Study on Vegetation Extraction Method in Karst Areas Based on Visible Light Band of Sentinel 2

doi:10.13466/j.cnki.lyzygl.2020.06.023

Abstract

Abstract:

In order to accurately extract vegetation information from visible band,study the characteristics of Karst vegetation in the visible light range and use the visible light band of the Sentinel 2 image,the spatial characteristics of the three bands of red,green and blue are created.The results showed that the spatial ratio characteristics of vegetation spectrum in blue-green are separable from other ground features and the brightness value of the vegetation is relatively low in the three visible lights.Comparing the extracted vegetation results with the normalized difference vegetation index,over-green index,ultra-green and ultra-red difference index,vegetation index,visible light band difference index,normalized green-red difference index,and normalized green-blue difference index,the study finds its precision is 92.67%,which is superior to other visible light extraction methods.It shows that the method is effective for the extraction of vegetation in Karst areas in the visible light band.

Key words: visible band, vegetation extraction, Karst landform, vegetation index, Sentinel 2 image

CLC Number:

TP79
P237

DUAN Jiwei, ZHONG Jiusheng, JIANG Li, DAI Renli, HE Zhiyuan, LIN Shuangshuang, HE Xin. Study on Vegetation Extraction Method in Karst Areas Based on Visible Light Band of Sentinel 2[J]. FOREST RESOURCES WANAGEMENT, 2020, (6): 143-152.

Figures/Tables 11

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波段	中心波长/nm	波段宽度/nm	空间分辨率/m	备注
2	492.4	98
3	559.8	45	10
4	664.6	38
8	832.8	145
5	704.1	19
6	740.5	18	20	窄波段红边
7	782.8	28
8a	864.7	33
11	1616.7	143	20
12	2202.4	242
1	442.7	27
9	945.1	26	60
10	1373.5	75

地物名称	红波段			绿波段			蓝波段
地物名称	均值	标准差	植被阈值内像素比/%	均值	标准差	植被阈值内像素比/%	均值	标准差	植被阈值内像素比/%
植被	450.72	94.87	100.00	709.79	134.97	100.00	402.56	76.68	100.00
水体	427.74	205.60	72.63	580.57	247.22	29.21	487.56	207.98	72.10
其他城市建筑	1156.81	354.36	19.21	1358.98	435.68	33.15	1156.81	354.36	9.73
裸土	2293.95	463.41	0	1871.77	437.28	0	1413.10	409.54	1.57
蓝色建筑	1296.93	277.43	5.52	1407.75	322.88	11.05	2274.54	298.77	0.26
火燎迹地	616.69	72.61	99.47	504.68	61.680	72.1	389.65	58.90	98.15
红色建筑	2088.54	714.92	0.26	1089.97	301.91	52.89	915.82	295.20	18.42
高速	1052.31	174.69	9.21	1038.19	142.65	43.42	888.84	132.88	2.36

光谱比值地类	斜率k值	截距b值	R²值	点线阈值	计算结果
绿比蓝植被	1.4676	108.03	0.834	(-138.3195,105.8213)	A2
绿比蓝水体	1.0125	51.588	0.8455	(-39.4251,67.3981)	B2
红比绿植被	0.6493	-5.224	0.6799	(-271.1123,171.7994)	C2
红比绿火烧迹地	1.0763	75.293	0.7138	(-97.6862,110.3322)	D2

植被指数提取方法	植被指数提取方法中文全称	公式	文献
NDVI	归一化差异植被指数	(NIR-R)/(NIR+R)	[3]
EXG	过绿指数	2g-r-b	[11]
EXGR	超绿超红差异指数	EXG-1.4r-g	[21]
VEG	植被指数	g/r⁰^.⁶⁷b⁰^.³³	[22]
VDVI	可见光波段差异指数	(2G-R-B)/(2G+R+B)	[23]
NGRDI	归一化绿红差异指数	(G-R)/(G+R)	[24]
NGBDI	归一化绿蓝差异指数	(G-B)/(G+B)	[25]

植被指数提取方法	总体精度/%	生产精度/%		用户精度/%		Kappa系数
植被指数提取方法	总体精度/%	植被	非植被	植被	非植被	Kappa系数
NDVI	94.13	94.59	93.67	93.63	94.63	0.8826
EXG	90.99	96.93	85.14	86.51	96.58	0.8200
EXGR	92.60	94.43	90.80	90.99	94.31	0.8521
VEG	91.57	96.590	86.63	87.66	96.27	0.8315
VDVI	90.12	97.60	82.76	84.77	97.23	0.8026
NGRDI	92.45	93.60	91.33	91.39	93.55	0.8491
NGBDI	77.49	97.09	58.21	69.56	95.32	0.5513
本文方法	92.67	94.46	90.92	91.09	94.34	0.8535