基于无人机影像和面向对象随机森林算法的岩溶湿地植被识别方法研究

doi:10.12082/dqxxkx.2019.180631

Abstract

Abstract:

Wetlands are among the most important ecosystems on Earth. They play a key role in alleviating floods and filtering polluted water, and also provide habitats for many plants and animals. A unique wetland type, karst wetland, is widely distributed in southwest China, as influenced by the special soil and water structure of karst landforms. Currently, domestic and foreign scholars pay much less attention to karst wetland than other wetland types, and lack targeted research on high-precision vegetation identification of karst wetland using remote sensing technology. However, like other wetland types, karst wetland has seriously degraded, and many problems need to be solved urgently. Huixian National Wetland Park, located in Guilin, Guangxi province, is a typical karst wetland. In this paper, part of the core area of the Huixian National Wetland Park was selected as the study area, which is greatly affected by human activities and severely degraded. The aerial photography images from an unmanned aerial vehicle (UAV) were used as the data source, and the object-based random forest algorithm was used to realize the high-precision classification of karst wetland vegetation. In so doing, we explored the applicability of UAV RGB remote sensing image and object-based random forest algorithm in karst wetland vegetation recognition, and provided a technical reference for the research and protection of karst wetland by using UAV remote sensing technology. First, the multiscale iterative segmentation algorithm was used to segment the image layers in eCognition Developer 9.0. Then, the texture features calculated based on the grey level co-occurrence matrix (GLCM) and spectral features of the images, the vegetation indexes, geometric features, and the elevation information (DSM) derived from the UAV remote sensing data were fully considered in the feature selection. Finally, the tuning of random forest algorithm parameters, model construction, and classification were implemented in RStudio. Results showed that the object-based random forest algorithm had a high recognition ability for the Huixian wetland vegetation. The overall accuracy was 86.75% and the Kappa coefficient was 0.83 in the 95% confidence interval. In the identification accuracy of vegetation in a single typical karst wetland, the user accuracy of the vegetation cluster of Bermudagrass-Cogongrass-Ludwigia was above 90%, the producer accuracy was over 80%. And the producer accuracy of the Bamboo-Thorny Wingnic-Sweet Olive was higher than 80%, but its user accuracy was only 70.59%.

Key words: UAV remote sensing, object-based, random forest, multiscale iterative segmentation, feature selection, karst wetland, vegetation classification, Huixian National Wetland Park, located in Guilin, Guangxi province

GENG Renfang,FU Bolin,CAI Jiangtao,CHEN Xiaoyu,LAN Feiwu,YU Hangming,LI Qingxun. Object-Based Karst Wetland Vegetation Classification Method Using Unmanned Aerial Vehicle images and Random Forest Algorithm[J].Journal of Geo-information Science, 2019, 21(8): 1295-1306.DOI:10.12082/dqxxkx.2019.180631

Figures/Tables 13

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References 27

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类型	岩溶河流-岩溶湖泊	狗牙根-白茅-水龙	水稻	竹子-马甲子-桂花	菩提树	柑橘	建设用地	总计
训练样本	26	36	34	23	20	7	14	160
验证样本	39	47	6	29	28	3	14	166

	处理时间	空三误差/像元
Smart 3D	5h:10m:8s	0.72
Pix4D Mapper	1h:20m:57s	0.43
Drone2Map	1h:31m:9s	0.24
One Button	3h:56m:58s	-

参数	精细尺度	中等尺度	大尺度
初始值	13	26	37
步长	10	30	50
迭代次数	100	100	100
Shape	0.7	0.7	0.7
Compactness	0.5	0.5	0.5

类别	面积/hm²	比重/%
水稻	0.91	3
柑橘	0.37	1
菩提树	3.74	13
建设用地	0.31	1
狗牙根-白茅-水龙	12.84	45
竹子-马甲子-桂花	5.66	20
岩溶河流-岩溶湖泊	4.84	17

检验指标	精度评估	标准差	95%置信区间
总体精度/%	86.75	2.47	81.91	91.59
Kappa系数	0.83	0.03	0.77	0.90

Object-Based Karst Wetland Vegetation Classification Method Using Unmanned Aerial Vehicle images and Random Forest Algorithm

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类别	用户精度				生产者精度
类别	精度评估	标准差	95% 置信区间		精度评估	标准差	95% 置信区间
狗牙根-白茅-水龙	92.86	2.00	88.94	96.77	82.98	3.16	76.78	89.18
柑橘	100.00	0.00	100.00	100.00	100.00	0.00	100.00	100.00
竹子-马甲子-桂花	70.59	3.54	63.66	77.52	82.76	6.22	70.57	94.95
菩提树	79.31	3.14	73.15	85.47	82.14	7.46	67.52	96.76
岩溶河流-岩溶湖泊	94.87	1.71	91.52	98.23	94.87	4.02	87.00	102.74
水稻	100.00	0.00	100.00	100.00	100.00	0.00	100.00	100.00
建设用地	92.31	2.07	88.25	96.36	85.71	23.17	40.30	131.13