CN114724029A - Remote sensing extraction method and system of mining goaf's influence on the surface - Google Patents

Abstract

The invention provides a remote sensing extraction method and a system for the influence of a goaf of a mining area on the earth's surface, wherein the method comprises the following steps: determining a region to be monitored of a mining area, and acquiring remote sensing data of the region; acquiring a normalized vegetation index mean value of a time sequence of a region to be monitored and a crop identification index based on remote sensing data, and confirming that the region to be monitored is a farmland region through a first preset condition based on the crop identification index and the normalized vegetation index mean value of the time sequence; acquiring a temperature vegetation drought index and crop nitrogen content of the farmland region, preliminarily determining the farmland region as a region influenced by the goaf through a second preset condition based on the temperature vegetation drought index and the crop nitrogen content, and further finally determining the farmland region as the region influenced by the goaf. According to the method, the remote sensing extraction of the earth surface can be performed aiming at the goaf of the mining area through the remote sensing image, so that whether the area corresponding to the remote sensing data is the area influenced by the goaf or not is judged, and the purpose of accurately identifying the crop extraction under the influence of the goaf is achieved.

Description

Remote sensing extraction method and system of mining goaf's influence on the surface

technical field

The invention relates to the technical fields of agriculture and remote sensing, in particular to a remote sensing extraction method and system for the influence of a goaf in a mining area on the surface.

Background technique

The goaf is a "hole" created by artificial excavation or natural geological movement under the surface. The existence of the goaf makes the safety production of the mine face great safety problems. Personnel and mechanical equipment may fall into the goaf and be affected. harm. Coal mine goaf: refers to the cavity or cavity left after the mining of underground coal or coal gangue is completed during the operation of the coal mine.

If the goaf in the mining area is not properly managed, it will lead to surface subsidence. The direct impact is that the houses on the gob are inclined, the water body on the gob is leaking, the road will also collapse due to subsidence, and the farmland will not be able to work on the surface due to the hollowing effect of the underground. A series of geological disasters can occur due to problems such as maintaining moisture, leading to droughts and, ultimately, reduced yields. Therefore, in accordance with national requirements, green mining is generally required, and mining and governance are generally required. However, the impact of goaf on farmland crops is obviously concealed, and it is not easy to be discovered, which has become a difficult point in the governance of goaf at present.

Therefore, how to use remote sensing images to extract the ground surface from the goaf in the mining area and determine whether the area corresponding to the remote sensing data is the area affected by the goaf is a technical problem that needs to be solved urgently.

SUMMARY OF THE INVENTION

The invention provides a remote sensing extraction method and system for the influence of a goaf in a mining area on the surface, so as to solve the defect that it is difficult to control the goaf in the prior art, and realize the remote sensing extraction of the surface of the goaf in the mining area through remote sensing images. , to judge whether the area corresponding to the remote sensing data is the area affected by the goaf.

The invention provides a remote sensing extraction method for the influence of a goaf in a mining area on the surface, comprising:

Determine the area to be monitored in the mining area, and obtain remote sensing data of the area to be monitored;

In the case of confirming that the to-be-monitored area is a crop sensitive area to precipitation, obtain the time-series normalized vegetation index mean value and crop identification index of the to-be-monitored area based on the remote sensing data, and based on the crop identification index and the mean value of the normalized vegetation index of the time series through the first preset condition to confirm that the area to be monitored is a farmland area;

Obtain the temperature vegetation drought index and crop nitrogen content of the farmland area, and based on the temperature vegetation drought index and the crop nitrogen content, the farmland area is preliminarily confirmed as an area affected by a goaf through a second preset condition.

According to a remote sensing extraction method for the influence of a goaf in a mining area on the surface provided by the present invention, the average value of the normalized vegetation index based on the crop identification index and the time series confirms that the to-be-monitored area is determined by a first preset condition. Farmland areas, including:

When the crop identification index is not less than the first preset threshold, and the mean value of the normalized vegetation index of the time series is not less than the second preset threshold, it is confirmed that the area to be monitored is a farmland area.

According to a remote sensing extraction method for the influence of a goaf in a mining area on the surface provided by the present invention, the farmland area is preliminarily confirmed as a goaf by a second preset condition based on the temperature, vegetation drought index and crop nitrogen content Affected areas include:

Under the condition that the temperature vegetation drought index is not less than the third preset threshold, and the nitrogen content of the crop is not greater than the fourth preset threshold, the farmland area is preliminarily confirmed as the area affected by the goaf.

According to a remote sensing extraction method for the influence of a goaf in a mining area on the surface provided by the present invention, when the temperature vegetation drought index is not less than a third preset threshold, and the nitrogen content of the crop is not greater than a fourth preset threshold Next, after the farmland area is preliminarily confirmed as the area affected by the goaf, the method further includes:

Obtaining the mean value of the normalized vegetation index and the crop growth period of the time series in the area that is initially confirmed to be affected by the goaf, and obtaining the mean value of the normalized vegetation index and the mean value of the growth period of the farmland in the mining area;

The difference between the mean value of the normalized vegetation index of the time series and the mean value of the normalized vegetation index of the farmland in the mining area in the area that is preliminarily confirmed to be affected by the goaf is not less than the fifth preset threshold, and the preliminary confirmation is If the crop growth cycle in the area affected by the goaf is not equal to the average growth cycle of the farmland in the mining area, the farmland area is finally confirmed as the area affected by the goaf.

According to a remote sensing extraction method for the impact of mined-out areas in mining areas on the surface provided by the present invention, the acquisition of the time-series normalized vegetation index mean value and crop identification index of the to-be-monitored area based on the remote sensing data includes:

Selecting target scene data from the scene data of the remote sensing data, and obtaining the normalized vegetation index of the target scene data and the mean value of the normalized vegetation index of the time series;

The crop identification index of the to-be-monitored area is obtained based on the normalized vegetation index of the target scene data, the mean value of the normalized vegetation index of the time series, and the scene data of the remote sensing image.

According to a remote sensing extraction method for the influence of a goaf in a mining area on the surface provided by the present invention, after determining the area to be monitored in the mining area and obtaining the remote sensing data of the area to be monitored, the method further includes:

Obtain the annual average precipitation of the area to be monitored and the precipitation in the crop planting season;

When the average annual precipitation is not greater than the sixth preset threshold, and the precipitation during the crop planting season is not greater than the seventh preset threshold, the to-be-monitored area is determined as a crop sensitive area to precipitation.

The present invention also provides a remote sensing extraction system for the influence of the goaf in the mining area on the surface, including:

The acquisition module is used to determine the area to be monitored in the mining area and obtain the remote sensing data of the area to be monitored;

The farmland area confirmation module is used to obtain, based on the remote sensing data, the normalized vegetation index mean value and the crop identification index of the time series of the to-be-monitored area under the condition that the to-be-monitored area is confirmed as a crop sensitive area to precipitation, and confirming that the area to be monitored is a farmland area through a first preset condition based on the crop identification index and the mean value of the normalized vegetation index of the time series;

The preliminary confirmation module is used to obtain the temperature vegetation drought index and the crop nitrogen content of the farmland area, and based on the temperature vegetation drought index and the crop nitrogen content, the farmland area is preliminarily confirmed as harvesting through the second preset condition. The area affected by the empty zone.

The present invention also provides an electronic device, comprising a memory, a processor and a computer program stored in the memory and running on the processor, when the processor executes the program, the goaf of any one of the above-mentioned mining areas is realized Remote sensing extraction methods of regional impacts on the surface.

The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements the remote sensing extraction method for the influence of a goaf in a mining area on the surface as described above.

The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements the remote sensing extraction method for the impact of a goaf in a mining area on the surface as described above.

The method and system for remote sensing extraction of the influence of mined-out areas in mining areas on the surface provided by the present invention, by determining the area to be monitored in the mining area, and obtaining the remote sensing data of the area to be monitored, based on the remote sensing data to obtain the normalized vegetation of the time series of the area to be monitored The average value of the index and the crop identification index, and based on the crop identification index and the mean value of the normalized vegetation index of the time series, the area to be monitored is confirmed as a farmland area through the first preset condition, and the temperature, vegetation drought index and crop nitrogen content of the farmland area are obtained, And based on the temperature vegetation drought index and crop nitrogen content, the farmland area is preliminarily confirmed as the area affected by the goaf through the second preset condition. The invention can use remote sensing images to extract the ground surface from the goaf in the mining area, so as to judge whether the area corresponding to the remote sensing data is the area affected by the goaf, and achieve the purpose of accurately identifying the crop extraction under the influence of the goaf.

Description of drawings

In order to explain the present invention or the technical solutions in the prior art more clearly, the following will briefly introduce the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are the For some embodiments of the invention, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without any creative effort.

Fig. 1 is one of the schematic flow charts of the remote sensing extraction method of the influence of mining goaf on the surface provided by the present invention;

Fig. 2 is the second schematic flow chart of the remote sensing extraction method of the influence of mining goaf on the surface provided by the present invention;

Fig. 3 is the structure schematic diagram of the remote sensing extraction system of the influence of the mining area goaf on the surface provided by the present invention;

FIG. 4 is a schematic structural diagram of an electronic device provided by the present invention.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention. , not all examples. 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.

The method and system for remote sensing extraction of the influence of the mined goaf on the surface of the present invention will be described below with reference to FIGS. 1 to 4 .

Referring to Fig. 1, the present invention provides a remote sensing extraction method for the impact of a mining goaf on the surface, comprising the following steps:

Step 110: Determine the area to be monitored in the mining area, and acquire remote sensing data of the area to be monitored.

Specifically, in this embodiment, the coordinates of the center point of the mining area are determined, and professional geographic information software is used to create a buffer area with a certain radius, and this buffer area is used as the area to be monitored. Among them, the areas covering the mining area are the main shaft, auxiliary shaft, coal bunker production area, living area, public facilities and transportation management areas of the mining area. After confirming the area to be monitored, the remote sensing image of the area to be monitored is obtained, and the remote sensing image is analyzed to obtain the remote sensing data, so as to monitor the area to be monitored covering the mining area based on the remote sensing data.

Step 120, in the case of confirming that the area to be monitored is a crop sensitive area to precipitation, obtain the mean value of the normalized vegetation index and the crop identification index of the time series of the area to be monitored based on the remote sensing data, and based on the The crop identification index and the mean value of the normalized vegetation index of the time series confirm that the to-be-monitored area is a farmland area through the first preset condition.

和作物识别指数(CRI)作为判断指标，将待监测区域确认为农田区域，即该区域满足作物提取的首要目标。Specifically, on the basis that the to-be-monitored area covering the mining area is a crop sensitive to precipitation, the mean value of the normalized vegetation index of the time series of the to-be-monitored area is obtained according to the remote sensing data

The crop identification index (CRI) is used as the judgment index, and the area to be monitored is confirmed as the farmland area, that is, the area meets the primary goal of crop extraction.

Step 130: Obtain the temperature vegetation drought index and crop nitrogen content of the farmland area, and based on the temperature vegetation drought index and crop nitrogen content, preliminarily confirm that the farmland area is affected by the goaf through a second preset condition. Area.

Specifically, in this embodiment, after confirming that the area to be monitored is a farmland area, the temperature vegetation drought index (TVDI) and crop nitrogen content (TCARI/OSAVI) of the area are obtained. When the temperature vegetation drought index and crop nitrogen content meet the preset conditions, it is determined that the area is the farmland area affected by the goaf.

The present invention provides a remote sensing extraction method for the influence of a mined-out area of a mining area on the surface, by determining a to-be-monitored area of a mining area, and acquiring remote-sensing data of the to-be-monitored area, based on the remote-sensing data to obtain the mean value of the normalized vegetation index of the time series of the to-be-monitored area and the crop identification index, and based on the crop identification index and the mean value of the normalized vegetation index of the time series, the area to be monitored is confirmed as a farmland area through the first preset condition, and the temperature, vegetation drought index and crop nitrogen content of the farmland area are obtained, and based on The temperature vegetation drought index and the crop nitrogen content preliminarily confirm the farmland area as the area affected by the goaf through the second preset condition. The invention can use remote sensing images to extract the ground surface from the goaf in the mining area, so as to judge whether the area corresponding to the remote sensing data is the area affected by the goaf, and achieve the purpose of accurately identifying the crop extraction under the influence of the goaf.

Based on the above embodiment, it is confirmed that the to-be-monitored area is a farmland area based on the crop identification index and the mean value of the normalized vegetation index of the time series through the first preset condition, including:

When the crop identification index is not less than the first preset threshold, and the mean value of the normalized vegetation index of the time series is not less than the second preset threshold, it is confirmed that the area to be monitored is a farmland area.

做一个范围限定，从而确定待监测区域为农田区域。Specifically, in this embodiment, the crop identification index (CRI) and the time series normalized vegetation index are

Make a scope limit to determine the area to be monitored as a farmland area.

时，判定待监测区域为农田区域。That is: CRI≥a1 and

, it is determined that the area to be monitored is a farmland area.

It should be noted that, a1 and a2 in this embodiment can be adjusted according to actual conditions, which are not specifically limited here.

Referring to FIG. 2, based on the above embodiment, under the condition that the temperature vegetation drought index is not less than the third preset threshold, and the nitrogen content of the crop is not greater than the fourth preset threshold, the farmland area is preliminarily confirmed as After the area affected by the gob, the method further includes:

Step 210, obtaining the mean value of the normalized vegetation index and the crop growth period of the time series in the area that is initially confirmed to be affected by the goaf, and obtaining the mean value of the normalized vegetation index and the mean value of the growth period of the farmland in the mining area;

Step 220: The difference between the mean value of the normalized vegetation index of the time series and the mean value of the normalized vegetation index of the farmland in the mining area is not less than the fifth preset threshold in the area that is initially confirmed to be affected by the goaf, and the If the crop growth cycle in the area preliminarily confirmed to be affected by the goaf is not equal to the average growth cycle of the farmland in the mining area, the farmland area is finally confirmed as the area affected by the goaf.

Specifically, in this implementation, after the area to be monitored is preliminarily confirmed as the area affected by the goaf, further confirmation is required, so as to finally confirm that the area to be monitored is the area affected by the goaf.

即时间序列的归一化植被指数均值，矿区农田的归一化植被指数均值

以及采空区影响的农田区域内的作物生长周期

和矿区农田的生长周期均值

First, obtain the normalized vegetation index in the farmland area that is preliminarily confirmed to be affected by the goaf

That is, the mean value of the normalized vegetation index of the time series, the mean value of the normalized vegetation index of the farmland in the mining area

and the crop growth cycle in the farmland area affected by the goaf

and the average growth cycle of farmland in the mining area

且

时，则可进一步判定该农田区域为最终确认的采空区影响的区域。when

and

, it can be further determined that the farmland area is the area affected by the final confirmed goaf.

In this embodiment, by judging the average value of the normalized vegetation index and the crop growth cycle in the farmland area that is initially confirmed to be affected by the goaf, the farmland area is finally confirmed as the farmland area affected by the goaf, so that it can be more effectively , Accurately identify crop extraction under the influence of goaf.

Based on the above embodiment, the acquisition of the time-series normalized vegetation index mean and crop identification index of the to-be-monitored area based on the remote sensing data includes:

Selecting target scene data from the scene data of the remote sensing data, and obtaining the normalized vegetation index of the target scene data and the mean value of the normalized vegetation index of the time series;

The crop identification index of the to-be-monitored area is obtained based on the normalized vegetation index of the target scene data, the mean value of the normalized vegetation index of the time series, and the scene data of the remote sensing image.

作物识别指数通过以下公式实现：Specifically, in this embodiment, the target scene data is selected from all scene data n ₁ of the remote sensing data as the calculation scene data, which is denoted as i. Obtain the normalized vegetation index of the target scene data i, denoted as NDVI _i . Obtain the mean value of the normalized vegetation index of the time series of the target scene data i, denoted as

The crop identification index is achieved by the following formula:

为目标景数据i的时间序列的归一化植被指数均值。Among them, CRI is the crop identification index, n ₁ is the scene number of remote sensing data, i is the target scene data used for calculation, NDVI _i is the normalized vegetation index of the target scene data i,

is the mean value of the normalized vegetation index of the time series of the target scene data i.

The mean value of the normalized vegetation index is determined by the following formula:

Among them, R _nir is the reflectance in the near-infrared band, and R _r is the reflectance in the red band.

In this embodiment, by calculating the target scene data of the remote sensing data, parameters such as the mean value of the normalized vegetation index and the crop identification index of the time series in the to-be-monitored area are obtained, thereby facilitating the confirmation of whether the to-be-monitored area is a farmland area.

Based on the above embodiment, the said farmland area is preliminarily confirmed as the area affected by the goaf through the second preset condition based on the temperature vegetation drought index and the crop nitrogen content, including:

Under the condition that the temperature vegetation drought index is not less than the third preset threshold, and the nitrogen content of the crop is not greater than the fourth preset threshold, the farmland area is preliminarily confirmed as the area affected by the goaf.

Specifically, in this embodiment, the temperature vegetation drought index (TVDI) and crop nitrogen content (TCARI/OSAVI) are defined within a range, thereby preliminarily confirming the farmland area as the area affected by the goaf.

That is, when TVDI≥a3 and TCARI/OSAVI≤a4, the farmland area is preliminarily confirmed as the area affected by the goaf.

It should be noted that, a3 and a4 in this embodiment can be adjusted according to actual conditions, which are not specifically limited here.

On the one hand, the TVDI in this embodiment is obtained on the basis that the two-dimensional vector space formed by the normalized vegetation index NDVI and the surface temperature Ts of any pixel is a triangle, which is suitable for studying a certain period of time in a specific year. the degree of drought in the area. As shown in the following formula:

Among them, TVDI represents the temperature vegetation drought index, Ts _min represents the minimum surface temperature, corresponding to the wet edge, Ts is the surface temperature of any pixel, a and b are parameters, that is, the dry edge (dry edge) The coefficient of the fitting equation .

It should be further explained that the above parameters require that the scope of the study area is large enough, and the surface coverage changes from bare soil to fully covered with vegetation. The soil surface water content changes from wilting water content to field capacity.

On the other hand, when crops are under stress, leaf nitrogen will be affected. Therefore, it is necessary to combine the nitrogen hyperspectral remote sensing diagnostic model to calculate the crop nitrogen content (TCARI/OSAVI), as shown in the following formula:

表示作物氮素含量，Rx表示在x波段下对应的中心波长的反射率，Rx₁、Rx₂、Rx₃和Rx₄取值分别为700、670、550和800nm。in,

represents the nitrogen content of crops, Rx represents the reflectance of the corresponding central wavelength in the x-band, and the values of Rx ₁ , Rx ₂ , Rx ₃ and Rx ₄ are 700, 670, 550 and 800 nm, respectively.

Based on the above embodiment, after determining the to-be-monitored area of the mining area and obtaining the remote sensing data of the to-be-monitored area, the method further includes:

Obtain the annual average precipitation of the area to be monitored and the precipitation in the crop planting season;

When the average annual precipitation is not greater than the sixth preset threshold, and the precipitation during the crop planting season is not greater than the seventh preset threshold, the to-be-monitored area is determined as a crop sensitive area to precipitation.

和作物种植季节降水量

从而判断待监测区域是否为作物对降水敏感区。Specifically, in this embodiment, the annual average precipitation in the area to be monitored for many years is obtained by obtaining

and precipitation during the planting season

Thereby, it can be judged whether the area to be monitored is a sensitive area of crops to precipitation.

且

时，将判定待监测区域为作物对降水敏感区。That is: when

and

, the to-be-monitored area will be determined as the crop sensitive area to precipitation.

It should be noted that, b1 and b2 in this embodiment can be adjusted according to actual conditions, which are not specifically limited here.

By judging the precipitation sensitivity of the area to be monitored, it is convenient to obtain the crop identification index and normalized vegetation parameters of the crops in the area to be monitored, which provides a basis for judging whether the area to be monitored is the affected area of the goaf.

The following describes the remote sensing extraction system for the influence of the mining area goaf on the surface provided by the present invention. refer to each other.

Referring to Fig. 3, the present invention also provides a remote sensing extraction system for the impact of a mining goaf on the surface, including the following modules:

The acquisition module 310 is used to determine the area to be monitored in the mining area, and acquire remote sensing data of the area to be monitored;

The farmland area confirmation module 320 is used to obtain the mean value of the normalized vegetation index and the crop identification index of the time series of the to-be-monitored area based on the remote sensing data when confirming that the area to be monitored is a crop sensitive to precipitation , and based on the crop identification index and the mean value of the normalized vegetation index of the time series, it is confirmed that the to-be-monitored area is a farmland area through a first preset condition;

The preliminary confirmation module 330 is used to obtain the temperature vegetation drought index and the crop nitrogen content of the farmland area, and based on the temperature vegetation drought index and the crop nitrogen content, the farmland area is preliminarily confirmed as a second preset condition. The area affected by the gob.

Based on the above embodiment, the farmland area confirmation module is specifically used for:

When the crop identification index is not less than the first preset threshold, and the mean value of the normalized vegetation index of the time series is not less than the second preset threshold, it is confirmed that the area to be monitored is a farmland area.

Based on the above embodiment, the preliminary confirmation module is specifically used for:

Under the condition that the temperature vegetation drought index is not less than the third preset threshold, and the nitrogen content of the crop is not greater than the fourth preset threshold, the farmland area is preliminarily confirmed as the area affected by the goaf.

Based on the above embodiments, the device further includes:

The preliminary area parameter acquisition module is used to acquire the mean value of the normalized vegetation index and the crop growth period of the time series in the area that is initially confirmed to be affected by the goaf, and obtain the mean value of the normalized vegetation index and the growth period of the farmland in the mining area mean;

The final confirmation module is used for the difference between the mean value of the normalized vegetation index of the time series and the mean value of the normalized vegetation index of the farmland in the mining area in the area that is initially confirmed to be affected by the goaf is not less than the fifth preset threshold, And if the crop growth cycle in the area preliminarily confirmed to be affected by the goaf is not equal to the average growth cycle of the farmland in the mining area, the farmland area is finally confirmed as the area affected by the goaf.

Based on the above embodiment, the farmland area confirmation module is specifically used for:

Selecting target scene data from the scene data of the remote sensing data, and obtaining the normalized vegetation index of the target scene data and the mean value of the normalized vegetation index of the time series;

The crop identification index of the to-be-monitored area is obtained based on the normalized vegetation index of the target scene data, the mean value of the normalized vegetation index of the time series, and the scene data of the remote sensing image.

Based on the above embodiments, the device further includes:

a precipitation acquisition module, used to acquire the annual average precipitation of the to-be-monitored area and the precipitation in the crop planting season;

A determination module, configured to determine the to-be-monitored area as a crop-to-rain precipitation under the condition that the annual average precipitation is not greater than the sixth preset threshold, and the precipitation during the crop planting season is not greater than the seventh preset threshold sensitive area.

FIG. 4 illustrates a schematic diagram of the physical structure of an electronic device. As shown in FIG. 4 , the electronic device may include: a processor (processor) 410, a communication interface (Communications Interface) 420, a memory (memory) 430, and a communication bus 440, The processor 410 , the communication interface 420 , and the memory 430 communicate with each other through the communication bus 440 . The processor 410 can invoke the logic instructions in the memory 430 to execute a remote sensing extraction method for the impact of a goaf in a mining area on the surface, the method comprising:

Determine the area to be monitored in the mining area, and obtain remote sensing data of the area to be monitored;

In the case of confirming that the to-be-monitored area is a crop sensitive area to precipitation, obtain the time-series normalized vegetation index mean value and crop identification index of the to-be-monitored area based on the remote sensing data, and based on the crop identification index and the mean value of the normalized vegetation index of the time series through the first preset condition to confirm that the area to be monitored is a farmland area;

Obtain the temperature vegetation drought index and crop nitrogen content of the farmland area, and based on the temperature vegetation drought index and the crop nitrogen content, the farmland area is preliminarily confirmed as an area affected by a goaf through a second preset condition.

In addition, the above-mentioned logic instructions in the memory 430 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on such understanding, the technical solution of the present invention can be embodied in the form of a software product in essence, or the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, Read-Only Memory (ROM, Read-Only Memory), Random Access Memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program codes .

In another aspect, the present invention also provides a computer program product, the computer program product includes a computer program, the computer program can be stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer can Execute the remote sensing extraction method for the impact of mined-out areas in mining areas on the surface provided by the above methods, the method includes:

Determine the area to be monitored in the mining area, and obtain remote sensing data of the area to be monitored;

In the case of confirming that the area to be monitored is a crop sensitive area to precipitation, obtain the mean value of the normalized vegetation index and the crop identification index of the time series of the area to be monitored based on the remote sensing data, and based on the crop identification index and the mean value of the normalized vegetation index of the time series through the first preset condition to confirm that the area to be monitored is a farmland area;

Obtain the temperature vegetation drought index and crop nitrogen content of the farmland area, and based on the temperature vegetation drought index and the crop nitrogen content, the farmland area is preliminarily confirmed as an area affected by a goaf through a second preset condition.

In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the computer program is implemented to perform the effects of the mine goaf on the surface provided by the above methods. Remote sensing extraction method, the method includes:

Determine the area to be monitored in the mining area, and obtain remote sensing data of the area to be monitored;

In the case of confirming that the to-be-monitored area is a crop sensitive area to precipitation, obtain the time-series normalized vegetation index mean value and crop identification index of the to-be-monitored area based on the remote sensing data, and based on the crop identification index and the mean value of the normalized vegetation index of the time series through the first preset condition to confirm that the area to be monitored is a farmland area;

Obtain the temperature vegetation drought index and crop nitrogen content of the farmland area, and based on the temperature vegetation drought index and the crop nitrogen content, the farmland area is preliminarily confirmed as an area affected by a goaf through a second preset condition.

The system embodiments described above are only illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in One place, or it can be distributed over multiple network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution in this embodiment. Those of ordinary skill in the art can understand and implement it without creative effort.

From the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and certainly can also be implemented by hardware. Based on this understanding, the above-mentioned technical solutions can be embodied in the form of software products in essence or the parts that make contributions to the prior art, and the computer software products can be stored in computer-readable storage media, such as ROM/RAM, magnetic A disc, an optical disc, etc., includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the methods described in various embodiments or some parts of the embodiments.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, but not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that it can still be Modifications are made to the technical solutions described in the foregoing embodiments, or some technical features thereof are equivalently replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. a kind of remote sensing extraction method of mining goaf impact on surface, is characterized in that, comprises: Determine the area to be monitored in the mining area, and obtain remote sensing data of the area to be monitored; In the case of confirming that the to-be-monitored area is a crop sensitive area to precipitation, obtain the time-series normalized vegetation index mean value and crop identification index of the to-be-monitored area based on the remote sensing data, and based on the crop identification index and the mean value of the normalized vegetation index of the time series through the first preset condition to confirm that the area to be monitored is a farmland area; Acquire the temperature vegetation drought index and crop nitrogen content of the farmland area, and based on the temperature vegetation drought index and the crop nitrogen content, the farmland area is preliminarily confirmed as an area affected by a goaf through a second preset condition. 2. The remote sensing extraction method of mining goaf according to claim 1, characterized in that, the normalized vegetation index mean value based on the crop identification index and time series is confirmed by the first preset condition The to-be-monitored area is a farmland area, including: When the crop identification index is not less than the first preset threshold, and the mean value of the normalized vegetation index of the time series is not less than the second preset threshold, it is confirmed that the area to be monitored is a farmland area. 3. The remote sensing extraction method of mining goaf impact on surface according to claim 1, characterized in that, described farmland area based on the temperature vegetation drought index and crop nitrogen content by the second preset condition. Areas initially identified as goaf affected include: Under the condition that the temperature vegetation drought index is not less than the third preset threshold, and the nitrogen content of the crop is not greater than the fourth preset threshold, the farmland area is preliminarily confirmed as the area affected by the goaf. 4. The remote sensing extraction method of mining goaf impact on the surface according to claim 3, characterized in that, at the temperature, the vegetation drought index is not less than the third preset threshold, and the nitrogen content of the crops is not greater than the third preset threshold. In the case of four preset thresholds, after the farmland area is preliminarily confirmed as the area affected by the goaf, the method further includes: Obtaining the mean value of the normalized vegetation index and the crop growth period of the time series in the area that is initially confirmed to be affected by the goaf, and obtaining the mean value of the normalized vegetation index and the mean value of the growth period of the farmland in the mining area; The difference between the mean value of the normalized vegetation index of the time series and the mean value of the normalized vegetation index of the farmland in the mining area in the area that is preliminarily confirmed to be affected by the goaf is not less than the fifth preset threshold, and the preliminary confirmation is If the crop growth cycle in the area affected by the goaf is not equal to the average growth cycle of the farmland in the mining area, the farmland area is finally confirmed as the area affected by the goaf. 5. the remote sensing extraction method of mining goaf according to claim 1, is characterized in that, described based on described remote sensing data obtains the normalized vegetation index mean value and crop of the time series of described area to be monitored Identify indices, including: Selecting target scene data from the scene data of the remote sensing data, and obtaining the normalized vegetation index of the target scene data and the mean value of the normalized vegetation index of the time series; The crop identification index of the to-be-monitored area is obtained based on the normalized vegetation index of the target scene data, the mean value of the normalized vegetation index of the time series, and the scene data of the remote sensing image. 6. The remote sensing extraction method for the influence of mined-out areas in mining areas on the surface according to any one of claims 1-5, characterized in that, after determining the area to be monitored in the mining area, and after obtaining the remote sensing data of the area to be monitored, the method further includes: include: Obtain the annual average precipitation of the area to be monitored and the precipitation in the crop planting season; When the average annual precipitation is not greater than the sixth preset threshold, and the precipitation during the crop planting season is not greater than the seventh preset threshold, the to-be-monitored area is determined as a crop sensitive area to precipitation. 7. A remote sensing extraction system for the influence of a goaf in a mining area on the surface, comprising: The acquisition module is used to determine the area to be monitored in the mining area, and obtain the remote sensing data of the area to be monitored; a farmland area confirmation module, configured to obtain the mean value of the normalized vegetation index and the crop identification index of the time series of the to-be-monitored area based on the remote sensing data under the condition that the to-be-monitored area is confirmed as a crop sensitive area to precipitation, and confirming that the to-be-monitored area is a farmland area through the first preset condition based on the crop identification index and the mean value of the normalized vegetation index of the time series; The preliminary confirmation module is used to obtain the temperature vegetation drought index and the crop nitrogen content of the farmland area, and based on the temperature vegetation drought index and the crop nitrogen content, the farmland area is preliminarily confirmed as harvesting through the second preset condition. The area affected by the empty zone. 8. An electronic device comprising a memory, a processor and a computer program stored on the memory and running on the processor, wherein the processor implements the program as claimed in claim 1 when executing the program A remote sensing extraction method for the impact of goafs in mining areas on the surface of any one of to 6. 9. A non-transitory computer-readable storage medium having a computer program stored thereon, is characterized in that, when the computer program is executed by the processor, it is characterized in that, when the computer program is executed by the processor, the mining area goaf as described in any one of claims 1 to 6 is implemented. Remote sensing extraction methods for surface impacts. 10 . A computer program product, comprising a computer program, characterized in that, when the computer program is executed by a processor, the remote sensing extraction method for the influence of a goaf in a mining area on the ground surface according to any one of claims 1 to 6 is implemented.

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