Cultivated land identification method, system and device based on curve-to-curve distance, and storage medium

Abstract

The embodiment of the invention relates to the technical field of remote sensing technologies, and discloses a cultivated land identification method, system and device based on the distance between curves, and a storage medium. The method comprises the steps of acquiring an NDVI time sequence curve of cultivated land crops and a first NDVI time sequence curve under a current area; determining a to-be-adjusted curve distance between the reference NDVI time sequence curve and the first NDVI time sequence curve under each pixel; performing weighting processing on a curve distance corresponding tothe growth period in the to-be-adjusted curve distances to obtain a target curve distance; and dividing the pixels corresponding to the target curve distance in the preset numerical range into cultivated land pixels. According to the embodiment of the invention, weighting processing can be carried out on the curve distance of the growing period part, the remote sensing classification precision for the cultivated land finally can be improved, and the technical problem that the cultivated land information is difficult to extract accurately by the existing remote sensing data classification technology is solved.

Description

technical field [0001] The present invention relates to the technical field of remote sensing technology, in particular to a method, system, equipment and storage medium for identifying cultivated land based on the distance between curves. Background technique [0002] Land cover is one of the basic elements of the natural environment in which humans live, and changes in land cover have a profound impact on environmental quality, biodiversity, productivity and adaptability of terrestrial ecosystems. [0003] To gain a better understanding of land cover status, land cover classification methods can be applied. [0004] As far as the land cover classification method is concerned, the land cover classification method is a key technology to understand the distribution characteristics and regional structure of land cover. At the same time, remote sensing technology has become the main data source for land cover classification due to its advantages of low cost and high efficiency....

AI Technical Summary

Problems solved by technology

Therefore, when classifying land cover in tropical climate regions based on remote sensing data, many difficulties are often encountered

[0006] The difficulties encountered are as follows. First, in the cloudy and rainy tropical monsoon climate zone, the vegetation growth season is generally in the rainy season, which makes it difficult to obtain high-quality images in the rainy season; second, due to the abundant precipitation and abundant light and heat conditions in the rainy season, For cultivated land in the monsoon region, crops can be planted at any time during the rainy season, which leads to inconsistent planting times even for the same crop, and the multiple cropping index is relatively high.

These conditions make it difficult to obtain accurate land information

[0007] It can be seen that the current remote sensing data classification technology has the technical problem that it is difficult to accurately extract cultivated land information.

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