سابِق|تال

Automatic cloud detection for GF-4 series images

  • role： First author第一作者
  • Affiliation：

    Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China

  • Email：hucm@radi.ac.cn
  • Introduction：胡昌苗(1981—　)，男，助理研究员，研究方向为遥感辐射传输及大气校正理论和应用。E-mail：hucm@radi.ac.cn
Changmiao HU1,  
  • Affiliation：

    Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China

    University of Chinese Academy of Sciences, Beijing 100094, China

Yang BAI12,  
  • Affiliation：

    Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China

Ping TANG1

ملخص

The research on cloud detection is an important branch of remote sensing image research. In recent years, with the increasing number and type of remote sensing satellites, cloud detection based on reference map/sequence image has become a subject receiving close review in cloud detection. GF-4 is a geo-synchronous orbit satellite launched by China in December 2015. This satellite is equipped with a visible-light/near-infrared camera with a resolution of 50 m and has typical high-resolution and multi-spectral satellite data characteristics. GF-4 satellites have many common characteristics as meteorological satellites. These common features include the geostationary orbit, area array starring imaging, and the mid-infrared band. GF-4 has the capability to acquire the sequence data of the same area in a short time. This paper attached importance to the algorithm of automatic cloud detection for early GF-4 satellite data acquisition. The research is based on the same area of multiple GF-4 images. First, according to the characteristics of the image data and cloud in different images on the movement characteristics, this work performed automatic geometric registration and relative radiation normalization on multiple images. Then, the image was set to automatic threshold by cloud detection and was processed by the Savitzky–Golay filtering. Finally, this work implemented an automatic cloud detection algorithm for GF-4 sequence images. This paper selected 36 data in the eastern region of Inner Mongolia and 39 data in the middle and lower reaches of the Yangtze River for cloud testing to detect the practical feasibility of the new algorithm. The following preliminary conclusions were obtained. (1) The results of the cloud detection algorithm based on sequence image are superior to those of the single-image cloud detection in terms of overall accuracy. The main difference was observed in the image of the cloud boundary, highlighted surface, and thin cloud area. Through the experiment, this work showed that the algorithm has a high degree of automation and can satisfy the needs of engineering data. (2) Based on the single-image cloud detection, using the automatic threshold method can provide an overall stability for the test results. However, owing to the diversity of the cloud in the image, improving the accuracy is obviously difficult for the proposed algorithm. (3) The mid-infrared band data of GF-4 cannot be simply used for cloud detection due to differences in coverage area, spatial resolution, and acquisition time. The shortcoming of the current algorithm is that the acquisition time of the sequence data is extremely long. Eliminating the radiation difference between the data obtained in the morning and those obtained in the noon with the simple linear relation is difficult. Simultaneously, the follow-up research will focus on the systematic cloud detection accuracy evaluation method.

مفهوم

GF-4;cloud detection;automatically matching;Savitzky-Golay filtering

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