阅读说明：本技术 一种确定滑坡位移与库区水位波动关系的方法 (Method for determining relation between landslide displacement and reservoir area water level fluctuation ) 是由 曾润强 赵淑芬 张宏雪 张毅 孟兴民 张宗林 陈冠 于 2020-12-21 设计创作，主要内容包括：本发明属于遥感测绘领域,具体涉及一种确定滑坡形变与库区水位波动关系的方法,本方法通过采用SBAS-InSAR方法对研究区处理,计算得到滑坡位移数据；并利用多元遥感数据提取水位信息,获取具体滑坡周边水位数据；最后通过建模分析水位波动条件下库区滑坡位移的变形规率。本发明方法解决了现有相关研究中运用单点监测水位代替特定滑坡周边水位的问题,从新视角分析库水位波动条件下库区滑坡形变规律,为区域监测预警提供新思路。(The invention belongs to the field of remote sensing mapping, and particularly relates to a method for determining a relation between landslide deformation and reservoir area water level fluctuation, wherein the method comprises the steps of processing a research area by adopting an SBAS-InSAR method, and calculating to obtain landslide displacement data; extracting water level information by using the multivariate remote sensing data to obtain water level data around the concrete landslide; and finally, analyzing the deformation regulation of the displacement of the landslide in the reservoir area under the condition of water level fluctuation through modeling. The method solves the problem that the water level around the specific landslide is replaced by the single-point monitoring water level in the existing related research, analyzes the landslide deformation rule of the reservoir area under the condition of reservoir water level fluctuation from a new perspective, and provides a new idea for regional monitoring and early warning.)

1. A method for determining the relation between landslide displacement and reservoir water level fluctuation is characterized in that: processing the research area by adopting an SBAS-InSAR method, and calculating to obtain the accumulated displacement of the landslide; extracting water level information by using the multivariate remote sensing data to obtain water level fluctuation data around the concrete landslide; and finally, analyzing the deformation regulation rate of the accumulated displacement of the reservoir landslide under the condition of water level fluctuation through modeling.

2. The method of claim 1, wherein the step of determining the relationship between landslide displacement and reservoir water level fluctuation comprises the steps of: comprises the following steps

S1, obtaining an average displacement rate of a coverage research area by using an SABS-InSAR technology, drawing a displacement rate graph, delineating a deformation area, and calculating the accumulated displacement of a landslide;

s2, selecting multi-element remote sensing data covering a research area;

s3, calculating a normalized difference water body index to obtain a water body distribution map, and processing the water body distribution map to obtain water body boundaries in different periods;

s4, modeling by using a DEM (digital elevation model), and overlapping the water body boundary and the DEM to obtain reservoir water bit data in different periods;

and S5, analyzing the deformation regulation rate of the accumulated displacement of the landslide in the reservoir area under the condition of water level fluctuation.

3. The method of claim 1, wherein the step of determining the relationship between landslide displacement and reservoir water level fluctuation comprises the steps of: the multivariate remote sensing data comprises Landsat8-OLI data and Sentinel-2 data.

4. A method of determining landslide displacement versus reservoir water level fluctuation as claimed in claim 3 wherein: the remote sensing image time of the multi-remote sensing data is 3-7 days earlier than that of the SAR image.

5. The method of claim 1, wherein the step of determining the relationship between landslide displacement and reservoir water level fluctuation comprises the steps of: and determining water body boundaries at different periods after the image gray values of the water body distribution map are subjected to threshold segmentation.

6. The method of claim 1, wherein the step of determining the relationship between landslide displacement and reservoir water level fluctuation comprises the steps of: the S4 specifically includes:

s401, obtaining DEM data and improving data precision in the water level calculation process;

s402, performing terrain shadow modeling by using a 3D analysis tool in ArcGIS, setting an azimuth angle and a solar height in parameter setting, checking a simulated shadow option, calculating a terrain shadow, performing reclassification on the terrain shadow, and representing a shadow area by an area with a value of 0 in a unit grid;

s403, overlapping the primarily obtained water body boundary with the shadow area, and removing the water body boundary extracted by mistake in the shadow area;

s404, overlapping the finally obtained water body boundary and the DEM to obtain water level data covering the whole reservoir area, and then performing mask extraction in the boundary range to obtain the water level data around a certain specific landslide.

7. The method of claim 1, wherein the step of determining the relationship between landslide displacement and reservoir water level fluctuation comprises the steps of: the water level fluctuation condition comprises a water level increasing stage and a water level decreasing stage, the water level increasing stage and the water level decreasing stage of the reservoir area are determined according to the water level change rule, daily displacement rates of landslides in corresponding time periods are respectively calculated, the daily displacement rates of the landslides in the water level increasing period and the water level decreasing period are compared, and the influence rule of the water level change on the landslide displacement is analyzed.

Technical Field

The invention belongs to the field of remote sensing mapping, and particularly relates to a method for determining a relation between landslide deformation and reservoir area water level fluctuation.

Background

Due to the shortage of energy and the requirement of environmental protection, many countries in the world pay attention to the construction of water conservancy and hydropower engineering. However, hydropower stations solve energy problems and change regional natural environmental conditions, which may bring new geological environmental problems, wherein reservoir bank slope stability is always one of the issues of great concern in hydropower engineering. The damage cases of Dam instability caused after the reservoir stores water are not sufficient, and thousands of people death and economic loss are caused by Dam instability damage or bank landslide caused by water storage of a Malpaset Dam, a Buffalo Creek Dam, a Vajoin reservoir, a pond rock-light reservoir, a stream Luo-crossing hydropower station and the like. The existing research shows that the fluctuation of the reservoir water level, such as the rapid drop of the water level, can reduce the stability of a slope body, not only increases the revival rate of an old landslide, but also induces a new landslide, so that the reservoir becomes a main geological disaster prone area and a high-risk area.

The traditional research on influence of reservoir water level fluctuation on landslide deformation focuses on single-point monitoring, regional analysis is rarely carried out by using an integrated remote sensing means, at present, SAR images and optical remote sensing images can be used for extracting water body information, the SAR images have the characteristics of being all-weather, free of cloud and mist influence on imaging and the like, a time sequence identical to InSAR deformation can be obtained, however, mountain shadow, aeolian sand and the like show low backward scatterer coefficients identical to those of a water body, and the accuracy of water body extraction is greatly influenced by interference information. Optical remote sensing images have been widely applied to flood disaster monitoring, wetland water body boundary extraction and other aspects, but previous research mainly focuses on identifying water body information or extracting large-range planar water bodies, and the specific water level of a certain area is not deeply researched.

Disclosure of Invention

Aiming at the problems in the background art, the invention provides a method for determining the relation between landslide deformation and reservoir area water level fluctuation, which utilizes multivariate remote sensing data to extract water level information, obtains water level data around a specific landslide and specifically analyzes the influence of water level change on landslide deformation.

In order to achieve the purpose, the technical scheme adopted by the invention is as follows:

a method for determining the relation between landslide displacement and reservoir area water level fluctuation comprises the steps of processing a research area by adopting an SBAS-InSAR method, and calculating to obtain the accumulated displacement of the landslide; extracting water level information by using the multivariate remote sensing data to obtain water level fluctuation data around the concrete landslide; and finally, analyzing the deformation regulation rate of the accumulated displacement of the reservoir landslide under the condition of water level fluctuation through modeling.

Comprises the following steps

S1, obtaining an average displacement rate of a coverage research area by using an SABS-InSAR technology, drawing a displacement rate graph, delineating a deformation area, and calculating the accumulated displacement of a landslide;

s2, selecting multi-element remote sensing data covering a research area;

s3, calculating a normalized difference water body index to obtain a water body distribution map, and processing the water body distribution map to obtain water body boundaries in different periods;

s4, modeling by using a DEM (digital elevation model), and overlapping the water body boundary and the DEM to obtain reservoir water bit data in different periods;

and S5, analyzing the deformation regulation rate of the accumulated displacement of the landslide in the reservoir area under the condition of water level fluctuation.

The multivariate remote sensing data comprises Landsat8-OLI data and Sentinel-2 data.

The remote sensing image time of the multi-remote sensing data is 3-7 days earlier than that of the SAR image.

And determining water body boundaries at different periods after the image gray values of the water body distribution map are subjected to threshold segmentation.

The S4 specifically includes:

s401, obtaining DEM data and improving data precision in the water level calculation process;

s402, performing terrain shadow modeling by using a 3D analysis tool in ArcGIS, setting an azimuth angle and a solar height in parameter setting, checking a simulated shadow option, calculating a terrain shadow, performing reclassification on the terrain shadow, and representing a shadow area by an area with a value of 0 in a unit grid;

s403, overlapping the primarily obtained water body boundary with the shadow area, and removing the water body boundary extracted by mistake in the shadow area;

s404, overlapping the finally obtained water body boundary and the DEM to obtain water level data covering the whole reservoir area, and then performing mask extraction in a smaller boundary range to obtain water level data around a certain specific landslide.

The water level fluctuation condition comprises a water level increasing stage and a water level decreasing stage, the water level increasing stage and the water level decreasing stage of the reservoir area are determined according to the water level change rule, daily displacement rates of landslides in corresponding time periods are respectively calculated, and the daily displacement rates of the landslides in the water level increasing period and the water level decreasing period are compared, so that the influence rule of the water level change on the landslide displacement is analyzed.

The invention has the beneficial effects that: according to the method, the normalized water body index is calculated through Landsat8-OLI and Sentinel-2 images, the mountain shadow extracted by mistake is removed through DEM modeling, the water body boundary is obtained, water level data around a specific landslide is further obtained, and a large-range planar data extraction method in most researches is improved. And secondly, obtaining the landslide deformation rate of the research area by using an SBAS-InSAR method. The method improves the speed of acquiring the landslide displacement data and the water level data, overcomes the problems of long time consumption, small monitoring range, high cost and the like of the conventional monitoring method for acquiring the data, analyzes the landslide deformation rule of the reservoir area under the condition of reservoir water level fluctuation from a new visual angle, and provides a new idea for landslide monitoring and early warning.

Drawings

FIG. 1 is a flow chart of the method of the present invention;

FIG. 2 is a binarized graph of NDWI calculated by an embodiment;

FIG. 3 is an embodiment NDWI threshold segmentation graph

FIG. 4 illustrates reservoir water boundaries under different threshold segmentation ranges according to an embodiment;

FIG. 5 is a shadow removal map for DEM modeling of an embodiment

FIG. 6 is an overlay of the water level boundary and DEM of the embodiment

FIG. 7 is a graph of cumulative landslide displacement for an embodiment;

FIG. 8 is a graph of typical landslide displacement versus water level change according to an embodiment

FIG. 9 shows the correlation between the stage of water level decrease and the displacement of the landslide according to the embodiment.

Detailed Description

The technical scheme of the invention is further explained by specific embodiments in the following with the accompanying drawings:

example 1:

as shown in fig. 1, a method for determining a relation between landslide deformation and reservoir water level fluctuation provided by an embodiment of the present invention includes the following steps:

two high resolution optical images were selected in this example, Landsat8-OLI image and Sentinel-2 image. And preprocessing the two images before calculating the normalized difference water body index. Firstly, cropping Landsat8-OLI data and Sentinel-2 data by using a vector boundary covering a study area, reducing workload and improving processing speed; two images need to be preprocessed before calculating the normalized water difference index (NDWI): landsat8-OLI image preprocessing is performed in ENVI software, mainly comprising radiometric calibration and atmospheric correction, Sentinel-2 image preprocessing is performed in SNAP software, firstly, original Sentinel-2 images are resampled to be identical in resolution, then Sen2cor plug-in is used for atmospheric correction, NDWI is calculated for the two preprocessed images, and the formula is as follows:

NDWI＝(Green-NIR)/(Green+NIR)

NDWI >0, NDWI <0, Green, and NIR are water, non-water, Green, and near-infrared.

Replacing a near infrared band of the Sentinel-2 data with a B8 band with similar Popp values, outputting the number of the normalized differential water body files obtained through calculation into a GeoTiff format, loading an NDWI image obtained through Landsat8-OLI data and the Sentinel-2 data into ENVI software for threshold segmentation, finding an interest area (Region of interest) tool in an ENVI toolbar, selecting a threshold window, adding files to be subjected to threshold segmentation, popping up a selected threshold parameter window, and selecting the minimum value and the maximum value of the threshold interval. The obtained RIO region is output in a Shpfile format, so that the RIO region can be conveniently processed in ArcGIS for the next step. The method comprises the steps of simulating mountain shadow by using DEM data of 7.73 meters, calculating the mountain shadow, modeling the terrain shadow by using a 3D analysis tool in ArcGIS, calculating a shadow area of an embodiment by setting an azimuth angle and a solar altitude, selecting a simulated shadow option, and reclassifying obtained results. The area in the cell grid assigned a value of 0 represents the shaded area. And overlapping the primarily obtained water body boundary with the DEM shadow area, and removing the water body boundary extracted by mistake in the shadow area. And overlapping the water body boundary without the shadow with the DEM, and performing mask extraction to obtain water level data of the reservoir area at different periods. And then, carrying out mask extraction on the obtained water body grid data of the whole reservoir area within a boundary range of 2km to obtain water level data around a specific landslide, constructing a grid attribute table for the water level data, obtaining an attribute value of each grid pixel, and specifically calculating the average water level around the specific landslide.

And processing the research area by using an SBAS-InSAR method to obtain the annual average deformation rate of the area, determining the deformation area, and calculating the accumulated displacement of the landslide. Firstly, basic data preparation is carried out, and high-precision DEM data covering a research area, a high-resolution Sentinel-1A image and high-precision orbit data are downloaded. Cutting data in SARscape to generate an interference pattern, removing a terrain phase, an atmospheric phase and a noise phase, performing phase unwrapping by adopting a 3D unwrapping method, performing track refining, re-leveling and other steps to obtain an embodiment displacement rate, loading an obtained time sequence displacement result to ArcGIS to determine a stable threshold according to an average value and a standard deviation of a coherent point target, obtaining an embodiment deformation rate distribution diagram by grading, and finally, defining a deformed landslide to obtain a displacement time sequence of a certain landslide.

Analyzing the change rule of the landslide displacement of the reservoir area under the condition of water level fluctuation: firstly, determining a reservoir water level increasing stage and a reservoir water level decreasing stage according to a water level change rule, respectively calculating daily displacement rates of landslides in corresponding time periods, and comparing the daily displacement rates of the landslides in the water level increasing and decreasing periods so as to analyze an influence rule of the water level change on the landslide displacement; then calculating the correlation between the water level change and the landslide displacement in the water level rising period and the water level falling period, wherein the value range of a correlation coefficient is (-1, +1), and when the correlation coefficient is less than 0, the correlation coefficient is called negative correlation; when the correlation coefficient is larger than 0, the positive correlation is called, and the larger the correlation coefficient R is, the more close the relationship between the two is.

It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.

Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.