Remote sensing extraction method for soil erosion degree of cultivated land in black soil area

Abstract

The invention relates to the field of farmland erosion degree rapid monitoring methods, and discloses a black soil area farmland soil erosion degree remote sensing extraction method, which comprises the following steps: S1, acquiring farmland range data, and collecting vector data of a farmland range of a research area; s2, selecting a remote sensing image, and performing image preprocessing such as radiation correction, atmospheric correction, geographical registration and cultivated land range mask extraction; s3, a soil erosion degree index is calculated, and remote sensing image related wavebands are calculated through professional software; step S4, soil erosion degree grading: according to ground survey data, soil erosion degree index values are graded into non-erosion, slight erosion, medium erosion and serious erosion, the method is simple in input quantity, high in adaptability and suitable for dynamically monitoring the cultivated land erosion degree in a large range, and a scientific basis is provided for land resource management and soil protection.

Description

Technical Field

[0001] The present invention relates to the field of rapid monitoring methods for cultivated land erosion degree, and specifically to a method for remotely sensing and extracting the soil erosion degree of cultivated land in black soil areas. Background Technique

[0002] Black soil is a type of soil with a relatively thick soil surface layer, a darker color, and a high organic matter content. It is a high-quality and important agricultural land. However, with the increase in tillage intensity and the influence of other natural factors, the cultivated land in black soil areas is facing a serious threat of soil erosion. Severe soil and water loss significantly reduces the content of soil nutrients and directly affects soil productivity.

[0003] The traditional universal soil loss equation requires a large amount of input data, including rainfall erosivity (R), soil erodibility factor (K), land slope (S), land length (L), vegetation cover (C), and tillage management practices (P), etc. These input quantities are often difficult to obtain with too rough resolution and require continuous calibration, which limits their application at medium and large scales and is more suitable for small-scale soil loss assessment.

[0004] Currently, remote sensing-based soil erosion monitoring methods usually require constructing complex data sets and performing cumbersome model training. However, this accuracy is based on the accurate interpretation of images by experts with rich experience. Therefore, to obtain accurate soil erosion type and intensity distribution maps, a large number of professional and technical personnel must be equipped, which limits their universal application.

[0005] Generally speaking, most of the existing erosion monitoring methods rely on ground observations, with problems such as large pre-workload, high professional skill requirements, and small coverage area. The lack of a simple and universal spectral index expression has become an important bottleneck restricting soil erosion monitoring. For this reason, the present invention proposes a method for remotely sensing and extracting the soil erosion degree of cultivated land in black soil areas. Summary of the Invention

[0006] The purpose of the present invention is to provide a method for remotely sensing and extracting the soil erosion degree of cultivated land in black soil areas to solve the problems raised in the above background technique.

[0007] To achieve the above purpose, the present invention provides the following technical solution: A method for remotely sensing and extracting the soil erosion degree of cultivated land in black soil areas, including the following steps: Step S1, obtaining cultivated land range data and collecting vector data of the cultivated land range in the study area; Step S2, selecting remote sensing images and performing image preprocessing such as radiometric correction, atmospheric correction, georegistration, and cultivated land range masking extraction; Step S3, calculating the soil erosion degree index by calculating relevant bands of the remote sensing images through professional software; Step S4, classifying the soil erosion degree, and classifying the soil erosion degree index values into non-erosion, slight erosion, moderate erosion, and severe erosion according to ground survey data.

[0008] Preferably, in step S2, remote sensing images during the bare soil period, without cloud cover, with less straw coverage, and having red, blue, near-infrared, and short-wave infrared bands are selected.

[0009] Preferably, the soil erosion degree index constructed in step S3, and the calculation process of the soil erosion degree index is ESI = (R / B) / (SWIR1 / NIR), where R is the red band, B is the blue band, SWIR1 is the short-wave infrared band, and NIR is the near-infrared band.

[0010] Preferably, in step S4, the relationship between the field monitoring data and the soil erosion degree index is analyzed, and based on the existing threshold of the field monitoring data, the soil erosion degree of cultivated land is qualitatively divided.

[0011] Preferably, the soil erosion degree index is positively correlated with the soil erosion degree of cultivated land.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0013] First: The monitoring of soil erosion degree in the present invention is only based on satellite remote sensing data, reducing the number of other input quantities and avoiding the time and space limitations of ground observation methods;

[0014] Second: It reduces the dependence on artificial experience, algorithms, and databases, improves work efficiency, can be widely applied to the dynamic monitoring of cultivated land in black soil areas on a large scale and long time series, and accurately obtains the change process of the erosion degree of cultivated land;

[0015] Third: The Erosion Severity Index (ESI) can not only qualitatively divide the soil erosion intensity but also quantitatively analyze it. The larger the ESI value, the more severe the soil erosion intensity. Description of the Drawings

[0016] Figure 1 is the flowchart of the method of the present invention;

[0017] Figure 2 is the specific framework diagram of the method of the present invention;

[0018] Figure 3 is the Sentinel-2 true color image of the whole area of County H on May 23, 2023, in the embodiment of the present invention;

[0019] Figure 4 is the Sentinel-2 true color image of the cultivated land area of County H on May 23, 2023, in the embodiment of the present invention;

[0020] Figure 5It is the numerical map of the cultivated land soil erosion degree in County H of the embodiments of the present invention;

[0021] Figure 6 It is the classification map of the cultivated land soil erosion degree in County H of the embodiments of the present invention. Specific implementation manners

[0022] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0023] Embodiment

[0024] Please refer to Figure 1 , a method for remotely sensing extraction of the cultivated land soil erosion degree in a black soil area in the figure, includes the following steps: Step S1, obtain the cultivated land range data, and collect the vector data of the cultivated land range in the research area; Step S2, select the remote sensing image, and perform image preprocessing such as radiometric correction, atmospheric correction, georegistration, and cultivated land range masking extraction; Step S3, calculate the soil erosion degree index, and calculate the relevant bands of the remote sensing image through professional software; Step S4, classify the soil erosion degree, and classify the soil erosion degree index value into no erosion, slight erosion, moderate erosion, and severe erosion according to the ground survey data.

[0025] In this embodiment, a scene of Sentinel-2 is used as the example data, which is provided free of charge by the European Space Agency (ESA) (website: https: / / scihub.copernicus.eu / ), completely covers County H, the spatial resolution of the relevant bands of Sentinel-2 is 10-20m, the time resolution is 3-5 days, and the acquisition time is May 18, 2023.

[0026] Figure 2 It is the specific framework diagram of the method for remotely sensing extraction of the cultivated land soil erosion degree in a black soil area, including the following content.

[0027] Step S1, obtain the vector data of the cultivated land range in County H, and select the Sentinel-2 satellite remote sensing images in the bare soil period, without cloud cover, and with less straw cover. There are six scenes of images in County H that meet the conditions in May 2023. Figure 3 Taking the Sentinel-2 satellite remote sensing image on May 18, 2023 as an example to illustrate the implementation process;

[0028] Step S2, complete the preprocessing of Sentinel-2 remote sensing images, including radiometric correction, atmospheric correction, and georegistration. Using the masking extraction tool in ArcMap, mask and extract Figure 3 using the vector data of the cultivated land area in County H, and the result is as Figure 4 .

[0029] Step S3, select ArcToolbox > Spatial Analyst Tools > Map Algebra > Raster Calculator in the menu bar to open the Raster Calculator window. Enter the required formula (R / B) / (SWIR1 / NIR) in the expression box of the Raster Calculator. The finally calculated ESI result is as Figure 5 , and the larger the value, the greater the erosion degree.

[0030] Step S4, combine the ground survey data to classify the soil erosion degree. Conduct a fitting analysis on the measured organic matter values and ESI values collected in County H. The R2 is 0.75 and the RMSE is 0.55. Based on the classification of organic matter grades, an erosion degree classification model is established: ESI value < 0.8 indicates no erosion; ESI value in the range of 0.8 - 0.92 indicates slight erosion; ESI value in the range of 0.92 - 1.09 indicates moderate erosion; ESI value > 1.09 indicates severe erosion.

[0031] Based on the accuracy verification results of the remote sensing extraction method for the cultivated land soil erosion degree in the black soil area in County H, it shows that the extraction method has high reliability and can effectively extract the information on the cultivated land soil erosion degree in the black soil area. The specific classification results are as Figure 6 shown.

[0032] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device.

[0033] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A remote sensing extraction method for soil erosion degree of cultivated land in black soil area, characterized in that: The steps include: Step S1, obtaining cultivated land range data and collecting vector data of cultivated land range in the study area; Step S2, selecting remote sensing images, and performing image preprocessing such as radiation correction, atmospheric correction, geo-registration, and farmland range mask extraction; Step S3, calculating the soil erosion degree index, and calculating the relevant bands of the remote sensing image through professional software; Step S4, soil erosion degree classification, based on the ground survey data, the soil erosion degree index value is classified into no erosion, slight erosion, moderate erosion, and severe erosion.

2. The remote sensing extraction method for soil erosion degree of cultivated land in black soil area according to claim 1 is characterized in that: The step S2 selects a remote sensing image in the bare soil period, without cloud cover, with less straw cover, and having a red band, a blue band, a near infrared band, and a short-wave infrared band.

3. The remote sensing extraction method for soil erosion degree of cultivated land in black soil area according to claim 2 is characterized in that: The soil erosion degree index constructed in step S3, and the soil erosion degree index calculation process is (R / B) / (SWIR1 / NIR), R is the red band, B is the blue band, SWIR1 is the short-wave infrared band, and NIR is the near infrared band.

4. The remote sensing extraction method for soil erosion degree of cultivated land in black soil area according to claim 3 is characterized in that: The step S4 analyzes the relationship between the field monitoring data and the soil erosion degree index, and qualitatively divides the degree of soil erosion of cultivated land based on the existing threshold of the field monitoring data.

5. The remote sensing extraction method for soil erosion degree of cultivated land in black soil area according to claim 4 is characterized in that: The soil erosion degree index is positively correlated with the degree of soil erosion on cultivated land.

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