Remote sensing identification method of evergreen plantation and remote sensing monitoring method of evergreen plantation growth

Abstract

The embodiment of the present invention provides a method for remote sensing identification of evergreen plantations and a method for remote sensing monitoring of evergreen plantation growth. Firstly, the first type of time is determined according to the first type of time series remote sensing images of the working area in each year within the target time range. The evergreen forest coverage index at each pixel position in the sequence of remote sensing images; then based on the evergreen forest coverage index at each pixel position, determine the evergreen forest planting area index at each pixel position within the target time range ; Finally, based on the evergreen forest planting area index at each pixel position, determine the historical evergreen forest distribution area in the working area within the target time range. Determining various indexes used to identify whether evergreen forests have been planted through time-series remote sensing images can make the distribution area of ​​historical evergreen forests more scientific, accurate and reliable.

Description

technical field [0001] The invention relates to the technical field of plant information identification, and more specifically, to an evergreen plantation remote sensing identification method and an evergreen plantation growth remote sensing monitoring method. Background technique [0002] At present, artificial planting of evergreen forests is an important method for ecological restoration and control in arid and semi-arid areas, and has attracted widespread attention. Zhangzi pine and masson pine are common evergreen tree species, and their growth is limited by natural and human factors such as water, soil nutrients, temperature, topography, and human disturbance. [0003] Due to the limitations of human understanding of factors such as the water resource carrying capacity of evergreen forest restoration in arid and semi-arid areas, it is difficult to identify which places are suitable for planting, which places are not suitable for planting, and which places are subject t...

AI Technical Summary

Problems solved by technology

However, due to the complex background information of evergreen forest land, time series change characteristics and trends, and the balance of growth areas, it will be difficult to achieve satisfactory results using the above methods.

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