Combining the Red Edge-Near Infrared Vegetation Indexes of DEM to Extract Urban Vegetation Information

Xiao-xuan WANG; Xiao-ping LU; Guo-qing LI; Jun WANG; Zen-an YANG; Yu-shi ZHOU; Zhi-li FENG

doi:10.3964/j.issn.1000-0593(2022)07-2284-06

Spectroscopy and Spectral Analysis, Volume. 42, Issue 7, 2284(2022)

Combining the Red Edge-Near Infrared Vegetation Indexes of DEM to Extract Urban Vegetation Information

Xiao-xuan WANG1,*... Xiao-ping LU1,1; *;, Guo-qing LI2,2;, Jun WANG2,2;, Zen-an YANG1,1;, Yu-shi ZHOU1,1; and Zhi-li FENG1,1; |Show fewer author(s)

Author Affiliations

¹1. Henan Polytechnic University, Key Laboratory of Spatio-Temporal Information and Ecological Restoration of Mines, Ministry of Natural Resources, Jiaozuo 454000, China

²2. Henan Institute of Remote Sensing and Geomatics, Zhengzhou 450000, China

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Figures & Tables(10)

Fig. 1. Remote Sensing Images of worldview-3

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Fig. 2. Red-edge band analysis diagram

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Fig. 3. Ground feature fitting maps

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Fig. 4. Model interpretation diagram

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Fig. 5. Interpretation diagram of a and c calculations

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Fig. 6. Graph of distance from sample point to l₃

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Fig. 7. Urban vegetations extracted by different indexes
(a), (e), (i): reference diagram; (b), (f), (j): NDVI; (c), (g), (k): EVI; (d), (h), (l): RENVI

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Table 1. Evaluation of vegetation extraction accuracy for the first scene

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Table 1. Evaluation of vegetation extraction accuracy for the first scene

光谱指数	地物	数据			用户精度/%	生产者精度/%	总体精度/(%/%)	Kappa系数
光谱指数	地物	植被	非植被	总计	用户精度/%	生产者精度/%	总体精度/(%/%)	Kappa系数
	植被	198	97	295	67.12	60.74
NDVI	非植被	128	79	205	38.53	44.87	55.40/54.23	0.497 6/0.482 3
	总计	326	176	500
	203	72	275	73.82	62.08
RVI植被	非植被	124	101	225	44.89	58.38	60.8/57.26	0.552 3/0.532 4
	总计	327	173	500
	植被	353	28	381	92.65	92.89
RENVI	非植被	27	92	119	77.31	76.67	89/87.63	0.852 8/0.843 6
	总计	380	120	500

Table 2. Evaluation of vegetation extraction accuracy for the second scene

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Table 2. Evaluation of vegetation extraction accuracy for the second scene

光谱指数	地物	数据			用户精度/%	生产者精度/%	总体精度/(%/%)	Kappa系数
光谱指数	地物	植被	非植被	总计	用户精度/%	生产者精度/%	总体精度/(%/%)	Kappa系数
	植被	192	87	264	72.72	58
NDVI	非植被	139	82	236	34.74	48.52	54.80/53.26	0.491 3/0.483 2
	总计	331	169	500
	植被	216	75	268	80.60	64.86
RVI	非植被	117	92	232	28.48	55.09	61.60/59.23	0.566 3/0.536 4
	总计	333	167	500
	植被	329	32	375	87.73	84.35
RENVI	非植被	47	78	125	62.4	70.9	81.4/80.69	0.791 3/0.775 6
	总计	390	110	500

Table 3. Evaluation of vegetation extraction accuracy for the third scene

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Table 3. Evaluation of vegetation extraction accuracy for the third scene

光谱指数	地物	数据			用户精度/%	生产者精度/%	总体精度/(%/%)	Kappa系数
光谱指数	地物	植被	非植被	总计	用户精度/%	生产者精度/%	总体精度/(%/%)	Kappa系数
	植被	198	68	273	72.53	57.22
NDVI	非植被	148	86	227	37.88	55.84	56.8/54.32	0.515 5/0.473 6
	总计	346	154	500
	植被	204	43	265	76.98	58.29
RVI	非植被	128	107	235	45.53	73.33	62.2/60.95	0.575 6/0.536 9
	总计	350	150	500
	植被	369	23	389	94.86	95.34
RENVI	非植被	18	90	111	81.08	79.65	91.8/88.23	0.905 2/0.875 3
	总计	387	113	500

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Xiao-xuan WANG, Xiao-ping LU, Guo-qing LI, Jun WANG, Zen-an YANG, Yu-shi ZHOU, Zhi-li FENG. Combining the Red Edge-Near Infrared Vegetation Indexes of DEM to Extract Urban Vegetation Information[J]. Spectroscopy and Spectral Analysis, 2022, 42(7): 2284

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