Research on Inversion of Water Conservation Capacity of Forest Litter in Yarlung Zangbo Grand Canyon Based on Spectral Features

Qian-qian LONG; Ren-hao ZHOU; De-peng YUE; Teng NIU; Xue-qing MAO; Peng-chong WANG; Qiang YU

doi:10.3964/j.issn.1000-0593(2022)01-0229-07

Spectroscopy and Spectral Analysis, Volume. 42, Issue 1, 229(2022)

Research on Inversion of Water Conservation Capacity of Forest Litter in Yarlung Zangbo Grand Canyon Based on Spectral Features

Qian-qian LONG^1、*, Ren-hao ZHOU^2、2;, De-peng YUE^1、1;, Teng NIU^1、1;, Xue-qing MAO^1、1;, Peng-chong WANG^3、3;, and Qiang YU^{1、1; *;}

Author Affiliations

¹1. Beijing Key Research Office of Precision Forestry, Beijing Forestry University, Beijing 100083, China

²2. Cyberspace Security Academy, Chengdu University of Information Technology, Chengdu 610200, China

³3. Beijing Linmiao Ecological Environment Technology Co., Ltd., Beijing 100085, China

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Figures & Tables(11)

Fig. 1. Surface profile and sampling points distribution in the study area

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Fig. 2. Spectral reflectance of leaves

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Fig. 3. First derivative of spectrum
(a): The visible light band; (b): The red-edged band

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Fig. 4. Water conservation and distribution of forest litter in Grand Canyon

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Fig. 5. Precision evaluation of water conservation capacity for different species litter layer in model
(a): Pinus densata; (b): Picea Linzhi; (c): Quercusaqui folioides

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Table 1. Characteristic spectral parameters and calculation method

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Table 1. Characteristic spectral parameters and calculation method

植被指数	计算方法
NDVI	$\frac{ρ_{N IR} - ρ_{R}}{ρ_{NIR} + ρ_{R}}$
EVI	2.5× $\frac{ρ_{NIR} - ρ_{R}}{ρ_{NIR} + (6 \times ρ_{R} - 7.5 \times ρ_{B}) + 1}$
VOG	$\frac{ρ_{RE 2}}{ρ_{RE 1}}$
LCI	$\frac{ρ_{NIR} - ρ_{RE 1}}{ρ_{NIR} - ρ_{R}}$
GVMI	$\frac{(ρ_{NIR} + 0.1) - (ρ_{MIR} + 0.02)}{(ρ_{NIR} + 0.1) + (ρ_{MIR} + 0.02)}$
NRI	$\frac{ρ_{G}}{ρ_{R}}$
PWP	$\frac{ρ_{G}}{ρ_{G} - ρ_{R}}$
PSRI	$\frac{ρ_{R} - ρ_{B}}{ρ_{RE 2}}$

Table 2. Parameter of blue edge, yellow edge and red edge
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Table 2. Parameter of blue edge, yellow edge and red edge
树种蓝边位
置/nm 黄边位
置/nm 红边位
置/nm 红边
斜率红边峰
值面积
高山松 524 567 721 0.009 5 0.404 1
林芝云杉 522 572 717 0.006 3 0.307 6
川滇高山栎 524 568 721 0.011 9 0.523 0

Table 3. Litter Stock volume and natural water content
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Table 3. Litter Stock volume and natural water content
树种蓄积量自然
含水
率/%
未分解层
占比/% 半分解层
占比/% 总量
/(t·ha^-1)
高山松 53.68 46.32 17.53 30.84
林芝云杉 29.18 70.82 26.46 69.06
川滇高山栎 41.17 58.83 25.14 62.89

Table 4. Water holding capacity of litter
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Table 4. Water holding capacity of litter
树种最大持水
率/% 最大持水量
/(t·ha^-1) 有效拦蓄
率/% 有效拦蓄量
/(t·ha^-1)
高山松 253.19 44.38 184.37 32.32
林芝云杉 296.25 78.39 182.75 48.36
川滇高山栎 257.61 64.76 156.08 39.24

Table 5. Person correlation coefficient analysis

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Table 5. Person correlation coefficient analysis

植被指数	Person相关系数
植被指数	高山松	林芝云杉	川滇高山栎
NDVI	0.481^*	0.277	0.204
EVI	0.288	0.331^*	0.231
VOG	0.345	0.312^*	0.358^*
GVMI	0.507^*	0.546^**	0.407^*
LCI	0.396^*	0.235	0.375^*
NRI	0.194	0.363^*	0.289
PWP	-0.623^**	-0.437^*	-0.565^**
PSRI	-0.519^**	-0.544^*	-0.442^**

Table 6. Inversion model of water conservation in litter layer of different tree species

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Table 6. Inversion model of water conservation in litter layer of different tree species

植被类型	反演模型	R²
高山松	W_L=-13.78PWP^*-10.69PSRI^+8.24GVMI^+5.51NDVI^+2.82LCI^*+69.03	0.691
林芝云杉	W_L=21.43GVMI^-15.77PWP^-10.81PSRI^+9.38NRI^+7.88EVI^+2.51VOG^+20.14	0.779
川滇高山栎	W_L=-15.16PWP^*-12.73PSRI^+12.62GVMI^+9.64LCI^+6.79VOG^*+72.11	0.743

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Qian-qian LONG, Ren-hao ZHOU, De-peng YUE, Teng NIU, Xue-qing MAO, Peng-chong WANG, Qiang YU. Research on Inversion of Water Conservation Capacity of Forest Litter in Yarlung Zangbo Grand Canyon Based on Spectral Features[J]. Spectroscopy and Spectral Analysis, 2022, 42(1): 229

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