Dr. Weimin Wang Profile

Dr. Weimin Wang

at Shenzhen Environmental Monitoring Ctr.

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Author

Publications (4)

Proceedings Article | 18 September 2018 Presentation + Paper

Investigation of the impact of urban vegetation on air pollutants based on remotely sensed measurements: a case study in Shenzhen, China

Weimin Wang, Lijun Yang, Liming Wang, Qinghuai Zeng, Lihuan He

Proceedings Volume 10767, 107670G (2018) https://doi.org/10.1117/12.2323686

KEYWORDS: Vegetation, Earth observing sensors, Landsat, Air contamination, Near infrared, Deposition processes, Analytical research, Atmospheric modeling, Clouds, Calibration

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Proceedings Article | 17 May 2016 Paper

Monitoring of urban heat island over Shenzhen, China using remotely sensed measurements

Weimin Wang, Liang Hong, Lijun Yang, Lihuan He, Guihua Dong

Proceedings Volume 9840, 98402A (2016) https://doi.org/10.1117/12.2240254

KEYWORDS: Statistical analysis, Landsat, Earth observing sensors, Environmental monitoring, Vegetation, Atmospheric corrections, Calibration, Clouds, Algorithm development, Climatology

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Proceedings Article | 24 October 2013 Paper

Object-based change detection in rapid urbanization regions with remotely sensed observations: a case study of Shenzhen, China

Lihuang He, Guihua Dong, Wei-Min Wang, Lijun Yang, Hong Liang

Proceedings Volume 8893, 88931W (2013) https://doi.org/10.1117/12.2031675

KEYWORDS: Image segmentation, Landsat, Image classification, Image processing, Environmental sensing, Process control, Environmental monitoring, Vegetation, Satellites, Earth observing sensors

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Proceedings Article | 17 October 2013 Paper

Two-stage algorithm for cloud detection with ZY-1 02C multi-spectral measurements

Ye-Yao Wang, Wei-Min Wang, Lijun Yang, Hong Liang

Proceedings Volume 8890, 889012 (2013) https://doi.org/10.1117/12.2031673

KEYWORDS: Clouds, Remote sensing, Satellites, Detection and tracking algorithms, Spatial resolution, Vegetation, Algorithm development, Visualization, Roads, Imaging systems

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Optical remote sensing observations often are the primary data source for many studies and applications in large scale, even in tropical regions. Frequent clouds over moist tropical regions often cause difficulty in obtaining good-quality high-resolution images. Different cloud styles and shadows make it hard to be masked on the images. The ZY-1 02C satellite, where multi-spectral and panchromatic imagers were on-boarded, was launched on 22 Nov. 2011. The objective of this satellite is to acquire data contributing for earth resources and environmental monitoring, as well as for other applications such as land use and disaster reduction. The multi-spectral imager has three wavebands, centered at 0.55 micrometer (green), 0.66 micrometer (red) and 0.83 micrometer (near infrared), at a spatial resolution of 10 meters. Panchromatic band, centered at 0.68 micrometer, has a spatial resolution of 5 m and is not used in this study. A twostage algorithm is presented to detect cloud and cloud shadow for ZY-1 02C multi-spectral measurements in this study. First, maximum and minimum filters with a moving window size of 5 by 5 pixels are operated on ZY-1 02C multispectral measurements. Optimal thresholds are selected by spatial statistics and visual examination. Pixels in maximumfiltered images with a grey level higher than the given thresholds (Tc) are labeled as potential cloud. In contrast, pixels in minimum-filtered images with a grey value lower than the given thresholds (Ts) are considered as potential shadow. Second, the contextual are used to mask out errors with potential cloud and shadow (e.g. vegetation canopy-cast shadow, road and bare soil) in previous stage. A window size of 9 by 9 centered at each potential cloud position is searched. If no potential shadow is found the potential cloud is rejected. Meanwhile, each potential shadow also is tested to get the final cloud and cloud shadow mask. Two ZY-1 02C multi-spectral images acquired over Pearl River Delta, a subtropical region in South China, are used to validate the two-stage algorithm. The research result indicates that, two-stage algorithm developed in this study has successfully detected the cloud and shadow on ZY-1 02C multi-spectral images.

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