Research on the Inversion Method of Desert Grassland Fractional Vegetation Cover based on Collaborative UAV-Satellite Remote Sensing

Kexin NING; Chenxi SUN; Huawei WAN; Yanmin SHUAI

doi:10.11873/j.issn.1004-0323.2024.5.1054

Remote Sensing Technology and Application, Volume. 39, Issue 5, 1054(2024)

Research on the Inversion Method of Desert Grassland Fractional Vegetation Cover based on Collaborative UAV-Satellite Remote Sensing

Kexin NING, Chenxi SUN, Huawei WAN, and Yanmin SHUAI

Author Affiliations

School of Surveying and Mapping and Geographical Sciences，Liaoning University of；Engineering and Technology， Fuxin123000， China

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Figures & Tables(10)

Fig. 1. Location map of study area and satellite，UAV images

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Fig. 2. Technology roadmap

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Fig. 3. Fractional vegetation cover extraction effect based on pixel scale of BJ3 satellite image

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Fig. 4. Pearson correlation matrix

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$Fitting curve between measured and predicted values of fractional vegetation cover$

Fig. 5. Fitting curve between measured and predicted values of fractional vegetation cover

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$Error distribution box chart of fractional vegetation cover of inversion results of NDVI quadratic polynomial model， random forest model and pixel dichotomy model$

Fig. 6. Error distribution box chart of fractional vegetation cover of inversion results of NDVI quadratic polynomial model， random forest model and pixel dichotomy model

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$Inversion results of fractional vegetation cover in various models based on satellite image$

Fig. 7. Inversion results of fractional vegetation cover in various models based on satellite image

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Table 1. Table1The corresponding relationship between satellite data and UAV data
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Table 1. Table1The corresponding relationship between satellite data and UAV data
波段 BJ3N1 MS数据无人机数据
中心波长
/nm
空间分辨率
/m
中心波长
/nm
空间分辨率
/m
Dark Blue 436 1.2 - -
Blue 483 450 0.033
Green 561 555
Red 653 660
Red Edge 722 720
Near infrared 828 840

Table 2. Table2Formula for calculating vegetation indices

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Table 2. Table2Formula for calculating vegetation indices

植被指数	公式
归一化植被指数NDVI	$N D V I = (ρ_{N I R} - ρ_{R}) / (ρ_{N I R} + ρ_{R})$
增强型植被指数EVI	$E V I = G \times (ρ_{N I R} - ρ_{R}) / (ρ_{N I R} + C_{1} \times ρ_{R} - C_{2} \times ρ_{B} + L)$
比值植被指数RVI	$R V I = ρ_{N I R} / ρ_{R}$
差值植被指数DVI	$D V I = ρ_{N I R} - ρ_{R}$
土壤调节植被指数SAVI	$S A V I = (ρ_{N I R} - ρ_{R}) \times (1 + L_{1}) / (ρ_{N I R} + ρ_{R} + L_{1})$
修正土壤调整植被指数MSAVI	$M S A V I = (2 ρ_{N I R} + 1 - \sqrt[]{(2 ρ_{N I R} {+ 1)}^{2} - 8 (ρ_{N I R} - ρ_{R})}) / 2$

Table 3. Table3Inversion model of fractional vegetation cover based on regression analysis method

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Table 3. Table3Inversion model of fractional vegetation cover based on regression analysis method

植被指数	模型类型	模型	R²	RMSE
NDVI	指数模型	$y = 6.70 E - 05 ⅇ^{18.827 x}$	0.772	0.463
	二次多项式模型	$y = 13.671 x^{2} - 6.787 x + 0.714$	0.778	0.131
	幂函数模型	$y = 271.2 x^{8.382}$	0.811	0.422
EVI	二次多项式模型	$y = 5.629 x^{2} + 1.789 x - 0.884$	0.762	0.136
	幂函数模型	$y = 543.854 x^{7.092}$	0.772	0.463
RVI	线性模型	$y = 0.809 x - 1.694$	0.771	0.133
	对数模型	$y = 2.133 l n (x) - 1.614$	0.760	0.136
	二次多项式模型	$y = 0.015 x^{2} + 0.73 x - 1.589$	0.771	0.133
SAVI	二次多项式模型	$y = 10.023 x^{2} + 1.231 x - 0.875$	0.763	0.135
	幂函数模型	$y = 3689.991 x^{7.879}$	0.761	0.474

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Kexin NING, Chenxi SUN, Huawei WAN, Yanmin SHUAI. Research on the Inversion Method of Desert Grassland Fractional Vegetation Cover based on Collaborative UAV-Satellite Remote Sensing[J]. Remote Sensing Technology and Application, 2024, 39(5): 1054

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Paper Information

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Received: Aug. 15, 2023

Accepted: --

Published Online: Jan. 7, 2025

The Author Email:

DOI:10.11873/j.issn.1004-0323.2024.5.1054

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Table1The corresponding relationship between satellite data and UAV data

Table 1. Table1The corresponding relationship between satellite data and UAV data

Table 2. Table2Formula for calculating vegetation indices

Table 2. Table2Formula for calculating vegetation indices

Table 3. Table3Inversion model of fractional vegetation cover based on regression analysis method

Table 3. Table3Inversion model of fractional vegetation cover based on regression analysis method