CN117113160A - Post-disaster recovery condition monitoring method and device, computer equipment and storage medium - Google Patents
Post-disaster recovery condition monitoring method and device, computer equipment and storage medium Download PDFInfo
- Publication number
- CN117113160A CN117113160A CN202311387243.0A CN202311387243A CN117113160A CN 117113160 A CN117113160 A CN 117113160A CN 202311387243 A CN202311387243 A CN 202311387243A CN 117113160 A CN117113160 A CN 117113160A
- Authority
- CN
- China
- Prior art keywords
- disaster
- mode
- recovery
- determining
- index
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000011084 recovery Methods 0.000 title claims abstract description 122
- 238000000034 method Methods 0.000 title claims abstract description 43
- 238000012544 monitoring process Methods 0.000 title claims abstract description 34
- 238000012806 monitoring device Methods 0.000 claims description 3
- 230000008859 change Effects 0.000 abstract description 12
- 238000011156 evaluation Methods 0.000 abstract description 3
- 230000008569 process Effects 0.000 description 9
- 230000000694 effects Effects 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 230000002265 prevention Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 230000007423 decrease Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000005855 radiation Effects 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 230000001174 ascending effect Effects 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 238000004040 coloring Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
- G06Q10/06375—Prediction of business process outcome or impact based on a proposed change
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B20/00—Energy efficient lighting technologies, e.g. halogen lamps or gas discharge lamps
- Y02B20/40—Control techniques providing energy savings, e.g. smart controller or presence detection
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Educational Administration (AREA)
- Physics & Mathematics (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- General Business, Economics & Management (AREA)
- Data Mining & Analysis (AREA)
- Entrepreneurship & Innovation (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Engineering & Computer Science (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Computational Biology (AREA)
- Quality & Reliability (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Circuit Arrangement For Electric Light Sources In General (AREA)
Abstract
The application provides a method and a device for monitoring post-disaster recovery conditions, computer equipment and a storage medium. The method comprises the following steps: acquiring night light data of a target area; the night lamplight data comprise disaster front lamplight parameters, disaster middle lamplight parameters and disaster back lamplight parameters of each pixel, and each pixel corresponds to one sub-area of the target area; for any one sub-area, determining an interference index according to the in-disaster lamplight parameter and the pre-disaster lamplight parameter, and determining a recovery index according to the post-disaster lamplight parameter and the in-disaster lamplight parameter; determining a target evolution mode corresponding to the subarea from a plurality of preset evolution modes according to the interference index and the recovery index, and determining a mode class to which the target evolution mode belongs; and identifying post-disaster recovery conditions of the sub-areas according to the mode types. The method can quantitatively characterize dynamic change characteristics of the pixel horizontal noctilucent image before-after-disaster by effectively utilizing information in the lamplight data, and realizes monitoring and evaluation of post-disaster recovery progress.
Description
Technical Field
The present application relates to the field of post-disaster monitoring technologies, and in particular, to a post-disaster recovery condition monitoring method, apparatus, computer device, and storage medium.
Background
Various regional natural disasters form disaster-forming areas with larger scale, and the natural and artificial activity processes of disaster areas are also greatly changed, so that night light data closely related to artificial activities are obviously changed, and theory and practice problem researches related to the natural disasters are conducted by utilizing a noctilucent remote sensing means, so that the method becomes a leading-edge hot topic in recent years.
The surface space units often vary significantly in terms of environmental conditions and land use, resulting in significant differences in the disaster management strategies for people. Some key sensitive areas may put more disaster prevention and reduction measures and disaster prevention and relief measures, and also put more force to restore and reconstruct after disaster, while some non-sensitive areas (such as large-area natural vegetation distribution areas) may rely more on the resistance and restoration capacity of the ecosystem itself to cope with the challenges of natural disasters. This differentiated countermeasure inevitably results in different dynamic patterns of light intensity. Because of the lack of scientific means to quantitatively characterize the dynamic light change mode at the pixel level, the conventional technology cannot provide means for monitoring the post-disaster recovery condition according to different evolution modes.
Disclosure of Invention
The application aims to at least solve one of the technical defects, and particularly provides a scientific and effective method for monitoring post-disaster recovery conditions.
In a first aspect, the present application provides a method for monitoring a post-disaster recovery situation, including:
acquiring night light data of a target area; the night lamplight data comprise disaster front lamplight parameters, disaster middle lamplight parameters and disaster back lamplight parameters of each pixel, and each pixel corresponds to one sub-area of the target area;
for any one sub-area, determining an interference index according to the in-disaster lamplight parameter and the pre-disaster lamplight parameter, and determining a recovery index according to the post-disaster lamplight parameter and the in-disaster lamplight parameter;
determining a target evolution mode corresponding to the subarea from a plurality of preset evolution modes according to the interference index and the recovery index, and determining a mode class to which the target evolution mode belongs;
and identifying post-disaster recovery conditions of the sub-areas according to the mode types.
In one embodiment, determining the interference index based on the in-disaster lighting parameters and the pre-disaster lighting parameters includes:
and dividing the difference between the disaster light parameters and the disaster front light parameters by the disaster front light parameters to obtain an interference index.
In one embodiment, determining the recovery index based on the post-disaster lighting parameters and the in-disaster lighting parameters includes:
and dividing the difference between the light parameters after the disaster and the light parameters in the disaster by the light parameters before the disaster to obtain a recovery index.
In one embodiment, determining, according to the interference index and the recovery index, a target evolution mode corresponding to the sub-region from a plurality of preset evolution modes includes:
the method comprises the steps that if a plurality of disturbance indexes are smaller than zero and a recovery index is larger than zero, a target evolution mode is determined to be a first evolution mode;
the disturbance indexes are larger than zero and the recovery index is smaller than zero, and the target evolution mode is determined to be a second evolution mode;
if the disturbance indexes are larger than zero and the recovery index is larger than or equal to zero, determining that the target evolution mode is a third evolution mode;
if the disturbance indexes are smaller than zero and the recovery index is smaller than or equal to zero, determining that the target evolution mode is a fourth evolution mode;
if the interference index is equal to zero and the recovery index is not equal to zero, determining that the target evolution mode is a fifth evolution mode;
and if the interference index and the recovery index are both equal to zero, determining that the target evolution mode is a sixth evolution mode.
In one embodiment, determining a mode class to which the target evolution mode belongs includes:
if the target evolution mode is the first evolution mode or the second evolution mode, determining the mode category as a first category;
if the target evolution mode is the third evolution mode, the fourth evolution mode or the fifth evolution mode, determining the mode category as the second category;
and if the target evolution mode is the sixth evolution mode, determining the mode category as the third category.
In one embodiment, identifying post-disaster recovery situations for a sub-area according to a pattern category includes:
if the mode class is the first class, marking a first mark for the subarea;
if the mode class is the second class, marking a second mark for the subarea;
if the mode class is the third class, marking a third mark for the subarea;
the first mark, the second mark and the third mark are respectively used for representing different attention-required grades of the subareas, wherein the arrangement of the attention-required grades from low to high is respectively as follows: a third identifier, a first identifier and a second identifier.
In one embodiment, the pre-disaster lighting parameter, the mid-disaster lighting parameter and the post-disaster lighting parameter are all illuminance values.
In a second aspect, the present application provides a post-disaster recovery situation monitoring apparatus, including:
the data acquisition module is used for acquiring night light data of the target area; the night lamplight data comprise disaster front lamplight parameters, disaster middle lamplight parameters and disaster back lamplight parameters of each pixel, and each pixel corresponds to one sub-area of the target area;
the index determining module is used for determining an interference index according to the light parameters in the disaster and the light parameters in the front disaster for any one of the sub-areas, and determining a recovery index according to the light parameters after the disaster and the light parameters in the disaster;
the mode determining module is used for determining a target evolution mode corresponding to the subarea from a plurality of preset evolution modes according to the interference index and the recovery index and determining a mode category to which the target evolution mode belongs;
and the identification module is used for identifying the post-disaster recovery condition of the sub-area according to the mode category.
In a third aspect, the present application provides a computer device comprising one or more processors, and a memory having stored therein computer readable instructions which, when executed by the one or more processors, perform the steps of the post-disaster recovery situation monitoring method of any of the embodiments described above.
In a fourth aspect, the present application provides a storage medium having stored therein computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of the post-disaster recovery situation monitoring method in any of the embodiments described above.
From the above technical solutions, the embodiment of the present application has the following advantages:
based on any of the above embodiments, first, night light data of a target area is acquired, including light parameters of each sub-area at three time points before, during and after a disaster, and an interference index and a recovery index of each sub-area are calculated on the basis. Then, by matching with different lamplight evolution modes, a target evolution mode and a mode category thereof corresponding to each sub-area are determined. Finally, the post-disaster recovery condition identification is carried out on each sub-area according to the mode category, and the identification result can be intuitively displayed in front of decision-making staff, so that the resources can be conveniently allocated accordingly to carry out targeted recovery work. The method can quantitatively depict dynamic change characteristics of the pixel horizontal noctilucent images before and after disaster by effectively utilizing information in lamplight data, provides scientific support for disaster management and recovery and reconstruction work of disaster areas, and realizes monitoring and evaluation of recovery progress after disaster.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the application, and that other drawings can be obtained from these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for monitoring post-disaster recovery conditions according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a preset evolution mode according to an embodiment of the present application;
FIG. 3 is a schematic block diagram of a post-disaster recovery monitoring apparatus according to an embodiment of the present application;
fig. 4 is an internal structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In a first aspect, the present application provides a method for monitoring post-disaster recovery situations, referring to fig. 1, including steps S102 to S108.
S102, night light data of a target area are acquired.
It can be understood that the target area is the area where the post-disaster recovery condition monitoring is required. The lamplight parameters represent the lamplight intensity in the specific area in an imaging mode, the pixel is the minimum unit in the image, and the corresponding part of the pixel in the target area is a sub-area of the target area. The night light data comprises disaster front light parameters, disaster middle light parameters and disaster back light parameters of each pixel. The light parameters can directly select the radiation brightness value in the noctilucent remote sensing data. The noctilucent remote sensing data is derived from the upward light of the ground, so that the noctilucent remote sensing data can be interfered by natural environment and human factors, the built environment and the human activities in the city are complex, and the direct use of the radiation brightness value as the lamplight parameter is not objective. And compared with the brightness value, the brightness value can more intuitively reflect the brightness of the environment. Thus, the illumination value obtained based on the inversion of the radiance value may be utilized as the lighting parameter. The disaster front lamplight parameters refer to lamplight parameters acquired one day before the disaster occurs in the target area, and lamplight parameters corresponding to the night of the day before the disaster occurs can be selected. The lamplight parameters in the disaster refer to lamplight parameters acquired in one day of the disaster occurrence and duration stage, and the lamplight parameters can be selected according to the duration time of the disaster. For short-term disasters, such as typhoons, the lighting parameters corresponding to the night of the day before the end of the typhoon can be selected. For long-term disasters, such as earthquakes, the corresponding lamplight parameters at night after the main disasters are finished and the preset days can be selected. Post-disaster lighting parameters refer to lighting parameters acquired on one day of the reconstruction phase. The date for monitoring the post-disaster recovery condition can be selected according to the requirement, and the lamplight parameters collected at night on the same day are selected.
S104, for any sub-area, determining an interference index according to the in-disaster lamplight parameter and the pre-disaster lamplight parameter, and determining a recovery index according to the post-disaster lamplight parameter and the in-disaster lamplight parameter.
It is understood that the interference index reflects the extent to which the intensity of the lights of the sub-area is affected before and after the disaster. The restoration index reflects the restoration degree of the lamplight intensity of the subarea after disaster and during monitoring restoration. According to natural disaster forming and recovering theory, the typical situation of a disaster affected area is that lamplight data before disaster maintains a stable state, and lamplight intensity suddenly drops in disaster until gradually recovering along with post-disaster reconstruction, and returning to a new stable state again. However, it has been found through analysis that, although there are many regions that conform to models of conventional theory, there are still many regions whose evolution process during disaster recovery is not the same. In order to further identify the evolution mode of the light intensity of each sub-area in the disaster recovery process, the interference index and the recovery index need to be determined respectively.
S106, determining a target evolution mode corresponding to the subarea from a plurality of preset evolution modes according to the interference index and the recovery index, and determining a mode category to which the target evolution mode belongs.
It can be understood that, based on natural disaster recovery theory, the present embodiment combines analysis of lamplight evolution conditions of disaster recovery-disaster recovery processes in different areas under different types of disasters to sum up a plurality of preset evolution modes. Each preset evolution mode is used for describing a typical mode of light intensity change of different areas under natural disasters. According to the interference index and the recovery index of the subarea, the light change process of the subarea can be judged to be most matched with the mode so as to determine the corresponding target evolution mode. These preset evolution modes can further be categorized into different mode categories. Each mode class corresponds to a post-disaster recovery scenario.
S108, identifying post-disaster recovery conditions of the sub-areas according to the mode types.
It can be understood that the different mode categories reflect the difference of the evolution process of the area under the disaster and correspond to different recovery conditions, so that corresponding marks can be marked on each subarea of the target area and are respectively used for representing the attention degree of the recovery condition after the disaster. The identification can be displayed to relevant decision-making staff through a visual means, and manpower and material resources are conveniently allocated and adjusted to carry out recovery reconstruction work.
According to the scheme, night light data of a target area are firstly obtained, the night light data comprise light parameters of each sub-area at three time points before, during and after a disaster, and an interference index and a recovery index of each sub-area are calculated on the basis. Then, by matching with different lamplight evolution modes, a target evolution mode and a mode category thereof corresponding to each sub-area are determined. Finally, the post-disaster recovery condition identification is carried out on each sub-area according to the mode category, and the identification result can be intuitively displayed in front of decision-making staff, so that the resources can be conveniently allocated accordingly to carry out targeted recovery work. The method can quantitatively depict dynamic change characteristics of the pixel horizontal noctilucent images before and after disaster by effectively utilizing information in lamplight data, provides scientific support for disaster management and recovery and reconstruction work of disaster areas, and realizes monitoring and evaluation of recovery progress after disaster.
In one embodiment, determining the interference index based on the in-disaster lighting parameters and the pre-disaster lighting parameters includes: and dividing the difference between the disaster light parameters and the disaster front light parameters by the disaster front light parameters to obtain an interference index.
The mathematical expression is used for representing:
；
wherein,Dntlin order to be an index of the interference,E（NTLin) Is the light parameter in the disaster,E（NTLpre) Is a disaster front lighting parameter. It can be understood that although the difference between the light parameters in the disaster and the light parameters in the disaster can reflect the absolute magnitude of the light intensity change of the subareas after the disaster, the difference of the light intensity of each subarea before the disaster is not considered, and the interference indexes of the different subareas are inconvenient to compare with each other. Based on the above, in this embodiment, the difference between the light parameter in the disaster and the light parameter in the disaster is compared with the light parameter in the disaster, so as to obtain the relative magnitude of the light intensity change of the sub-area after the disaster is suffered, which is equivalent to obtaining the normalized interference ratio.
In one embodiment, determining the recovery index based on the post-disaster lighting parameters and the in-disaster lighting parameters includes: and dividing the difference between the light parameters after the disaster and the light parameters in the disaster by the light parameters before the disaster to obtain a recovery index.
The mathematical expression is used for representing:
；
wherein,Rntlin order to be an index of the interference,E（NTLpost) Is the light parameter of the post-disaster light,E（NTLin) Is the light parameter in the disaster,E（NTLpre) Is a disaster front lighting parameter. It will be appreciated that although the difference between the post-disaster lighting parameters and the mid-disaster lighting parameters may reflect the absolute magnitude of the change in lighting intensity of the sub-areas during the reconstruction process, the difference in lighting intensity of each sub-area before the disaster is not considered, and the recovery indexes of the different sub-areas are inconvenient to compare with each other. Based on the above, in this embodiment, the difference between the light parameters after and during the disaster is compared with the light parameters before the disaster to obtain the relative magnitude of the light intensity change of the sub-area in the reconstruction process, which is equivalent to obtaining the normalized recovery rate.
In one embodiment, referring to fig. 2, the total number of preset evolution modes is six, which are respectively a first evolution mode, a second evolution mode, a third evolution mode, a fourth evolution mode, a fifth evolution mode and a sixth evolution mode (i.e. patterns 1 to 6 In the figure), and three vertical dashed lines In fig. 2 are respectively used to represent three time points of Pre-disaster, in-disaster and Post-disaster. The arrow in fig. 2 indicates the trend of the light intensity, and the arrow in fig. 2 indicates the upward direction, the downward direction, and the rightward direction, the steady state. According to the interference index and the recovery index, determining a target evolution mode corresponding to the subarea from a plurality of preset evolution modes, wherein the target evolution mode comprises:
(1) And if the disturbance indexes are smaller than zero and the recovery index is larger than zero, determining the target evolution mode as a first evolution mode.
The interference index and the recovery index can be used as two coordinate axes of a space, for example, the interference index is used as a horizontal axis, the recovery index is used as a vertical axis, and the corresponding target evolution mode is determined according to the position of the interference index and the recovery index of each sub-area in the space. Specifically, the interference index is smaller than zero and the recovery index is larger than zero, which means that the lamplight intensity of the subarea tends to decrease and increase in the disaster and recovery process as shown in Pattern1 in fig. 2. The method embodies the artificial activities and infrastructure related to night light intensity and the recovery and reconstruction process after disaster caused by the disaster-stricken area disaster-stricken process, and belongs to a first evolution mode.
(2) And if the disturbance indexes are larger than zero and the recovery index is smaller than zero, determining the target evolution mode as a second evolution mode.
In particular, an interference index greater than zero and a recovery index less than zero, i.e. representing a tendency for the light intensity of the sub-area to be increased and decreased during disaster recovery. The method has the advantages that the general sensitive targets possibly exist in the subareas, a large amount of manpower maintenance investment is needed before and during disaster prevention and disaster prevention, and after the disaster relief is finished, the manpower is removed, as shown in Pattern2 in fig. 2, so that the light intensity is changed in a first evolution mode.
(3) And if the disturbance indexes are larger than zero and the recovery index is larger than or equal to zero, determining the target evolution mode as a third evolution mode.
Specifically, the interference index is greater than zero and the recovery index is greater than or equal to zero, which means that the light intensity of the subarea continuously increases or maintains a high level during disaster and recovery. The situation that the light intensity after the disaster maintains high position or continues to rise is caused as shown by Pattern3 in fig. 2, and the light intensity belongs to a third evolution mode.
(4) And if the disturbance indexes are smaller than zero and the recovery index is smaller than or equal to zero, determining the target evolution mode as a fourth evolution mode.
In particular, the interference index is less than zero and the recovery index is less than or equal to zero, i.e. it represents a tendency that the light intensity of the sub-area continuously decreases or remains low during disaster and recovery. The situation that the night light intensity is reduced in the disaster process and the night light intensity is not restored due to the fact that the artificial activity intensity after the disaster maintains the mid-disaster level or continuously reduces as shown by Pattern4 in fig. 2 is reflected, and the method belongs to a fourth evolution mode.
(5) And if the interference index is equal to zero and the recovery index is not equal to zero, determining the target evolution mode as a fifth evolution mode.
Specifically, the interference index is equal to zero and the recovery index is not equal to zero, namely, the situation that the disaster occurs to cause local disaster is represented, but the night light intensity is not affected, and after the disaster, due to different recovery strategies (human intervention is performed to recover or the disaster area is abandoned, etc.), as shown in Pattern5 in fig. 2, the night light intensity after the disaster has an ascending or descending trend, and the method belongs to a fifth evolution mode.
(6) And if the interference index and the recovery index are both equal to zero, determining that the target evolution mode is a sixth evolution mode.
Specifically, the interference index and the recovery index are both equal to zero, that is, the disaster occurrence does not affect the subarea, and the disaster is generally in a high-toughness area which is distributed in a concentrated manner and almost has no artificial activity, and the disaster does not affect the light intensity at night before and after the disaster, as shown by Pattern6 in fig. 2, and belongs to a sixth evolution mode. When the target area is a urban area, the duty ratio of the first evolution mode is generally highest, the duty ratio of the second evolution mode, the duty ratio of the third evolution mode and the duty ratio of the fourth evolution mode are centered, the duty ratio of the fifth evolution mode is relatively less, and the duty ratio of the sixth evolution mode is extremely low.
In one embodiment, referring to fig. 2, determining a mode class to which the target evolution mode belongs includes:
(1) And if the target evolution mode is the first evolution mode or the second evolution mode, determining the mode category as the first category.
When the light intensity of the subarea is in the first evolution mode or the second evolution mode, the change trend of the light intensity of the subarea is recovered to the level before the disaster, the subarea is represented to be subjected to benign recovery process, and the recovery power input by the subarea is reasonable and belongs to the first category. In the identification, a first identification corresponding to the first category will be used.
(2) And if the target evolution mode is the third evolution mode, the fourth evolution mode or the fifth evolution mode, determining the mode category as the second category.
The fact that the light intensity in the sub-region is in the third evolution mode, the fourth evolution mode and the fifth evolution mode means that the change trend of the light intensity of the sub-region deviates from the pre-disaster level, represents that the light evolution rule of the sub-region is abnormal, and needs to pay attention to whether the reconstruction plan needs to be corrected or not, and belongs to the second category. In the case of identification, a second identification corresponding to the second category will be used.
(3) And if the target evolution mode is the sixth evolution mode, determining the mode category as the third category.
In the sixth evolution mode, this sub-area is generally represented by a strong resistance to disasters, without excessive attention, belonging to the third category. In the identification, a third identification corresponding to a third category will be used. The first mark, the second mark and the third mark are respectively used for representing different attention-required grades of the subareas, wherein the arrangement of the attention-required grades from low to high is respectively as follows: a third identifier, a first identifier and a second identifier. I.e. the sub-area belonging to the third category, requires minimal attention and no additional resources to be devoted to it. The required attention of the sub-region belonging to the first category is centered, and only the original reconstruction force and the continuous attention are required to be kept until the complete reconstruction is completed. The subareas belonging to the second category need to pay great attention to find out the reasons of the abnormal lamplight evolution by combining with the field investigation results, so that the post-disaster reconstruction actions can be developed in a targeted manner. The marking of each sub-area may be performed by text marking on the map, or may be performed by a visual method such as coloring the portion of each sub-area on the map with different specific colors.
The application provides a device for monitoring post-disaster recovery conditions, referring to fig. 3, comprising a data acquisition module 310, an index determination module 320, a mode determination module 330 and an identification module 340.
The data acquisition module 310 is configured to acquire night light data of a target area. The night light data comprises disaster front light parameters, disaster middle light parameters and disaster back light parameters of each pixel, and each pixel corresponds to one sub-area of the target area.
The index determining module 320 is configured to determine, for any one of the sub-areas, an interference index according to the in-disaster lamplight parameter and the pre-disaster lamplight parameter, and determine a recovery index according to the post-disaster lamplight parameter and the in-disaster lamplight parameter.
The mode determining module 330 is configured to determine, according to the interference index and the recovery index, a target evolution mode corresponding to the sub-region from a plurality of preset evolution modes, and determine a mode class to which the target evolution mode belongs.
The identification module 340 is configured to identify post-disaster recovery situations of the sub-area according to the pattern category.
For specific limitation of the post-disaster recovery condition monitoring device, reference may be made to the limitation of the post-disaster recovery condition monitoring method hereinabove, and no further description is given here. All or part of the modules in the post-disaster recovery condition monitoring device can be realized by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules. It should be noted that, in the embodiment of the present application, the division of the modules is schematic, which is merely a logic function division, and other division manners may be implemented in actual implementation.
The present application provides a computer device comprising one or more processors and a memory having stored therein computer readable instructions which, when executed by the one or more processors, perform the steps of the post-disaster recovery situation monitoring method of any of the above embodiments.
Schematically, as shown in fig. 4, fig. 4 is a schematic internal structure of a computer device according to an embodiment of the present application. Referring to FIG. 4, computer device 400 includes a processing component 402 that further includes one or more processors, and memory resources represented by memory 401, for storing instructions, such as application programs, executable by processing component 402. The application program stored in the memory 401 may include one or more modules each corresponding to a set of instructions. Further, processing component 402 is configured to execute instructions to perform the steps of the post-disaster recovery scenario monitoring method of any of the embodiments described above.
The computer device 400 may also include a power component 403 configured to perform power management of the computer device 400, a wired or wireless network interface 404 configured to connect the computer device 400 to a network, and an input output (I/O) interface 405.
It will be appreciated by persons skilled in the art that the architecture shown in fig. 4 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting as to the computer device to which the present inventive arrangements are applicable, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
The present application provides a storage medium having stored therein computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of the post-disaster recovery situation monitoring method of any of the embodiments described above.
In the present specification, each embodiment is described in a progressive manner, and each embodiment focuses on the difference from other embodiments, and may be combined according to needs, and the same similar parts may be referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for monitoring post-disaster recovery conditions, comprising:
acquiring night light data of a target area; the night light data comprise disaster front light parameters, disaster middle light parameters and disaster rear light parameters of each pixel, and each pixel corresponds to one sub-area of the target area;
for any one of the subareas, determining an interference index according to the disaster-in lamplight parameters and the disaster-front lamplight parameters, and determining a recovery index according to the disaster-back lamplight parameters and the disaster-in lamplight parameters;
determining a target evolution mode corresponding to the subarea from a plurality of preset evolution modes according to the interference index and the recovery index, and determining a mode class to which the target evolution mode belongs;
and identifying post-disaster recovery conditions of the subareas according to the mode types.
2. The method for monitoring post-disaster recovery situations according to claim 1, wherein determining an interference index according to the in-disaster lighting parameters and the pre-disaster lighting parameters comprises:
and dividing the disaster front lamplight parameter by the difference between the disaster middle lamplight parameter and the disaster front lamplight parameter to obtain the interference index.
3. The method for monitoring post-disaster recovery situations according to claim 2, wherein determining a recovery index according to the post-disaster lighting parameters and the in-disaster lighting parameters comprises:
and dividing the disaster front lamplight parameter by the difference between the disaster rear lamplight parameter and the disaster middle lamplight parameter to obtain the recovery index.
4. The method for monitoring post-disaster recovery situations according to claim 3, wherein determining a target evolution mode corresponding to the sub-area from a plurality of preset evolution modes according to the interference index and the recovery index comprises:
if the interference index is smaller than zero and the recovery index is larger than zero, determining the target evolution mode as a first evolution mode;
if the interference index is greater than zero and the recovery index is less than zero, determining that the target evolution mode is a second evolution mode;
if the interference index is greater than zero and the recovery index is greater than or equal to zero, determining that the target evolution mode is a third evolution mode;
if the interference index is less than zero and the recovery index is less than or equal to zero, determining that the target evolution mode is a fourth evolution mode;
if the interference index is equal to zero and the recovery index is not equal to zero, determining that the target evolution mode is a fifth evolution mode;
and if the interference index and the recovery index are both equal to zero, determining that the target evolution mode is a sixth evolution mode.
5. The post-disaster recovery situation monitoring method of claim 4, wherein said determining a pattern class to which said target evolution pattern belongs comprises:
if the target evolution mode is the first evolution mode or the second evolution mode, determining the mode category as a first category;
if the target evolution mode is the third evolution mode, the fourth evolution mode or the fifth evolution mode, determining that the mode class is a second class;
and if the target evolution mode is the sixth evolution mode, determining the mode category as a third category.
6. The method for monitoring post-disaster recovery situations according to claim 5, wherein the identifying post-disaster recovery situations of the sub-area according to the pattern category comprises:
if the mode category is the first category, marking a first mark for the subarea;
if the mode category is the second category, marking a second mark for the subarea;
if the mode category is the third category, marking a third mark for the subarea;
the first identifier, the second identifier and the third identifier are respectively used for representing different attention-required grades of the subareas, wherein the arrangement of the attention-required grades from low to high is as follows: a third identifier, a first identifier and a second identifier.
7. The method for monitoring post-disaster recovery situations according to any one of claims 1-6, wherein the pre-disaster lighting parameters, the in-disaster lighting parameters, and the post-disaster lighting parameters are illuminance values.
8. A post-disaster recovery situation monitoring device, comprising:
the data acquisition module is used for acquiring night light data of the target area; the night light data comprise disaster front light parameters, disaster middle light parameters and disaster rear light parameters of each pixel, and each pixel corresponds to one sub-area of the target area;
the index determining module is used for determining an interference index according to the disaster-in lamplight parameter and the disaster-front lamplight parameter for any one of the subareas, and determining a recovery index according to the disaster-back lamplight parameter and the disaster-in lamplight parameter;
the mode determining module is used for determining a target evolution mode corresponding to the subarea from a plurality of preset evolution modes according to the interference index and the recovery index, and determining a mode category to which the target evolution mode belongs;
and the identification module is used for identifying the post-disaster recovery condition of the subarea according to the mode category.
9. A computer device comprising one or more processors and a memory having stored therein computer readable instructions which, when executed by the one or more processors, perform the steps of the post-disaster recovery situation monitoring method of any of claims 1-7.
10. A storage medium having stored therein computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of the post-disaster recovery situation monitoring method of any of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311387243.0A CN117113160B (en) | 2023-10-25 | 2023-10-25 | Post-disaster recovery condition monitoring method and device, computer equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311387243.0A CN117113160B (en) | 2023-10-25 | 2023-10-25 | Post-disaster recovery condition monitoring method and device, computer equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117113160A true CN117113160A (en) | 2023-11-24 |
| CN117113160B CN117113160B (en) | 2024-02-02 |
Family
ID=88795197
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311387243.0A Active CN117113160B (en) | 2023-10-25 | 2023-10-25 | Post-disaster recovery condition monitoring method and device, computer equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117113160B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117408438A (en) * | 2023-12-14 | 2024-01-16 | 中国测绘科学研究院 | Industrial park low-utility land extraction method and system based on multi-source big data |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101614822A (en) * | 2009-07-17 | 2009-12-30 | 北京大学 | Detect the method for road damage based on post-disaster high-resolution remote sensing image |
| JP2011014151A (en) * | 2010-08-19 | 2011-01-20 | Maoka Sekkei:Kk | Disaster recovery support system |
| CN109145454A (en) * | 2018-08-24 | 2019-01-04 | 中国科学院、水利部成都山地灾害与环境研究所 | The method that triple exponential models portray snow disaster in pastoral area restoring force space-time characterisation |
| CN109886067A (en) * | 2018-12-17 | 2019-06-14 | 北京师范大学 | Wetland is damaged remote sensing recognition method and device |
| CN115062853A (en) * | 2022-06-23 | 2022-09-16 | 中国科学院地理科学与资源研究所 | Scene simulation method, device, storage medium and system for post-disaster recovery |
| CN115511266A (en) * | 2022-09-02 | 2022-12-23 | 湖北省地震局(中国地震局地震研究所) | Method and system for analyzing influence factors of restoring force of earthquake disaster |
| CN115700645A (en) * | 2022-09-15 | 2023-02-07 | 北京师范大学 | Method for evaluating indirect damage of disaster |
-
2023
- 2023-10-25 CN CN202311387243.0A patent/CN117113160B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101614822A (en) * | 2009-07-17 | 2009-12-30 | 北京大学 | Detect the method for road damage based on post-disaster high-resolution remote sensing image |
| JP2011014151A (en) * | 2010-08-19 | 2011-01-20 | Maoka Sekkei:Kk | Disaster recovery support system |
| CN109145454A (en) * | 2018-08-24 | 2019-01-04 | 中国科学院、水利部成都山地灾害与环境研究所 | The method that triple exponential models portray snow disaster in pastoral area restoring force space-time characterisation |
| CN109886067A (en) * | 2018-12-17 | 2019-06-14 | 北京师范大学 | Wetland is damaged remote sensing recognition method and device |
| CN115062853A (en) * | 2022-06-23 | 2022-09-16 | 中国科学院地理科学与资源研究所 | Scene simulation method, device, storage medium and system for post-disaster recovery |
| CN115511266A (en) * | 2022-09-02 | 2022-12-23 | 湖北省地震局(中国地震局地震研究所) | Method and system for analyzing influence factors of restoring force of earthquake disaster |
| CN115700645A (en) * | 2022-09-15 | 2023-02-07 | 北京师范大学 | Method for evaluating indirect damage of disaster |
Non-Patent Citations (3)
| Title |
|---|
| ZEAL SHAH ET AL.`: "Mapping Disasters & Tracking Recovery in Conflict Zones Using Nighttime Lights", 《2020 IEEE GLOBAL HUMANITARIAN TECHNOLOGY CONFERENCE (GHTC)》, pages 1 - 8 * |
| 刘文毅 等: "基于NPP－VIIＲS 夜间灯光数据的2017 年九寨沟地震灾后恢复动态监测", 《北京测绘》, vol. 36, no. 12, pages 1739 - 1746 * |
| 马玥桐: "基于街景图像的北京市中轴线道路系统绿视率特征分析", 《中国城市林业》, vol. 18, no. 3, pages 46 - 50 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117408438A (en) * | 2023-12-14 | 2024-01-16 | 中国测绘科学研究院 | Industrial park low-utility land extraction method and system based on multi-source big data |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117113160B (en) | 2024-02-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20200357109A1 (en) | Method for detecting display screen quality, apparatus, electronic device and storage medium | |
| CN117113160B (en) | Post-disaster recovery condition monitoring method and device, computer equipment and storage medium | |
| CN108961238A (en) | Display screen quality determining method, device, electronic equipment and storage medium | |
| CN106780392A (en) | A kind of image interfusion method and device | |
| CN111383429A (en) | Method, system, device and storage medium for detecting dress of workers in construction site | |
| CN108921840A (en) | Display screen peripheral circuit detection method, device, electronic equipment and storage medium | |
| CN109064446A (en) | Display screen quality determining method, device, electronic equipment and storage medium | |
| CN108961239A (en) | Continuous casting billet quality detection method, device, electronic equipment and storage medium | |
| CN109410192A (en) | A kind of the fabric defect detection method and its device of multi-texturing level based adjustment | |
| CN115620241B (en) | Image processing-based field safety measure identification method and device | |
| CN109087281A (en) | Display screen peripheral circuit detection method, device, electronic equipment and storage medium | |
| CN105260995A (en) | Image repairing and denoising method and system | |
| CN116343103B (en) | Natural resource supervision method based on three-dimensional GIS scene and video fusion | |
| CN112419231A (en) | Visibility determination method and device, computer equipment and storage medium | |
| CN113033401A (en) | Human activity change recognition and supervision method for ecological protection red line | |
| CN110321378A (en) | A kind of mobile monitor image identification system and method | |
| CN114842240A (en) | Method for classifying images of leaves of MobileNet V2 crops by fusing ghost module and attention mechanism | |
| CN117237925B (en) | Intelligent road disease inspection method and system based on computer vision | |
| CN108564076B (en) | Visual control system in electric power wiring in intelligent building | |
| US9613294B2 (en) | Control of computer vision pre-processing based on image matching using structural similarity | |
| CN110210401B (en) | Intelligent target detection method under weak light | |
| Yang et al. | EHNQ: Subjective and objective quality evaluation of enhanced night-time images | |
| CN116686535A (en) | Unmanned harvester control method and system based on data analysis | |
| CN116245400A (en) | Mining area landscape pattern evolution analysis method based on high-resolution remote sensing | |
| CN113762020B (en) | Highway road surface crack detecting system based on matrix structure degree of depth neural network |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |