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浏览/检索结果: 共6条，第1-6条 帮助 已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Retrieving dynamics of the surface water extent in the upper reach of Yellow River 期刊论文 SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 卷号: 800, 页码: 17 作者:  Zhou, Haowei;  Liu, Suxia;  Hu, Shi;  Mo, Xingguo 收藏  |  浏览/下载：74/0  |  提交时间：2021/11/05 Surface water extent dynamics  Landsat images  Water extraction  Surface water gaps interpolation  Google Earth Engine   A detailed mangrove map of China for 2019 derived from Sentinel-1 and-2 images and Google Earth images 期刊论文 GEOSCIENCE DATA JOURNAL, 2021, 页码: 15 作者:  Zhao, Chuan-Peng;  Qin, Cheng-Zhi 收藏  |  浏览/下载：17/0  |  提交时间：2021/06/10 fragmented mangroves  Google Earth Engine  Google Earth images  mangrove map  Sentinel   Mapping coastal wetlands of China using time series Landsat images in 2018 and Google Earth Engine 期刊论文 ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2020, 卷号: 163, 页码: 312-326 作者:  Wang, Xinxin;  Xiao, Xiangming;  Zou, Zhenhua;  Hou, Luyao;  Qin, Yuanwei 收藏  |  浏览/下载：16/0  |  提交时间：2021/03/23 Coastal wetlands  Tidal flats  Coastal vegetation  Time series Landsat images  Pixel- and phenology-based algorithm  Google Earth Engine  China   Differences of Regulative Flexibility between Hydrological Isolated and Connected Lakes in a Large Floodplain: Insight from Inundation Dynamics and Landscape Heterogeneity 期刊论文 WATER, 2020, 卷号: 12, 期号: 4, 页码: 15 作者:  Teng, Jiakun;  Xia, Shaoxia;  Liu, Yu;  Cui, Peng;  Chen, Jiang 收藏  |  浏览/下载：7/0  |  提交时间：2021/07/09 inundation area  hydrological connectivity  remote sensing images  Google Earth Engine  Yangtze River Floodplain   Tracking annual changes of coastal tidal flats in China during 1986-2016 through analyses of Landsat images with Google Earth Engine 期刊论文 REMOTE SENSING OF ENVIRONMENT, 2020, 卷号: 238, 页码: 15 作者:  Wang, Xinxin;  Xiao, Xiangming;  Zou, Zhenhua;  Chen, Bangqian;  Ma, Jun 收藏  |  浏览/下载：10/0  |  提交时间：2020/05/19 Tidal flats  Time series Landsat images  Pixel and frequency-based algorithm  Google Earth Engine  China coastal zone   Automatic bridge extraction for optical images (EI CONFERENCE) 会议论文 6th International Conference on Image and Graphics, ICIG 2011, August 12, 2011 - August 15, 2011, Hefei, Anhui, China Gu D.-Y.; Zhu C.-F.; Shen H.; Hu J.-Z.; Chang H.-X. 收藏  |  浏览/下载：16/0  |  提交时间：2013/03/25 This paper describes a novel hierarchy algorithm for extracting bridges over water in optical images. To reduce the omission of bridges by searching the edge  we extract the river regions which the bridges are included in. Firstly  we segment the optical image to get the coarse water bodies using iterative threshold  eliminate the noise regions and add the missing regions based on k-means clustering with texture information and spatial coherence. Then  the blanks are connected based on shape features and candidate bridge regions are segmented from river regions. Finally  the bridges are verified by geometric information and the ubiety between bridges and river. The results show that this approach is efficient and effective for extracting bridges in satellite image from Google Earth and in aerial optical images acquired by unmanned aerial vehicle. 2011 IEEE.