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长白山阔叶红松林不同演替阶段冠层光谱特征及其与气温的关系

王瑶瑶 周光 刘琪璟 周阳

王瑶瑶, 周光, 刘琪璟, 周阳. 长白山阔叶红松林不同演替阶段冠层光谱特征及其与气温的关系[J]. 北京林业大学学报, 2021, 43(7): 40-53. doi: 10.12171/j.1000-1522.20200373
引用本文: 王瑶瑶, 周光, 刘琪璟, 周阳. 长白山阔叶红松林不同演替阶段冠层光谱特征及其与气温的关系[J]. 北京林业大学学报, 2021, 43(7): 40-53. doi: 10.12171/j.1000-1522.20200373
Wang Yaoyao, Zhou Guang, Liu Qijing, Zhou Yang. Canopy spectral characteristics of broadleaved Korean pine forest in different successional stages and its relation with temperature in Changbai Mountain of northeastern China[J]. Journal of Beijing Forestry University, 2021, 43(7): 40-53. doi: 10.12171/j.1000-1522.20200373
Citation: Wang Yaoyao, Zhou Guang, Liu Qijing, Zhou Yang. Canopy spectral characteristics of broadleaved Korean pine forest in different successional stages and its relation with temperature in Changbai Mountain of northeastern China[J]. Journal of Beijing Forestry University, 2021, 43(7): 40-53. doi: 10.12171/j.1000-1522.20200373

长白山阔叶红松林不同演替阶段冠层光谱特征及其与气温的关系

doi: 10.12171/j.1000-1522.20200373
基金项目: 国家自然科学基金项目(31670436)
详细信息
    作者简介:

    王瑶瑶。主要研究方向:林业遥感与信息技术。Email:308714182@qq.com 地址:100083 北京市海淀区清华东路35号北京林业大学林学院

    责任作者:

    刘琪璟,教授。主要研究方向:森林资源调查与监测。Email:liuqijing@bjfu.edu.cn 地址:同上

  • 中图分类号: S791.247

Canopy spectral characteristics of broadleaved Korean pine forest in different successional stages and its relation with temperature in Changbai Mountain of northeastern China

  • 摘要:   目的  通过遥感数据分析长白山阔叶红松林不同演替阶段冠层光谱变化特征,为揭示长白山群落内部种间变化以及植被生产力对气候因子的响应机制提供理论依据。  方法  通过Google Earth Engine平台提取1984—2019年长白山原始阔叶红松林与次生白桦林Landsat和Sentinel多年冠层光谱数据并计算植被绿度参数,分析二者冠层光谱特征季节变化、植被绿度的季节与年际变化,计算植被年际绿度变化与同期月均温的Pearson相关系数。  结果  (1)原始林与次生林冠层可见光反射率在非生长季较高,生长季下降,而近红外光变化趋势则与此相反。在生长旺盛季节(5—10月底)原始林与次生林可见光波段冠层反射率相近,近红外波段差异明显,次生林冠层反射率更高。二者都具有明显的“红谷”、 “绿峰”、 “蓝谷”和“红边”现象,原始林冠层光谱反射率年变化幅度小于次生林。(2)原始林与次生林的绿度表现为相同的变化趋势,即春季展叶期间增长、秋季落叶期衰减。非生长季,原始林植被指数变化较为稳定且大于次生林,次生林林下透光度高。生长季,次生林增强植被指数(EVI)和哨兵二号红边位置(S2REP)均大于原始林,植被冠层生理活动更为旺盛,不同的卫星影像数据表现一致,且次生林的EVI峰值比原始林出现得略早。(3)1985—2019年的35年期间,长白山气温呈上升趋势,植被绿度也随之变化,即:二者EVI在增加,且夏季(生长季)增长幅度大于其他季节,春、秋季的年际差异较大。(4)与原始林相比,次生林EVI年际变化受春季气温影响较大,在生长季初期,二者的EVI与气温呈显著正相关;在整个生长季期间,当气温增加达到一定阈值后,EVI增长显著。  结论  长时间的连续冠层光谱变化监测与分析,可有效反映原始林与次生林植被物候变化差异。气温上升可能是引起长白山阔叶红松林绿度变化的重要因素之一。

     

  • 图  1  植被遥感光谱信息提取位点

    Figure  1.  Sampling points for extracting spectral information from satellite images

    图  2  长白山两种森林植被冠层光谱8 d合成的反射率季节进程(2013—2019年Landsat 8数据)

    Figure  2.  Eight-day-composite seasonal pattern of canopy spectral reflectance of two forest vegetation types in Changbai Mountain (Landsat 8 data in 2013−2019)

    图  3  高分辨率影像提取的林冠层光谱反射率季节变化(2019年)

    Figure  3.  Seasonal pattern of forest canopy spectral reflectance from high-resolution images (2019)

    图  4  2019年长白山两种森林植被的绿度(a、b)与红边位置季节变化(c)

    Figure  4.  Seasonal changes of greenness (a, b) and red-edge position of two vegetation types in Changbai Mountain (c)

    图  5  长白山两种森林植被归一化植被指数逻辑斯蒂曲线

    Figure  5.  Logistic curves of NDVI of two vegetation types in Changbai Mountain

    图  6  长白山两种森林植被EVI季节变化(1985—2019年)

    Figure  6.  Seasonal pattern of EVI of two vegetation types in Changbai Mountain (1985−2019)

    图  7  长白山两种森林植被生长季EVI(a)和气温(b)的关系(1985—2018年)

    Figure  7.  Relationship between EVI (a) and temperature (b) of two forest vegetation types during growing season in Changbai Mountain (1985−2018)

    图  8  长白山两种森林植被EVI多年月均值与标准差(1985—2018年)

    Figure  8.  Multi-year monthly mean and standard deviation of EVI of two forest vegetation types during growing season in Changbai Mountain (1985−2018)

    表  1  长白山两种森林植被月均EVI年际变化与同期气温的相关系数(1985—2018年)

    Table  1.   Correlation coefficients between month-specific average EVI and temperature of two vegetation types in Changbai Mountain (1985−2018)

    月份 Month原始林 Primary forest次生林 Secondary forest
    平均气温
    Mean temperature
    最高气温
    Maximum temperature
    最低气温
    Minimum temperature
    平均气温
    Mean temperature
    最高气温
    Maximum temperature
    最低气温
    Minimum temperature
    1月 January 0.007 1 0.163 9 −0.079 1 −0.118 5 −0.022 1 −0.237 3
    2月 February −0.079 5 −0.009 5 −0.094 9 −0.126 5 0.161 5 −0.006 2
    3月 March −0.099 8 0.097 7 0.070 8 −0.456 4** −0.445 1** −0.158 0
    4月 April −0.229 8 −0.158 2 −0.260 6 −0.367 1* −0.266 7 −0.283 1
    5月 May 0.524 4** 0.476 4** 0.171 6 0.548 2** 0.399 2* 0.114 4
    6月 June 0.375 3* 0.378 6* 0.102 0 0.230 6 0.378 5* 0.001 6
    7月 July 0.218 2 0.314 5 0.057 2 0.091 6 0.200 6 0.041 0
    8月 August −0.035 4 0.259 0 −0.383 9* −0.030 0 0.176 5 −0.368 3*
    9月 September 0.053 0 0.059 5 0.007 0 0.017 2 −0.023 6 −0.158 9
    10月 October 0.266 9 0.377 2* −0.024 2 0.232 7 0.241 1 0.014 3
    11月 November −0.116 8 −0.176 8 −0.088 4 0.1375 0.107 8 0.108 7
    12月 December 0.087 4 0.005 2 −0.209 7 −0.073 0 −0.390 9* −0.029 8
    注:*表示在P < 0.05水平上显著相关,**表示在P < 0.01水平上显著相关。Notes: * means a significant correlation at the P < 0.05 level, ** means a significant correlation at the P < 0.01 level.
    下载: 导出CSV
  • [1] 汲常萍. 长白山阔叶红松林和杨桦林不同土壤组分碳氮相关指标及差异研究[D]. 哈尔滨: 东北林业大学, 2014.

    Ji C P. Comparisons of soil carbon and nitrogen-related parameters in 5 different soil fractions between broad-leaved Korean Pine mixed forests and secondary poplar-birch forests in Changbai Mts[D]. Harbin: Northeast Forestry University, 2014.
    [2] 徐振邦, 代力民, 陈吉泉, 等. 长白山红松阔叶混交林森林天然更新条件的研究[J]. 生态学报, 2001, 21(9):1413−1420. doi: 10.3321/j.issn:1000-0933.2001.09.003

    Xu Z B, Dai L M, Chen J Q, et al. Natural regeneration condition in Pinus koraiensis broad-leaved mixed forest[J]. Acta Ecologica Sinica, 2001, 21(9): 1413−1420. doi: 10.3321/j.issn:1000-0933.2001.09.003
    [3] 王树力, 武敬辉, 史永纯. 红松种群天然更新及幼年生长与林分结构关系的研究[J]. 吉林林学院学报, 1998, 14(8):6−10.

    Wang S L, Wu J H, Shi Y C. On the relationship between natural regeneration and early growth of Korean pine and stand structure[J]. Journal of Jilin Forestry University, 1998, 14(8): 6−10.
    [4] 王连喜, 陈怀亮, 李琪, 等. 植物物候与气候研究进展[J]. 生态学报, 2010, 20(2):447−454.

    Wang L X, Chen H L, Li Q, et al. Research advances in plant phenology and climate[J]. Acta Ecologica Sinica, 2010, 20(2): 447−454.
    [5] Zhou G, Liu Q J, Xu Z Z, et al. How can the shade intolerant Korean pine survive under dense deciduous canopy?[J]. Forest Ecology and Management, 2020, 457: 117735. doi: 10.1016/j.foreco.2019.117735
    [6] 许丹, 伍维模, 王家强, 等. 塔里木河流域上游天然胡杨叶片叶绿素与可见光−近红外光谱反射率的相关性研究[J]. 塔里木大学学报, 2012, 24(4):53−59. doi: 10.3969/j.issn.1009-0568.2012.04.0011

    Xu D, Wu W M, Wang J Q, et al. Study on the correlation between leaf chlorophyll content of Populus euphratica and the hyperspectral remote sensing data in upstream of Tarim River[J]. Journal of Tarim University, 2012, 24(4): 53−59. doi: 10.3969/j.issn.1009-0568.2012.04.0011
    [7] 赵恒谦, 张文博, 朱孝鑫, 等. 煤炭矿区植被冠层光谱土地复垦敏感性分析[J]. 光谱学与光谱分析, 2019, 39(6):1858−1863.

    Zhao H Q, Zhang W B, Zhu X X, et al. Analysis on susceptibility of vegetation canopy spectra in coal mining area to land reclamation[J]. Spectroscopy and Spectral Analysis, 2019, 39(6): 1858−1863.
    [8] 罗娜娜, 赵文吉, 晏星. 在滞尘影响下的植被叶片光谱变化特征研究[J]. 光谱学与光谱分析, 2013, 33(10):2715−2720. doi: 10.3964/j.issn.1000-0593(2013)10-2715-06

    Luo N N, Zhao W J, Yan X. Impact of dust-fall on spectral features of plant leaves[J]. Spectroscopy and Spectral Analysis, 2013, 33(10): 2715−2720. doi: 10.3964/j.issn.1000-0593(2013)10-2715-06
    [9] 张雪红, 田庆久, 沈润平. 冬小麦冠层光谱的方向性特征分析[J]. 光谱学与光谱分析, 2010, 30(6):1600−1605. doi: 10.3964/j.issn.1000-0593(2010)06-1600-06

    Zhang X H, Tian Q J, Shen R P. Analysis of directional characteristics of winter wheat canopy spectra[J]. Spectroscopy and Spectral Analysis, 2010, 30(6): 1600−1605. doi: 10.3964/j.issn.1000-0593(2010)06-1600-06
    [10] 于泉洲, 周蕾, 王绍强, 等. 基于EO-1 Hyperion的中国典型森林冠层高光谱特征分析[J]. 云南大学学报(自然科学版), 2018, 40(5):947−954.

    Yu Q Z, Zhou L, Wang S Q, et al. An analysis on the spectrum characteristics of Chinese typical forest canopy in growing season based on EO-1 Hyperion images[J]. Journal of Yunnan University (Natural Sciences Edition), 2018, 40(5): 947−954.
    [11] 马东辉, 柯长青. 南京冬季典型植被光谱特征分析[J]. 遥感技术与应用, 2016, 31(4):702−708.

    Ma D H, Ke C Q. Research on spectral characteristics of winter typical vegetation in Nanjing[J]. Remote Sensing Technology and Application, 2016, 31(4): 702−708.
    [12] 项巧巧, 申广荣, 吴裕, 等. 上海典型植被夏季与冬季的光谱特征分析[J]. 上海交通大学学报(农业科学版), 2018, 36(5):14−21.

    Xiang Q Q, Shen G R, Wu Y, et al. Spectral characteristics of typical vegetation in Shanghai in both summer and winter[J]. Journal of Shanghai Jiaotong University (Agricultural Science), 2018, 36(5): 14−21.
    [13] 程乾, 黄敬峰, 王人潮, 等. MODIS植被指数与水稻叶面积指数及叶片叶绿素含量相关性研究[J]. 应用生态学报, 2004, 15(8):1363−1367. doi: 10.3321/j.issn:1001-9332.2004.08.013

    Cheng Q, Huang J F, Wang R C, et al. Correlation analysis of simulated MODIS vegetation indices and rice leaf area index and leaf chlorophyll content[J]. Chinese Journal of Applied Ecology, 2004, 15(8): 1363−1367. doi: 10.3321/j.issn:1001-9332.2004.08.013
    [14] Frampton W J, Dash J, Watmough G, et al. Evaluating the capabilities of Sentinel-2 for quantitative estimation of biophysical variables in vegetation[J]. Journal of Photogrammetry and Remote Sensing, 2013, 82: 83−92.
    [15] 李明泽, 王雪, 高元科, 等. 大兴安岭植被指数年际变化及影响因子分析[J]. 北京林业大学学报, 2015, 37(5):1−10.

    Li M Z, Wang X, Gao Y K, et al. Inter-annual variation in vegetation index and analysis of factors affecting it in Daxing’anling Mountains[J]. Journal of Beijing Forestry University, 2015, 37(5): 1−10.
    [16] 沈文娟, 李明诗. 基于长时间序列Landsat影像的南方人工林干扰与恢复制图分析[J]. 生态学报, 2017, 37(5):1438−1449.

    Shen W J, Li M S. Mapping disturbance and recovery of plantation forests in southern China using yearly Landsat time series observations[J]. Acta Ecologica Sinica, 2017, 37(5): 1438−1449.
    [17] Aulia M R, Liyantono, Setiawan Y, et al. Drought detection of west java’s paddy field using MODIS EVI satellite images (case study: Rancaekek and Rancaekek Wetan)[J]. Procedia Environmental Sciences, 2016, 33: 646−653. doi: 10.1016/j.proenv.2016.03.119
    [18] 李明, 吴正方, 杜海波, 等. 基于遥感方法的长白山地区植被物候期变化趋势研究[J]. 地理科学, 2011, 31(10):1242−1248.

    Li M, Wu Z F, Du H B, et al. Growing-season trends determined from SPOT NDVI in Changbai Mountains, China, 1999−2008[J]. Scientia Geographica Sinica, 2011, 31(10): 1242−1248.
    [19] 于健. 长白山阔叶红松林主要树种径向生长对气候变化响应及温度重建[D]. 北京: 北京林业大学, 2019.

    Yu J. Rosponse of radial growth of main tree species of broad-leaved Korean pine forest to climate change in Changbai Mountain and temperature reconstruction[D]. Beijing: Beijing Forestry University, 2019.
    [20] 郝占庆, 代力民, 贺红士. 气候变暖对长白山主要树种的潜在影响[J]. 应用生态学报, 2001, 12(5):653−658. doi: 10.3321/j.issn:1001-9332.2001.05.003

    Hao Z Q, Dai L M, He H S. Potential response of major tree species to climate warming in Changbai Mountain, Northeast China[J]. Chinese Journal of Applied Ecology, 2001, 12(5): 653−658. doi: 10.3321/j.issn:1001-9332.2001.05.003
    [21] 周玉科, 刘建文. 基于MODIS NDVI和多方法的青藏高原植被物候时空特征分析[J]. 遥感技术与应用, 2018, 33(3):486−498.

    Zhou Y K, Liu J W. Spatio-temporal analysis of vegetation phenology with multiple methods over the Tibetan Plateau based on modis NDVI data[J]. Remote Sensing Technology and Application, 2018, 33(3): 486−498.
    [22] 吴玉莲, 王襄平, 李巧燕, 等. 长白山阔叶红松林净初级生产力对气候变化的响应: 基于BIOME-BGC模型的分析[J]. 北京大学学报(自然科学版), 2014, 50(3):577−586.

    Wu Y L, Wang X P, Li Q Y, et al. Response of broad-leaved Korean pine forest productivity of Mt. Changbai to climate change: an analysis based on BIOME-BGC modeling[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2014, 50(3): 577−586.
    [23] 徐琼瑶. 长白山植被景观变化遥感监测[D]. 北京: 北京林业大学, 2012.

    Xu Q Y. Monitoring vegetation water content with MODIS data in Changbai Mountain Area[D]. Beijing: Beijing Forestry University, 2012.
    [24] 刘敏. 基于MODIS数据的长白山地区植被水分动态变化研究[D]. 吉林: 东北师范大学, 2010.

    Liu M. Monitoring vegetation water content with MODIS data in Changbai Mountain area[D]. Jilin: Northeast Normal University, 2010.
    [25] 于泉洲, 王绍强, 黄昆, 等. 基于Hyperion高光谱数据的温带森林不同冠层结构的光谱特征分析[J]. 光谱学与光谱分析, 2015(7):1980−1985. doi: 10.3964/j.issn.1000-0593(2015)07-1980-06

    Yu Q Z, Wang S Q, Huang K, et al. An analysis of the spectrums between different canopy structures based on Hyperion hyperspectral data in a temperate forest of northeast China[J]. Spectroscopy and Spectral Analysis, 2015(7): 1980−1985. doi: 10.3964/j.issn.1000-0593(2015)07-1980-06
    [26] 姜超. 长白山五种槭属植物光合及光谱特性研究[D]. 北京: 北京林业大学, 2013.

    Jiang C. The photosynthetic and spectral reflectance characteristics of five Acer species in Changbai Mountain[D]. Beijing: Beijing Forestry University, 2013.
    [27] Gorelick N, Hancher M, Dixon M, et al. Google earth engine: planetary-scale geospatial analysis for everyone[J]. Remote Sensing of Environment, 2017, 202: 18−27. doi: 10.1016/j.rse.2017.06.031
    [28] 杜文先. 长白山杨桦林物候多样性及叶面积指数季节动态[D]. 北京: 北京林业大学, 2018.

    Du W X. Phenological diversity and seasonal leaf area index pattern of Betula-Populus forest in Changbai Mountain[D]. Beijing: Beijing Forestry University, 2018.
    [29] 于小舟, 袁凤辉, 王安志, 等. 积雪对长白山阔叶红松林土壤温度的影响[J]. 应用生态学报, 2010, 21(12):3015−3020.

    Yu X Z, Yuan F H, Wang A Z, et al. Effects of snow cover on soil temperature in broad-leaved Korean pine forest in Changbai Mountains[J]. Chinese Journal of Applied Ecology, 2010, 21(12): 3015−3020.
    [30] 章钊华, 赵书河, 丛佃敏, 等. 基于遥感的泰山地区植被绿度趋势变化研究[J]. 地理空间信息, 2018, 16(7):65−68. doi: 10.3969/j.issn.1672-4623.2018.07.020

    Zhang Z H, Zhao S H, Cong D M, et al. Vegetation greenness trend changes in Tai Mountain area based on remote sensing[J]. Geospatial Information, 2018, 16(7): 65−68. doi: 10.3969/j.issn.1672-4623.2018.07.020
    [31] 梁守真, 马万栋, 王猛, 等. 冠层绿色FPAR与植被指数关系及其对气溶胶的敏感性分析[J]. 测绘与空间地理信息, 2018, 41(12):11−14. doi: 10.3969/j.issn.1672-5867.2018.12.004

    Liang S Z, Ma W D, Wang M, et al. Analysis on the relationship between green FPAR and vegetation indices and their sensitivity to aerosol optical depth[J]. Geomatics & Spatial Information Technology, 2018, 41(12): 11−14. doi: 10.3969/j.issn.1672-5867.2018.12.004
    [32] 王宗明, 国志兴, 宋开山, 等. 中国东北地区植被NDVI对气候变化的响应[J]. 生态学杂志, 2009, 28(6):1041−1048.

    Wang Z M, Guo Z X, Song K S, et al. Responses of vegetation NDVI in northeast China to climate change[J]. Chinese Journal of Ecology, 2009, 28(6): 1041−1048.
    [33] 路中, 雷国平, 马泉来, 等. 基于重构的Landsat 8时间序列数据和温度植被指数的区域旱情监测[J]. 水土保持研究, 2018, 25(5):371−377.

    Lu Z, Lei G P, Ma Q L, et al. Regional drought monitoring based on reconstructed Landsat 8 data and temperature vegetation index[J]. Research of Soil and Water Conservation, 2018, 25(5): 371−377.
    [34] 张墨谦. 遥感时间序列数据的特征挖掘: 在生态学中的应用[D]. 上海: 复旦大学, 2014.

    Zhang M Q. Characterizing the remotely sensed time series data for ecological applications[D]. Shanghai: Fudan University, 2014.
    [35] 李百超. 基于高光谱成像技术的苹果叶片氮素含量估测研究[D]. 泰安: 山东农业大学, 2018.

    Li B C. Estimation of nitrogen content in apple leaves based on hyperspectral imaging technology[D]. Taian: Shandong Agricultural University, 2018.
    [36] 李淑敏, 李红, 孙丹峰, 等. PROSAIL冠层光谱模型遥感反演区域叶面积指数[J]. 光谱学与光谱分析, 2009, 29(10):2725−2729. doi: 10.3964/j.issn.1000-0593(2009)10-2725-05

    Li S M, Li H, Sun D F, et al. Estimation of regional leaf area index by remote sensing inversion of PROSAIL canopy spectral model[J]. Spectroscopy and Spectral Analysis, 2009, 29(10): 2725−2729. doi: 10.3964/j.issn.1000-0593(2009)10-2725-05
    [37] 张朋涛. 青海湖流域植被叶绿素含量遥感定量反演研究[D]. 西宁: 青海师范大学, 2015.

    Zhang P T. Chlorophyll content of vegetation in Qinghai Lake Basin quantitative remote sensing inversion[D]. Xining: Qinghai Normal University, 2015.
    [38] 徐光彩, 庞勇, 李增元, 等. 小兴安岭主要树种冠层光谱季相变化研究[J]. 光谱学与光谱分析, 2013, 33(12):3303−3307. doi: 10.3964/j.issn.1000-0593(2013)12-3303-05

    Xu G C, Pang Y, Li Z Y, et al. The changes of forest canopy spectral reflectance with seasons in Xiaoxing’anling[J]. Spectroscopy and Spectral Analysis, 2013, 33(12): 3303−3307. doi: 10.3964/j.issn.1000-0593(2013)12-3303-05
    [39] 周玉科. 基于遥感的中国东北植被物候不对称特征分析[J]. 遥感技术与应用, 2019, 34(2):345−354.

    Zhou Y K. Depicting the asymmetries of vegetation phenology over northeast China using remote sensing NDVI dataset[J]. Remote Sensing Technology and Application, 2019, 34(2): 345−354.
    [40] 赵冰茹, 马龙. 基于MODIS EVI的内蒙古草地多源信息综合分类研究[J]. 浙江大学学报(农业与生命科学版), 2007, 33(3):342−347.

    Zhao B R, Ma L. Multi-source data complex classification of grassland in Inner Mongolia based on MODIS EVI[J]. Journal of Zhejiang University (Agriculture & Life Sciences), 2007, 33(3): 342−347.
    [41] 方灿莹, 王琳, 徐涵秋. 不同植被红边指数在城市草地健康判别中的对比研究[J]. 地球信息科学学报, 2017, 19(10):1382−1392.

    Fang C Y, Wang L, Xu H Q. A comparative study of different red edge indices for remote sensing detection of urban grassland health status[J]. Journal of Geo-Information Science, 2017, 19(10): 1382−1392.
    [42] 赵冰茹, 贾翔, 金慧, 等. 1958—2015年长白山气候变化特征分析[J]. 北华大学学报(自然科学版), 2017, 18(6):727−731.

    Zhao B R, Jia X, Jin H, et al. Characteristics of climate change in Changbai Mountain from 1958 to 2015[J]. Journal of Beihua University (Natural Science), 2017, 18(6): 727−731.
    [43] 王小霞, 刘志华, 焦珂伟. 2000—2017年东北森林NDVI时空动态及其驱动因子[J]. 生态学杂志, 2020, 39(9):2878−2886.

    Wang X X, Liu Z H, Jiao K W. Spatiotemporal dynamics of normalized difference vegetation index (NDVI) and its drivers in forested region of Northeast China during 2000−2017[J]. Chinese Journal of Ecology, 2020, 39(9): 2878−2886.
    [44] 史国强, 牛丽君, 郭艳双,等. 长白山北坡春季物候特征及其对气候变化的响应[J]. 东北师大学报(自然科学版), 2019, 51(4):124−130.

    Shi G Q, Niu L J, Guo Y S, et al. Phenological characteristics of spring on the north slope of Changbai Mountain and its response to climate change[J]. Journal of Northeast Normal University (Natural Science Edition), 2019, 51(4): 124−130.
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出版历程
  • 收稿日期:  2020-11-29
  • 修回日期:  2021-01-20
  • 网络出版日期:  2021-05-15
  • 刊出日期:  2021-07-25

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