, Hu Yueming1, Shen Decai2, Huang Shengli3, Zhu Jianyun2, Wang Lu1   

  1. 1. College of Information, South China Agricultural University Guangzhou 510642;
    2. Dongguan Research Institute of Forestry Dongguan 523106;
    3. ASRC Federal US Geological Survey Earth Resources Observation and Science Center Sioux Falls, USA, 57198
  • Received:2013-02-04 Revised:2013-06-13 Online:2014-01-25 Published:2014-01-25
  • Contact: 王璐

摘要:

为探讨CBERS-02B星CCD数据在亚热带森林地上碳储量估算方面的能力,以东莞市范围内的亚热带森林为研究对象,对比分析CBERS-02B星CCD数据的波段信息、植被指数、纹理信息和森林地上碳储量之间的相关性,发现纹理信息的估算能力最强;在此基础上,将波段信息、植被指数和纹理信息结合在一起,通过逐步回归策略构建CBERS-02B星CCD数据的亚热带森林地上碳储量估算模型,其调整系数R2达到0.53,显著度水平P远远小于0.05。这表明:尽管CBERS-02B星CCD数据的近红外波段存在一定的漂移,但是将CBERS-02B星CCD数据的波段信息、植被指数、纹理信息集成构建森林地上碳储量估算模型,在一定程度上可以克服波段信息、植被指数、纹理信息各自单独估算森林地上碳储量的缺点,增强各自间的互补性,提高CBERS-02B星CCD数据估算森林地上碳储量的能力;而且基于CBERS-02B星CCD数据估算的东莞市碳储量空间分布和东莞市实际碳储量分布情况基本一致,说明CBERS-02B星CCD数据用于亚热带的森林地上碳储量估算是可行的。

关键词: 中巴资源卫星, 地上碳储量, 亚热带森林, 估算

Abstract:

Many remote sensing data have been applied to estimate forest above ground carbon storage(AGCS), but the estimation accuracy is varying. The capability of remotely sensed CBERS-02B CCD data for tropical and subtropical AGCS estimation is unknown. In this paper, with Dongguan forest region as a case study area, the CBERS-02B CCD data, along with the field survey data, were used to examine the relationship between forest biomass and band reflectance, vegetation indices, and image texture. It was found image texture performed the best in biomass estimation. When the band reflectance, vegetation indices, and image texture were combined in stepwise multiple regressions for biomass estimation, the adjustment coefficient R2 was 0.53, root mean square error was 15.66, and P-level was less than 0.05, indicating the significance of the model. The results also showed that the shift of near-infrared band of the CBERS-02B CCD had negative effect on biomass estimation, but the integration of band reflectance, vegetation indices, and image texture can improve the capability of CBERS-02B CCD data for AGCS estimation, because the integration can reduce limitation and improve the complementarity. Moreover, the spatial distribution of AGCS mapping by CBERS-02B CCD data is similar with the actual distribution. We concluded that CBERS data are promising for estimating subtropical forest biomass.

Key words: CBERS, above ground carbon storage (AGCS), subtropical forest, estimation

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