Identification of Single Plant of Karst Mountain Pitaya by Fusion of Color Index and Spatial Structure

Dongna Xiao; Zhongfa Zhou; Linjiang Yin; Denghong Huang; Yang Zhang; Qianxia Li

doi:10.3788/LOP202259.1028010

Journals >Laser & Optoelectronics Progress >Volume 59 >Issue 10 >Page 1028010 > Article

Laser & Optoelectronics Progress
Vol. 59, Issue 10, 1028010 (2022)

Identification of Single Plant of Karst Mountain Pitaya by Fusion of Color Index and Spatial Structure

Dongna Xiao^1、2, Zhongfa Zhou^1、2、*, Linjiang Yin^1、2, Denghong Huang^1、2, Yang Zhang^1、2, and Qianxia Li^1、2

Author Affiliations

¹School of Karst Science/School of Geography ＆ Environmental Science, Guizhou Normal University, Guiyang 550001, Guizhou , China

²State Engineering Technology Institute For for Karst Desertification Control, Guizhou Normal University, Guiyang 550001, Guizhou , China

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DOI: 10.3788/LOP202259.1028010 Cite this Article Set citation alerts

Dongna Xiao, Zhongfa Zhou, Linjiang Yin, Denghong Huang, Yang Zhang, Qianxia Li. Identification of Single Plant of Karst Mountain Pitaya by Fusion of Color Index and Spatial Structure[J]. Laser & Optoelectronics Progress, 2022, 59(10): 1028010 Copy Citation Text

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Fig. 1. Location diagram of study area. (a) DEM of Huajiang demonstration area; (b) visible remote sensing image of study area

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Fig. 2. Method test area and profile of its point cloud data. (a) Visible remote sensing image; (b) image matching point cloud data;(c) point cloud data profile

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Fig. 3. Schematic of extraction method of color index and CHM segmentation intersection fusion

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Fig. 4. Technology roadmap

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Fig. 5. Precision test standard of segmentation. (a) Match; (b) over matching; (c) over segmentation; (d) wrong segmentation; (e) missed inspection

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Fig. 6. Histograms of number of pixels with different color indices. (a) VDVI; (b) NGBDI; (c) NGRDI; (d) RGBVI

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Fig. 7. Extraction results of vegetation index. (a) VDVI; (b) NGBDI; (c) NGRDI; (d) RGBVI

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Fig. 8. Preprocessing results of point cloud data. (a) DEM; (b) DSM; (c) CHM; (d) CHM segmentation

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Fig. 9. Segmentation results of fusion of each color index and CHM segmentation. (a) VDVI_CHM; (b) NGBDI_CHM;(c) NGRDI_CHM; (d) RGBVI_CHM

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Fig. 10. Comparison of extraction results between local fusion method and single factor extraction

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Fig. 11. Box scatter diagram of four fusion results extraction and true value fitting degree

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Fig. 12. Extraction process diagram and segmentation results of accuracy verification area. (a) DEM; (b) CHM; (c) VDVI; (d) VDVI_CHM

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Training sample region	Red light band	Green light band	Blue light band
Pitaya area	0.235	0.213	0.251
Weeds	0.191	0.154	0.189
Bare land	0.100	0.122	0.138
Gravel ladder insuperior	0.180	0.196	0.189
Constructions	0.126	0.122	0.107

Table 1. Variation coefficient of reflection value in visible light band of training sample area

Vegetation index	Equation
VDVI	$(2 \times G - R - B) / (2 \times G + R + B)$
NGBDI	$(G - B) / (G + B)$
NGRDI	$(G - R) / (G + R)$
RGBVI	$(G \times R - R \times B) / (G \times G + R \times B)$

Table 2. Calculation formula of vegetation indexs

Segmentation type	P_P	P_C	S_C	L	P	R	F
VDVI	59.38	34.06	6.56	0.00	59.38	39.83	47.68
NGBDI	61.00	37.67	1.33	0.63	61.00	38.36	47.10
NGRDI	69.72	21.88	8.40	4.19	69.72	57.44	62.99
RGBVI	58.69	39.02	2.30	0.63	58.69	37.53	45.78

Table 3. Accuracy table of pitaya tree number extracted by each vegetation index

Parameter	P_P	P_C	S_E	S_C	L	P	R	F
Value	36.21	39.42	2.37	22.00	1.05	36.21	44.86	40.07

Table 4. Precision table of CHM segmentation

Segmentation type	P_P	P_C	S_E	S_C	L	P	R	F
VDVI_CHM	94.06	1.70	3.18	1.06	1.05	94.06	92.87	93.46
NGBDI_CHM	93.05	2.95	2.74	1.26	1.05	93.05	92.66	92.86
NGRDI_CHM	93.60	1.77	2.21	2.43	6.92	93.60	88.89	91.18
RGBVI_CHM	92.26	3.35	1.26	3.14	1.68	92.26	92.45	92.36

Table 5. Accuracy table of extraction based on CHM segmentation and fusion of four color indices

Segmentation type	Increase in relative vegetation index			Increase relative to CHM segmentation
Segmentation type	P	R	F	P	R	F
VDVI	34.68	53.04	45.78	57.85	48.01	53.39
NGBDI	32.05	54.30	45.75	56.84	47.80	52.78
NGRDI	23.88	31.45	28.19	57.39	44.03	51.11
RGBVI	33.57	54.93	46.58	56.05	47.59	52.28

Table 6. Comparison table of segmentation fusion results and extraction accuracy of single factor

Parameter	Mean value	Standard deviation	Variance	Skewness	Peakedness
True_AREA	133.800	37.496	1405.931	0.645	0.893
VDVI_AREA	144.293	48.244	2327.446	0.617	0.520
RGBVI_AREA	143.472	49.844	2484.471	0.862	1.874
NGBDI_AREA	143.571	51.018	2602.808	1.006	1.909
NGRDI_AREA	110.841	55.569	3087.924	1.502	3.984

Table 7. Description and analysis of basic data of real value and area value extracted by fusion

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