CN112711793A - Mountain cutting construction identification method and device - Google Patents
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Abstract
The invention discloses a mountain cutting construction identification method and a mountain cutting construction identification device, wherein the method comprises the following steps: carrying out gradient analysis based on the digital elevation model to generate a gradient map; determining a mountain area monitoring range according to the gradient map; extracting a mountain shadow area based on a remote sensing image of a mountain; acquiring geographical national conditions ground surface coverage data, and determining a newly added artificial facility area in the mountain area monitoring range according to the geographical national conditions ground surface coverage data; determining the intersection part of the newly added artificial facility area and the mountain shadow area as a mountain cutting construction target area; by utilizing the digital elevation model, the remote sensing image and the geographic national conditions earth surface coverage data, mountain cutting construction for changing a mountain structure can be rapidly and accurately identified so as to timely stop, avoid inducing geological disasters such as landslide and debris flow to a certain extent, and guarantee the life and property safety of people.
Description
Technical Field
The invention relates to the technical field of information processing, in particular to a mountain cutting construction identification method and device.
Background
The mountain is an important natural resource, and mountain cutting construction damages mountain ground surface coverage on one hand, and often changes mountain form structure on the other hand, so that geological disasters such as landslide and debris flow are easily induced in rainy season, and the life and property safety of people is damaged.
The urbanization process of China is faster and faster, the desire of people to improve living conditions is more and more urgent, ecological environment damage and geological disasters occur in the process, and particularly mountain cutting construction threatening the life and property safety of people is urgently needed to be found and stopped in time. At present, the information of the mountain cutting area is extracted from the remote sensing image by adopting the characteristics of normalized vegetation index, normalized water body index, maximum image brightness and spectrum differentiation and the like, but the mountain cutting construction aiming at changing the mountain structure cannot be identified by using an object-oriented decision tree classification method.
Disclosure of Invention
The invention provides a mountain cutting construction identification method and device, which can effectively and timely identify mountain cutting construction with a changed mountain structure.
A mountain cutting construction identification method comprises the following steps:
carrying out gradient analysis based on the digital elevation model to generate a gradient map;
determining a mountain area monitoring range according to the gradient map;
extracting a mountain shadow area based on a remote sensing image of a mountain;
acquiring geographical national conditions ground surface coverage data, and determining a newly added artificial facility area in the mountain area monitoring range according to the geographical national conditions ground surface coverage data;
and determining the intersection part of the newly added artificial facility area and the mountain shadow area as a mountain cutting construction target area.
Further, performing grade analysis based on the digital elevation model to generate a grade map, comprising:
converting the coordinate system of the digital elevation model into a projection coordinate system;
and calculating the average gradient value of grid points around each grid point in the digital elevation model to form a gradient map.
Further, according to the gradient map, determining a mountain area monitoring range comprises:
and searching a region with the average gradient value larger than a preset gradient value in the gradient map, and determining that the region is a mountain monitoring range.
Further, based on the remote sensing image of the mountain, extracting a mountain shadow area, including:
and carrying out gray level conversion on the remote sensing image of the mountain and adjusting the contrast, and selecting a pixel with an RGB value of 0 as a mountain shadow area.
Further, collecting geographic national conditions ground surface coverage data, and determining a newly added artificial facility area in the mountain area monitoring range according to the geographic national conditions ground surface coverage data, wherein the method comprises the following steps:
collecting current geographical national conditions ground surface coverage data and historical geographical national conditions ground surface coverage data in a mountain area monitoring range;
extracting current artificial facility data from the current geographical national conditions ground surface coverage data, and extracting historical artificial facility data from the historical geographical national conditions ground surface coverage data;
overlapping the current artificial facility data and the historical artificial facility data;
and deleting the shared part of the current artificial facility data and the historical artificial facility data, and taking the rest part as a newly added artificial facility area.
Further, after determining that an artificial facility area is newly added in the mountain area monitoring range, the method further includes:
extracting historical land vegetation coverage areas from the historical geographic national conditions land coverage data;
and superposing the newly added artificial facility area and the historical earth surface vegetation coverage area, and calculating the area of the superposed part.
Further, the historical geographical national condition ground coverage data comprises type information of a historical ground vegetation coverage area, and the current geographical national condition ground coverage data comprises current artificial facility type information;
after the area of the overlapped part is calculated, the method further comprises the following steps:
and correlating the calculated area of the overlapped part, the type information of the historical earth surface vegetation coverage area and the current artificial facility type information to obtain earth surface change information.
A mountain cutting construction recognition device comprising:
the gradient analysis module is used for carrying out gradient analysis based on the digital elevation model to generate a gradient map;
the monitoring range determining module is used for determining a mountain area monitoring range according to the gradient map;
the extraction module is used for extracting a mountain shadow region based on the remote sensing image of the mountain;
the newly-added artificial facility area determining module is used for acquiring geographical national conditions ground surface coverage data and determining a newly-added artificial facility area in the mountain area monitoring range according to the geographical national conditions ground surface coverage data;
and the target area determining module is used for determining the intersection part of the newly added artificial facility area and the mountain shadow area as a mountain cutting construction target area.
Further, the gradient analysis module is further configured to convert the coordinate system of the digital elevation model into a projection coordinate system; calculating the average gradient value of grid points around each grid point in the digital elevation model to form a gradient map;
the monitoring range determining module is further used for searching a region with the average gradient value larger than a preset gradient value in the gradient map and determining that the region is a mountain monitoring range.
Furthermore, the newly-added artificial facility area determining module is also used for acquiring current geographical national conditions ground surface coverage data and historical geographical national conditions ground surface coverage data in the mountain area monitoring range; extracting current artificial facility data from the current geographical national conditions ground surface coverage data, and extracting historical artificial facility data from the historical geographical national conditions ground surface coverage data; overlapping the current artificial facility data and the historical artificial facility data; and deleting the shared part of the current artificial facility data and the historical artificial facility data, and taking the rest part as a newly added artificial facility area.
According to the mountain cutting construction identification method and device, the digital elevation model, the remote sensing image and the geographic national conditions ground surface coverage data are utilized, the mountain cutting construction for changing the mountain body structure can be rapidly and accurately identified, so that the mountain cutting construction can be stopped in time, geological disasters such as landslide and debris flow are avoided to a certain extent, and the life and property safety of people is guaranteed.
Drawings
Fig. 1 is a flowchart of an embodiment of a mountain cutting construction identification method provided by the present invention.
Fig. 2 is a flowchart of an embodiment of a method for determining a newly added artificial facility area in the mountain cutting construction identification method provided by the present invention.
Fig. 3 is a schematic diagram of an application scenario of a pattern spot covered by a historical artificial facility in the mountain-cutting construction identification method provided by the present invention.
Fig. 4 is a schematic diagram of an application scenario of a pattern spot covered by a current artificial facility in the mountain-cutting construction identification method provided by the present invention.
Fig. 5 is a schematic diagram of an application scenario in which a pattern spot covered by a current artificial facility and a pattern spot covered by a historical artificial facility are superimposed in the mountain-cutting construction identification method provided by the present invention.
Fig. 6 is a schematic diagram of an application scenario of a pattern spot of a newly added artificial facility area in the mountain-cutting construction identification method provided by the present invention.
Fig. 7 is a schematic view of another application scenario of a newly added artificial facility area in the mountain-cutting construction identification method provided by the present invention.
Fig. 8 is a schematic diagram of an application scenario of a historic land vegetation coverage area in the mountain cutting construction identification method provided by the invention.
Fig. 9 is a schematic diagram of an application scenario in which a newly added artificial facility area and a historical land vegetation coverage area are superimposed in the mountain cutting construction identification method provided by the invention.
Fig. 10 is a schematic view of an application scenario of an overlapping portion of a newly added artificial facility area and a historical land vegetation coverage area in the mountain cutting construction identification method provided by the invention.
Fig. 11 is a schematic structural diagram of an embodiment of the mountain cutting construction recognition device provided in the present invention.
Detailed Description
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
Referring to fig. 1, in some embodiments, there is provided a mountain cutting construction identification method, including:
s1, performing gradient analysis based on the digital elevation model to generate a gradient map;
s2, determining a mountain area monitoring range according to the gradient map;
s3, extracting a mountain shadow area based on the remote sensing image of the mountain;
s4, collecting geographical national conditions ground surface coverage data, and determining a newly added artificial facility area in the mountain area monitoring range according to the geographical national conditions ground surface coverage data;
and S5, determining the intersection part of the newly added artificial facility area and the mountain shadow area as a mountain cutting construction target area.
Specifically, in step S1, the coordinate system of the Digital Elevation Model (DEM) is required to be a projection coordinate system, and if the coordinate system of the Digital Elevation Model (DEM) is not the projection coordinate system, the coordinate system of the digital elevation model is converted into the projection coordinate system; and then calculating the average gradient value of grid points around each grid point in the digital elevation model to form a gradient map.
The method for determining the gradient map is specifically described below by using a specific application scenario.
Table 1 shows an example of data of nine grid points of the digital elevation model, where a grid point with a row number of 2 and a column number of 2 has slope values of 35, 63, 0, 63, 72, 65, 79, and 71 respectively, and the average slope value of the grid point is (35 +63+0+72+71+79+65+ 63)/8 =55.96 degrees. The same operation is performed for each grid point, and a slope map is obtained.
TABLE 1
Further, in step S2, determining a mountain area monitoring range according to the gradient map includes:
and searching a region with the average gradient value larger than a preset gradient value in the gradient map, and determining that the region is a mountain monitoring range.
In some embodiments, the area with the preset gradient value of 7 degrees, i.e., greater than 7 degrees, is determined as the mountain area monitoring range.
Further, in step S3, the extracting a mountain shadow region based on the remote sensing image of the mountain includes:
and carrying out gray level conversion on the remote sensing image of the mountain and adjusting the contrast, and selecting a pixel with an RGB value of 0 as a mountain shadow area.
Specifically, the remote sensing image of the mountain is subjected to gray level conversion, the contrast is adjusted to 100, and a pixel with an RGB value of 0 is selected as a mountain shadow area, that is, a black area is selected as the mountain shadow area.
Further, referring to fig. 2, in step S4, acquiring geographic national conditions ground coverage data, and determining, according to the geographic national conditions ground coverage data, a newly added artificial facility area in the mountain area monitoring range includes:
s41, collecting current geographical national conditions ground surface coverage data and historical geographical national conditions ground surface coverage data in a mountain area monitoring range;
s42, extracting current artificial facility data from the current geographical national conditions ground surface coverage data, and extracting historical artificial facility data from the historical geographical national conditions ground surface coverage data;
s43, overlapping the current artificial facility data and the historical artificial facility data;
and S44, deleting the shared part of the current artificial facility data and the historical artificial facility data, and taking the rest part as a newly added artificial facility area.
Specifically, in step S41, the current geographical national conditions surface coverage data and the historical geographical national conditions surface coverage data are geographical national conditions surface coverage data of two different periods, and include artificial facility data, artificial facility type information, surface vegetation coverage area type information, and the like.
Further, in step S42, extracting current artificial facility data from the current geographical national conditions coverage data, and extracting historical artificial facility data from the historical geographical national conditions coverage data; the current artifact data includes a map blob of current artifact coverage and the historical artifact data includes a map blob of historical artifact coverage.
Further, in step S43, the current artificial facility data and the historical artificial facility data are superimposed, that is, the patches covered by the current artificial facility and the patches covered by the historical artificial facility are superimposed.
Further, in step S44, a part of the current artificial facility data that is common to the historical artificial facility data, that is, an overlapping part of the current artificial facility coverage patch and the historical artificial facility coverage patch, is deleted, and the remaining part is a new artificial facility region.
The determination method of the newly added artificial facility area is further explained by specific application scenarios.
Fig. 3 is a graph spot covered by a historical artificial facility, fig. 4 is a graph spot covered by a current artificial facility, fig. 5 is a schematic diagram of overlapping of the graph spot covered by the current artificial facility and the graph spot covered by the historical artificial facility, and fig. 6 is a graph spot of a newly added artificial facility region, which is a portion where an overlapping portion of the graph spot covered by the current artificial facility and the graph spot covered by the historical artificial facility is deleted.
Further, in step S5, the intersection of the new artificial facility region and the mountain shadow region is determined as a mountain cutting construction target region, that is, the new artificial facility is subjected to mountain cutting construction.
Further, after step S4, the method further includes:
extracting historical land vegetation coverage areas from the historical geographic national conditions land coverage data;
and superposing the newly added artificial facility area and the historical earth surface vegetation coverage area, and calculating the area of the superposed part.
The historical geographical national condition ground surface coverage data comprises type information of a historical ground surface vegetation coverage area, and the current geographical national condition ground surface coverage data comprises current artificial facility type information;
after the area of the overlapped part is calculated, the method further comprises the following steps:
and correlating the calculated area of the overlapped part, the type information of the historical earth surface vegetation coverage area and the current artificial facility type information to obtain earth surface change information.
Specifically, the overlapped part of the newly added artificial facility region and the historical earth surface vegetation coverage region after superposition is a part of artificial facilities changed from vegetation coverage, and the earth surface change information can be obtained by associating the area of the overlapped part with the type information of the historical earth surface vegetation coverage region and the type information of the current artificial facilities.
The type information of the land vegetation coverage area includes woodland, grassland, paddy field, dry land, etc., and the type information of the artificial facilities includes general houses, villas, etc.
The following is further described by specific application scenarios.
The newly added artificial facility area is shown in fig. 7, the historical land vegetation coverage area is shown in fig. 8, the schematic diagram of the superposition of the two areas is shown in fig. 9, and the schematic diagram of the superposition part is shown in fig. 10.
By associating the area of each repeated part with the type information of the historic land vegetation coverage area and the current artificial facility type information, an information table as shown in table 2 can be obtained:
TABLE 2
The parts with the same type before change and the same type after change are summarized, for example, the parts with ID 1 and ID 5 are all forest lands before change, and are all ordinary houses after change, and the summarized parts are shown in Table 3:
TABLE 3
According to the mountain cutting construction identification method provided by the embodiment, the mountain cutting construction for changing the mountain body structure can be quickly and accurately identified by using the digital elevation model, the remote sensing image and the geographic national conditions ground surface coverage data, so that the mountain cutting construction can be stopped timely, geological disasters such as landslide and debris flow can be avoided to a certain extent, and the life and property safety of people can be ensured.
Referring to fig. 11, in some embodiments, there is provided a mountain cutting construction recognition apparatus including:
a gradient analysis module 201, configured to perform gradient analysis based on the digital elevation model to generate a gradient map;
the monitoring range determining module 202 is used for determining a mountain monitoring range according to the gradient map;
the extraction module 203 is used for extracting a mountain shadow region based on the remote sensing image of the mountain;
a newly-added artificial facility area determining module 204, configured to collect geographic national conditions ground surface coverage data, and determine, according to the geographic national conditions ground surface coverage data, a newly-added artificial facility area within the mountain area monitoring range;
and a target area determining module 205, configured to determine an intersection of the newly added artificial facility area and the mountain shadow area as a mountain cutting construction target area.
Further, the gradient analysis module 201 is further configured to convert the coordinate system of the digital elevation model into a projection coordinate system; calculating the average gradient value of eight grid points around each grid point in the digital elevation model to form a gradient map;
the monitoring range determination module 202 is further configured to search a region in the slope map, where the average slope value is greater than a preset slope value, and determine that the region is a mountain monitoring range.
Further, the extraction module 203 is further configured to perform gray scale conversion on the remote sensing image of the mountain and adjust contrast, and select a pixel with an RGB value of 0 as a mountain shadow area.
Further, the newly added artificial facility area determination module 204 is further configured to acquire current geographical national conditions ground coverage data and historical geographical national conditions ground coverage data within the mountain area monitoring range; extracting current artificial facility data from the current geographical national conditions ground surface coverage data, and extracting historical artificial facility data from the historical geographical national conditions ground surface coverage data; overlapping the current artificial facility data and the historical artificial facility data; and deleting the shared part of the current artificial facility data and the historical artificial facility data, and taking the rest part as a newly added artificial facility area.
Further, the device also comprises a change information statistic module 206 for extracting historical land vegetation coverage areas from the historical geographic national condition land coverage data; superposing the newly added artificial facility area and the historical earth surface vegetation coverage area, and calculating the area of a superposed part; and correlating the calculated area of the overlapped part, the type information of the historical earth surface vegetation coverage area and the current artificial facility type information to obtain earth surface change information.
The mountain cutting construction recognition device provided by the embodiment utilizes the digital elevation model, the remote sensing image and the geographic national conditions earth surface coverage data, can rapidly and accurately recognize the mountain cutting construction for changing the mountain structure, so as to timely stop, avoid inducing geological disasters such as landslide and debris flow to a certain extent, and ensure the life and property safety of people.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention. It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A mountain cutting construction identification method is characterized by comprising the following steps:
carrying out gradient analysis based on the digital elevation model to generate a gradient map;
determining a mountain area monitoring range according to the gradient map;
extracting a mountain shadow area based on a remote sensing image of a mountain;
acquiring geographical national conditions ground surface coverage data, and determining a newly added artificial facility area in the mountain area monitoring range according to the geographical national conditions ground surface coverage data;
and determining the intersection part of the newly added artificial facility area and the mountain shadow area as a mountain cutting construction target area.
2. The method of claim 1, wherein performing a grade analysis based on the digital elevation model to generate a grade map comprises:
converting the coordinate system of the digital elevation model into a projection coordinate system;
and calculating the average gradient value of grid points around each grid point in the digital elevation model to form a gradient map.
3. The method of claim 2, wherein determining a mountain monitoring range from the grade map comprises:
and searching a region with the average gradient value larger than a preset gradient value in the gradient map, and determining that the region is a mountain monitoring range.
4. The method of claim 1, wherein extracting the mountain shadow region based on the remote sensing image of the mountain comprises:
and carrying out gray level conversion on the remote sensing image of the mountain and adjusting the contrast, and selecting a pixel with an RGB value of 0 as a mountain shadow area.
5. The method as claimed in claim 1, wherein the step of collecting geographic national conditions ground surface coverage data and determining the newly added artificial facility area in the mountain area monitoring range according to the geographic national conditions ground surface coverage data comprises:
collecting current geographical national conditions ground surface coverage data and historical geographical national conditions ground surface coverage data in a mountain area monitoring range;
extracting current artificial facility data from the current geographical national conditions ground surface coverage data, and extracting historical artificial facility data from the historical geographical national conditions ground surface coverage data;
overlapping the current artificial facility data and the historical artificial facility data;
and deleting the shared part of the current artificial facility data and the historical artificial facility data, and taking the rest part as a newly added artificial facility area.
6. The method as claimed in claim 5, further comprising, after determining the area of the additional artificial facilities in the mountain area monitoring range:
extracting historical land vegetation coverage areas from the historical geographic national conditions land coverage data;
and superposing the newly added artificial facility area and the historical earth surface vegetation coverage area, and calculating the area of the superposed part.
7. The method of claim 6, wherein the historical geographic national landscape coverage data includes type information for historical landscape vegetation coverage areas, and the current geographic national landscape coverage data includes current artificial facility type information;
after the area of the overlapped part is calculated, the method further comprises the following steps:
and correlating the calculated area of the overlapped part, the type information of the historical earth surface vegetation coverage area and the current artificial facility type information to obtain earth surface change information.
8. A mountain cutting construction recognition device, comprising:
the gradient analysis module is used for carrying out gradient analysis based on the digital elevation model to generate a gradient map;
the monitoring range determining module is used for determining a mountain area monitoring range according to the gradient map;
the extraction module is used for extracting a mountain shadow region based on the remote sensing image of the mountain;
the newly-added artificial facility area determining module is used for acquiring geographical national conditions ground surface coverage data and determining a newly-added artificial facility area in the mountain area monitoring range according to the geographical national conditions ground surface coverage data;
and the target area determining module is used for determining the intersection part of the newly added artificial facility area and the mountain shadow area as a mountain cutting construction target area.
9. The apparatus of claim 8, wherein the slope analysis module is further configured to convert the coordinate system of the digital elevation model to a projection coordinate system; calculating the average gradient value of grid points around each grid point in the digital elevation model to form a gradient map;
the monitoring range determining module is further used for searching a region with the average gradient value larger than a preset gradient value in the gradient map and determining that the region is a mountain monitoring range.
10. The device according to claim 8, wherein the newly added artificial facility region determining module is further configured to collect current geographical national conditions and surface coverage data and historical geographical national conditions and surface coverage data within the mountain area monitoring range; extracting current artificial facility data from the current geographical national conditions ground surface coverage data, and extracting historical artificial facility data from the historical geographical national conditions ground surface coverage data; overlapping the current artificial facility data and the historical artificial facility data; and deleting the shared part of the current artificial facility data and the historical artificial facility data, and taking the rest part as a newly added artificial facility area.
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| CN108985281A (en) * | 2018-09-19 | 2018-12-11 | 中国科学院东北地理与农业生态研究所 | Method and system are distinguished in a kind of construction land based on timing remote sensing image and farmland |
| CN110189043A (en) * | 2019-06-04 | 2019-08-30 | 中国地质大学（北京） | It is a kind of based on high score satellite remote sensing date using land resource analysis system |
| CN111142119A (en) * | 2020-01-10 | 2020-05-12 | 中国地质大学（北京） | Mine geological disaster dynamic identification and monitoring method based on multi-source remote sensing data |
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| CN113919185A (en) * | 2021-12-13 | 2022-01-11 | 中国测绘科学研究院 | Method and device for measuring landform and landform conditions |
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