Screening method of remote sensing image region covering dataset

doi:10.7523/j.ucas.2022.006

Abstract

Abstract: With the development of remote sensing satellite technology, the temporal and spatial resolution of remote sensing data has been continuously improved, showing the trend of big data and massive quantification, which has brought challenges to the screening of remote sensing data. Traditional remote sensing data retrieval often has the problem of large amount of query results and high overlap. It requires manual data selection, which is inefficient and low in accuracy. Therefore, how to quickly and accurately find the required data from a large number of remote sensing images is a problem that needs to be solved urgently. In this paper, a remote sensing data screening algorithm based on area coverage is used to divide the target area into non-overlapping fragments using the effective range of images. A normalized mathematical calculation model is established based on the number of fragments contained in the image, imaging time, and cloud cover. The model obtains a comprehensive cost. An optimal image combination is selected according to the cost, which completely covers the target area. This paper confirms the effectiveness of the method through Landsat8 data, and improves the screening efficiency through parallel computing.

Key words: remote sensing data retrieval, data screening, optimal image combination, parallel computing

CLC Number:

TP79

YAN Xuejing, LIU Wei, LIU Shibin, DUAN Jianbo, XIA Wei. Screening method of remote sensing image region covering dataset[J]. Journal of University of Chinese Academy of Sciences, 2023, 40(4): 523-530.

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