在林业碳汇量估算中遥感方法的应用分析
Application Analysis of Remote Sensing Method in Forestry Carbon Sink Estimation
DOI: 10.12677/WJF.2022.113017, PDF,   
作者: 胡 蝶, 王英伟：东北林业大学林学院，黑龙江 哈尔滨；孙红阳：黑龙江森工集团生态建设部，黑龙江 哈尔滨；朱凌燕：吉林省林草局，吉林 长春
关键词: 遥感；林业碳汇；碳储量；植被覆盖度；光能利用率；生物量方程；Remote Sensing； Forestry Carbon Sink； Carbon Storage； Vegetation Coverage； Light Utilization Rate； Biomass Equation
摘要: 研究针对没有样地数据的林业碳汇量估算，将遥感手段引入其中，作为现行林业碳汇量估算方式的补充。方法选择参考森林碳汇量估算方法，结合林业碳汇量特征，加以改进使之更符合用林业碳汇量估算。以三种方法对研究区碳储量进行估算，生物量方程法的估算结果最小值为1.97 MgC到最大值7.91 MgC；光能利用率法的估算结果最小值为0.57 MgC到最大值9.75 MgC；NDVI反演法的估算结果最小值为1.36 MgC到最大值8.68 MgC。光能利用率法估算的碳储量空间分布为由北向南、由西向东逐渐递增，NDVI反演法估算的碳储量空间分布为由南向北、由东向西逐渐递增。将生物量方程法的估算结果作为真实数据，分别用光能利用率法和NDVI反演法与真实数据进行结果拟合，NDVI反演法的最终拟合效果最好，并且碳储量空间分布也更符合实际。
Abstract: In this study, for the estimation of forest carbon sink without sample plot data, remote sensing is introduced into the estimation of forest carbon sink as a supplement to the current estimation method of forest carbon sink. Methods The reference forest carbon sink estimation method was selected, combined with the characteristics of forest carbon sink, and improved to make it more in line with the estimation of forest carbon sink. Three methods were used to estimate the carbon storage in the study area. The minimum value of biomass equation method was 1.97 MgC to the maximum value of 7.91 MgC. The minimum value of the light energy utilization method is 0.57 MgC to the maximum value of 9.75 MgC; the minimum value of NDVI inversion method is 1.36 MgC to the maximum value of 8.68 MgC. The spatial distribution of carbon storage estimated by the light energy utilization method is gradually increasing from north to south and from west to east. The spatial distribution of carbon storage estimated by NDVI inversion method is gradually increasing from south to north and from east to west. The estimation results of biomass equation method were used as real data, and the results were fitted by light energy utilization method and NDVI inversion method with real data. The final fitting effect of NDVI inversion method was the best, and the spatial distribution of carbon storage was more realistic. 
文章引用：胡蝶, 王英伟, 孙红阳, 朱凌燕. 在林业碳汇量估算中遥感方法的应用分析[J]. 林业世界, 2022, 11(3): 133-143. https://doi.org/10.12677/WJF.2022.113017

参考文献

[1] 吴颖. 林业碳汇潜力与碳汇计量监测体系建设路径分析[J]. 温带林业研究, 2021, 4(4): 54-56.
[2] 森林经营碳汇项目方法学(V01) [Z].
[3] 续珊珊. 森林碳储量估算方法综述[J]. 林业调查规划, 2014, 39(6): 28-33.
[4] 尹惠妍, 张志伟, 李海奎. 中国主要乔木树种生物量方程[J]. 中南林业科技大学学报, 2019, 39(5): 63-69. [Google Scholar] [CrossRef] 
[5] 代海军, 何怀江, 赵秀海, 张春雨, 汪金松, 杨松. 阔叶红松林两种主要树种的生物量分配格局及异速生长模型[J]. 应用与环境生物学报, 2013, 19(4): 718-722.
[6] 代海军. 吉林蛟河阔叶红松林主要树种异速生长模型[D]: [硕士学位论文]. 北京: 北京林业大学, 2013.
[7] 董利虎. 黑龙江省主要树种相容性生物量模型研究[D]: [硕士学位论文]. 哈尔滨: 东北林业大学, 2012.
[8] 陆龙龙, 袁靓, 范春楠, 郑金萍, 郭忠玲. 长白山林区主要树种含碳率及其差异分析[J]. 北华大学学报(自然科学版), 2018, 19(2): 164-169.
[9] 于颖, 范文义, 李明泽. 东北林区不同尺度森林的含碳率[J]. 应用生态学报, 2012, 23(2): 341-346. [Google Scholar] [CrossRef] 
[10] 碳汇造林项目方法学(V01) [Z].
[11] Patil, V., Singh, A., Naik, N. and Unnikrishnan, S. (2015) Estimation of Mangrove Carbon Stocks by Applying Remote Sensing and GIS Techniques. Wetlands, 35, 695-707. [Google Scholar] [CrossRef] 
[12] Tucker, C.J. (1979) Red and Photographic Infrared Linear Combinations for Monitoring Vegetation. Remote Sensing of Environment, 8, 127-150. [Google Scholar] [CrossRef] 
[13] 朱安然, 孙睿, 王梦佳. 植被光能利用率遥感估算[J]. 遥感学报, 2021, 25(6): 1227-1243.
[14] Zhao, M. and Running, S.W. (2015) User’s Guide-Daily GPP and Annual NPP (MOD17A2/A3) Products-NASA Earth Observing System MODIS Land Algorithm. NASA EOSDIS Land Processes DAAC.
[15] Potter, C.S., et al. (1993) Terrestrial Ecosystem Production: A Process Model Based on Global Satellite and Surface Data. Global Biogeochemical Cycles, 7, 811-841. [Google Scholar] [CrossRef] 
[16] Field, C.B., Randerson, J.T. and Malmström, C.M. (1995) Global Net Primary Production: Combining Ecology and Remote Sensing. Remote Sensing of Environment, 51, 74-88. [Google Scholar] [CrossRef] 
[17] Field, C.B., et al. (1998) Primary Production of the Bio-sphere: Integrating Terrestrial and Oceanic Components. Science, 281, 237-240. [Google Scholar] [CrossRef] [PubMed]
[18] Hamdan, O., Khairunnisa, M.R., Ammar, A.A., Hasmadi, I.M. and Khali Aziz, H. (2013) Mangrove Carbon Stock Assessment by Optical Satellite Imagery. Journal of Tropical Forest Science, 25, 554-565.
[19] 耿庆玲, 陈晓青, 赫晓慧, 田智慧. 中国不同植被类型NDVI对气候变化和人类活动的响应[J/OL]. 生态学报, 1-12. https://kns-cnki-net.webvpn.nefu.edu.cn/kcms/detail/11.2031.Q.20220106.0939.040.html, 2022-01-12.
[20] 张朔川, 汤军, 高贤君. 秦皇岛市2001-2020年植被覆盖动态变化及预测[J]. 科学技术与工程, 2021, 21(31): 13254-13261.

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