A Watershed Segmentation Method with Shape-Based Merging Criterion Based on Multispectral Remote Sensing Imagery

2011 ◽  
Vol 9 (3) ◽  
pp. 1006-1013 ◽  
Author(s):  
Anzhi Yue ◽  
Jianyu Yang ◽  
Chao Zhang ◽  
Wei Su ◽  
Wenju Yun ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Segmentation Method ◽  
Watershed Segmentation ◽  
Remote Sensing Imagery ◽  
Multispectral Remote Sensing

scholarly journals An Efficient Parallel Multi-Scale Segmentation Method for Remote Sensing Imagery

2018 ◽  
Vol 10 (4) ◽  
pp. 590 ◽  
Author(s):  
Haiyan Gu ◽  
Yanshun Han ◽  
Yi Yang ◽  
Haitao Li ◽  
Zhengjun Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Segmentation Method ◽  
Remote Sensing Imagery ◽  
Multi Scale

scholarly journals A Novel Remote Sensing Index for Extracting Impervious Surface Distribution from Landsat 8 OLI Imagery

2019 ◽  
Vol 9 (13) ◽  
pp. 2631 ◽  
Author(s):  
Hong Fang ◽  
Yuchun Wei ◽  
Qiuping Dai
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Impervious Surface ◽  
Landsat 8 ◽  
The Novel ◽  
Impervious Surfaces ◽  
Surface Distribution ◽  
Remote Sensing Imagery ◽  
Normalised Difference Vegetation Index ◽  
Multispectral Remote Sensing

The area of urban impervious surfaces is one of the most important indicators for determining the level of urbanisation and the quality of the environment and is rapidly increasing with the acceleration of urbanisation in developing countries. This paper proposes a novel remote sensing index based on the coastal band and normalised difference vegetation index for extracting impervious surface distribution from Landsat 8 multispectral remote sensing imagery. The index was validated using three images covering urban areas of China and was compared with five other typical index methods for the extraction of impervious surface distribution, namely, the normalised difference built-up index, index-based built-up index, normalised difference impervious surface index, normalised difference impervious index, and combinational built-up index. The results showed that the novel index provided higher accuracy and effectively distinguished impervious surfaces from bare soil, and the average values of the recall, precision, and F1 score for the three images were 95%, 91%, and 93%, respectively. The novel index provides better applicability in the extraction of urban impervious surface distribution from Landsat 8 multispectral remote sensing imagery.

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