Grassland rodent damage monitoring method based on low-altitude remote sensing

Abstract

The invention relates to the field of rat damage image processing, and aims at providing a grassland rat damage monitoring method based on low-altitude remote sensing, and the method comprises the steps: obtaining an aerial photo of an experiment region through an unmanned plane, processing the aerial photo through a Pix4D map platform, and obtaining four low-altitude remote sensing orthoimages; wherein the images comprise a zokor damage area image in spring, a zokor damage area image in summer, a marmot damage area image in spring and a marmot damage area image in summer. On the basis of fully mastering surface features of different rodent damages, surface rodent damage information of four images is extracted one by one by using four methods of gray threshold segmentation, color texture optimization, rule-based object-oriented and BP neural networks, and then the extraction precision is evaluated by using double evaluation standards of spatial precision and quantitative precision so as to obtain the surface rodent damage information of the four images. The method for extracting the rat damage information in the images in different seasons is reasonable in structure, ingenious in design and suitable for popularization.

Description

technical field [0001] The invention relates to the field of obtaining rodent damage information by low-altitude remote sensing, in particular to a grassland rodent damage monitoring method based on low-altitude remote sensing. Background technique [0002] For a long time, due to people's emphasis on grassland utilization and light management, rodent damage has become one of the main factors threatening grassland ecological security, seriously restricting the sustainable development of grassland animal husbandry [4-6]. Since the 1990s, my country's grassland rodents have occurred frequently, which not only caused serious losses to grassland resources, but also exacerbated the degradation and desertification of grasslands. Traditional medium and high-resolution satellite images are difficult to meet the high precision of grassland rodent monitoring. Requirements, with the rapid development of low-altitude remote sensing technology, a new direction has appeared in the research...

AI Technical Summary

Problems solved by technology

Since the 1990s, my country's grassland rodents have occurred frequently, which not only caused serious losses to grassland resources, but also exacerbated the degradation and desertification of grasslands. Traditional medium and high-resolution satellite images are difficult to meet the high precision of grassland rodent monitoring. Requirements, with the rapid development of low-altitude remote sensing technology, a new direction has appeared in the research of rodent monitoring. With the wide application of drones in the industry, remote sensing technology is developing at an unprecedented speed to ultra-high Due to the high resolution of satellite images, it is difficult to accurately obtain information on rodent damage on the ground. UAV images have sub-meter spatial resolution, and the sensor can be changed according to research needs, and the flight height can be adjusted to obtain centimeter-level resolution. This will greatly affect the expression of ground rodent damage information on the image, making the rodent damage information have more abundant features

[0003] CN201710636249.5, a UAV pasture management system and method. The invention provides a UAV pasture management system and method. The method includes: taking remote sensing images of grazing areas, and detecting soil information through soil detection sensors; Regional remote sensing images are used to distinguish pasture areas and non-grazing areas, and the above remote sensing images are divided into grazing areas and non-grazing areas according to the herd location, and the rat holes in the non-grazing area are marked; Grass coverage in the area, and determine the level of pest damage in the third detection unit, and analyze the soil conditions at the same time, and send the analysis results to the control station; select the area to be tested with the maximum grassland vegetation coverage in the remote sensing image of the second detection unit, According to the location of the area to be measured, control the UAV to drive towards the area to be measured; monitor the grassland vegetation, rat holes, and soil conditions in real time, and at the same time, during the grazing process, automatically grazing through the vegetation in the herd grazing area, However, for different rodents, it is not known whether the above method can obtain the best accuracy.

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