• Journal of Geo-information Science
  • Vol. 22, Issue 10, 1959 (2020)
Jiafeng XU, Yunmei LI*, Jie XU, Shaohua LEI, Shun BI, and Ling ZHOU
Author Affiliations
  • Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, China
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    DOI: 10.12082/dqxxkx.2020.190489 Cite this Article
    Jiafeng XU, Yunmei LI, Jie XU, Shaohua LEI, Shun BI, Ling ZHOU. Adaptive Threshold for Surface Shadow Detection of Black and Odor Water[J]. Journal of Geo-information Science, 2020, 22(10): 1959 Copy Citation Text show less
    The geographical location and surrounding environment of the study area
    Fig. 1. The geographical location and surrounding environment of the study area
    Example of sampling point collection
    Fig. 2. Example of sampling point collection
    Spectral characteristics of non-shadow water, shadow and vegetation on water surface
    Fig. 3. Spectral characteristics of non-shadow water, shadow and vegetation on water surface
    The scatter diagram of reflectance at 666 nm/791 nm and 492 nm
    Fig. 4. The scatter diagram of reflectance at 666 nm/791 nm and 492 nm
    Umbra, penumbra, non-shadow water image and reflectance spectral comparison
    Fig. 5. Umbra, penumbra, non-shadow water image and reflectance spectral comparison
    The process of surface shadow detection
    Fig. 6. The process of surface shadow detection
    The shadow detection result of test scenario 1
    Fig. 7. The shadow detection result of test scenario 1
    The shadow detection result of test scenario 2
    Fig. 8. The shadow detection result of test scenario 2
    The shadow detection result of test scenario 3
    Fig. 9. The shadow detection result of test scenario 3
    The shadow detection result of test scenario 4
    Fig. 10. The shadow detection result of test scenario 4
    Building shadow and tree shadow recognition effect
    Fig. 11. Building shadow and tree shadow recognition effect
    Analysis on the effect of floating objects on water shadow detection
    Fig. 12. Analysis on the effect of floating objects on water shadow detection
    The results of shadow detection when divided into 2 and 3 categories
    Fig. 13. The results of shadow detection when divided into 2 and 3 categories
    Black and odor water recognition result in test scenario 3 before and after shadow mask
    Fig. 14. Black and odor water recognition result in test scenario 3 before and after shadow mask
    序号仪器设备名称主要技术指标
    1大疆M600 pro多旋翼无人机旋翼数量:6个轴距:1133 mm起飞重量:15.5 kg最大载荷:6 kg 最大水平飞行速度:65 km/h(无风环境)最大续航时间:60 min(空载)18 min(5.5 kg载重)实用升限:4500 m
    2ZK-VNIR-FPG480机载高光谱成像仪光谱范围:400~1000 nm光谱分辨率:2.8 nm光谱通道数:270个空间通道数:480个空间分辨率:0.08 m(120 m高度)(35 mm镜头)视场角:26°A/D转换:12 bits最大帧频:100 fps数据接口:GigE最大功耗:20 W外形尺寸:310×87×87 mm重量:2.2 kg成像方式:采用外置推扫连续成像,采集画幅无限制,扫描路线一次成图,影像无畸变
    Table 1. Main technical parameters of the instrument and equipment
    区域生产者精度用户精度总体精度Kappa系数
    ηs/%ηn/%ps/%pn/%τ/%
    测试场景185.2782.8993.2567.0086.890.83
    测试场景289.5782.2689.0582.9887.300.88
    测试场景385.7095.2296.7491.7890.380.95
    测试场景490.0496.4984.5691.1588.610.92
    Table 2. Accuracy evaluation of each test scenario
    测试场景阴影提取前阴影提取后
    黑臭水体像元数/个正常水体像元数/个黑臭像元占比/%正常水体像元占比/%黑臭水体像元数/个正常水体像元数/个黑臭像元占比/%正常水体像元占比/%
    测试场景116 859562274.9925.01723514098.101.90
    测试场景227 202745078.5021.5013 04011299.150.85
    测试场景313 61212 88551.3748.6310 44553395.144.86
    测试场景417 827610674.4925.5112 13092892.897.11
    Table 3. The pixel proportion of black and odor water identified before and after shadow extraction
    Jiafeng XU, Yunmei LI, Jie XU, Shaohua LEI, Shun BI, Ling ZHOU. Adaptive Threshold for Surface Shadow Detection of Black and Odor Water[J]. Journal of Geo-information Science, 2020, 22(10): 1959
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