测绘通报 ›› 2015, Vol. 0 ›› Issue (1): 81-85.doi: 10.13474/j.cnki.11-2246.2015.0016
Previous Articles Next Articles
YIN Yaqiu, LI Jiaguo, YU Tao, YANG Hongyan, ZHANG Yonghong
Received:
2014-12-15
Online:
2015-01-25
Published:
2015-01-24
CLC Number:
YIN Yaqiu, LI Jiaguo, YU Tao, YANG Hongyan, ZHANG Yonghong. The Study of Object-oriented Water Body Extraction Method Based on High Resolution RS Image[J]. 测绘通报, 2015, 0(1): 81-85.
[1] 刘建波, 戴昌达. TM图像在大型水库库情监测管理中的应用[J]. 环境遥感, 1996, 11(1): 54-58. [2] 陆家驹, 李士鸿.TM资料水体识别技术的改进[J]. 环境遥感, 1992, 7(1): 17-23. [3] BARTON I J, BATHOLS J M. Monitoring Floods with AVHRR[J]. Remote Sensing of Environment, 1989, 30(1): 89-94. [4] 杜云艳, 周成虎. 水体的遥感信息自动提取方法[J]. 遥感学报, 1998, 2(4): 264-269. [5] 周成虎, 杜云艳, 骆剑承. 基于知识的AVHRR影像的水体自动识别方法与模型研究[J]. 自然灾害学报, 1996, 5(3): 100-108. [6] 杨存建, 徐美. 遥感信息机理的水体提取方法的探讨[J]. 地理研究, 1998, 17(S0): 86-89. [7] 徐涵秋. 利用改进的归一化差异水体指数(MNDWI)提取水体信息研究[J]. 遥感学报, 2005, 9(5): 589-595. [8] 乔玉良, 尚彦玲, 魏信. 遥感图像融合方法研究[J]. 气象与环境科学, 2010, 33(1): 73-76. [9] 曹凯, 江南, 吕恒,等. 面向对象的SPOT 5影像城区水体信息提取研究[J]. 国土资源遥感, 2007(2): 27-30. [10] 孙家炳. 遥感原理与应用[M]. 武汉: 武汉大学出版社, 2009:73-76. |
[1] | WANG Yanjun, LIN Yunhao, WANG Shuhan, LI Shaochun, WANG Mengjie. 3D road boundary extraction based on mobile laser scanning point clouds and OSM data [J]. Bulletin of Surveying and Mapping, 2022, 0(7): 18-25. |
[2] | LIU Lin, SUN Yi, LI Wanwu. Detection model construction based on CNN for offshore drilling platform and training algorithm analysis [J]. Bulletin of Surveying and Mapping, 2022, 0(7): 26-32,99. |
[3] | KONG Ruiyao, XIE Tao, MA Ming, KONG Ruilin. Application of CatBoost model in water depth inversion [J]. Bulletin of Surveying and Mapping, 2022, 0(7): 33-37. |
[4] | WEN Yuxiao, Lü Jie, MA Qingxun, ZHANG Peng, XU Ruling. Study on inversion of forest biomass by LiDAR and hyperspectral [J]. Bulletin of Surveying and Mapping, 2022, 0(7): 38-42. |
[5] | JIANG Zelin, DENG Jian, LUAN Haijun, LI Lanhui. Rapid extraction of COVID-19 information based on nighttime light remote sensing: a case study of Beijing [J]. Bulletin of Surveying and Mapping, 2022, 0(7): 43-48. |
[6] | ZHENG Yan, HE Huan, BU Lijing, JIN Xin. Super-resolution reconstruction method based on self-similarity and edge-preserving decomposition [J]. Bulletin of Surveying and Mapping, 2022, 0(7): 54-59. |
[7] | RAN Chongxian, LI Senlei. Tree canopy delineation using UAV multispectral imagery [J]. Bulletin of Surveying and Mapping, 2022, 0(7): 112-117. |
[8] | LIU Li, DONG Xianmin, LIU Juan, WEN Xuehu. A new method of remote sensing interpretation production based on integration of human-machine and intelligence [J]. Bulletin of Surveying and Mapping, 2022, 0(7): 118-123,137. |
[9] | AI Min, JING Hui, TIAN Yudong, GUO Lanqin, PEI Yuanjie. Analysis of land use and coverage change and driving force in Hulan district of Harbin city in recent 20 Years [J]. Bulletin of Surveying and Mapping, 2022, 0(7): 124-128. |
[10] | LIU Yuxian, RUAN Minghao, YAN Zhen. A method for accurate extraction of gated electric towers based on airborne laser point cloud [J]. Bulletin of Surveying and Mapping, 2022, 0(7): 129-133. |
[11] | LIU Guochao, PENG Weiping, YANG Shuihua, HU Zhouwen. Detection and application of urban road disease based on ground penetrating radar+3D measuring endoscope [J]. Bulletin of Surveying and Mapping, 2022, 0(7): 134-137. |
[12] | LIU Xiaoyu, LIU Yang, DU Mingyi, ZHANG Min, JIA Jingjue, YANG Heng. Research on construction and demolition waste stacking point identification based on DeeplabV3+ [J]. Bulletin of Surveying and Mapping, 2022, 0(4): 16-19,43. |
[13] | LI Jiahao, ZHOU Lü, MA Jun, YANG Fei, XIAN Lingxiao. Deformation monitoring and mechanism analysis of urban subway line based on PS-InSAR technology [J]. Bulletin of Surveying and Mapping, 2022, 0(4): 20-25. |
[14] | SHI Yun, SHI Longlong, NIU Minjie, ZHAO Kan. Multi-task automatic identification of loess landslide based on one-stage instance segmentation network [J]. Bulletin of Surveying and Mapping, 2022, 0(4): 26-31. |
[15] | DOU Shiqing, CHEN Zhiyu, XU Yong, ZHENG Hegang, MIAO Linlin, SONG Yingying. Hyperspectral image classification based on multi-feature fusion and dimensionality reduction algorithms [J]. Bulletin of Surveying and Mapping, 2022, 0(4): 32-36,50. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||