CN105809372B - Natural disaster risk monitoring system based on satellite remote sensing image - Google Patents
Natural disaster risk monitoring system based on satellite remote sensing image Download PDFInfo
- Publication number
- CN105809372B CN105809372B CN201610248227.7A CN201610248227A CN105809372B CN 105809372 B CN105809372 B CN 105809372B CN 201610248227 A CN201610248227 A CN 201610248227A CN 105809372 B CN105809372 B CN 105809372B
- Authority
- CN
- China
- Prior art keywords
- module
- information
- data
- early warning
- disaster
- 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.)
- Expired - Fee Related
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 29
- 238000013500 data storage Methods 0.000 claims abstract description 21
- 230000010365 information processing Effects 0.000 claims abstract description 11
- 238000012545 processing Methods 0.000 claims abstract description 11
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 39
- 230000002265 prevention Effects 0.000 claims description 29
- 238000010276 construction Methods 0.000 claims description 21
- 238000000034 method Methods 0.000 claims description 11
- 239000002689 soil Substances 0.000 claims description 10
- 238000001556 precipitation Methods 0.000 claims description 8
- 239000011435 rock Substances 0.000 claims description 8
- 238000006073 displacement reaction Methods 0.000 claims description 7
- 238000007726 management method Methods 0.000 claims description 5
- 239000000463 material Substances 0.000 claims description 5
- 238000011161 development Methods 0.000 claims description 4
- 238000005259 measurement Methods 0.000 claims description 4
- 230000006378 damage Effects 0.000 abstract description 8
- 238000004458 analytical method Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 238000011160 research Methods 0.000 description 4
- 230000009172 bursting Effects 0.000 description 3
- 238000009825 accumulation Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- DMBHHRLKUKUOEG-UHFFFAOYSA-N diphenylamine Chemical compound C=1C=CC=CC=1NC1=CC=CC=C1 DMBHHRLKUKUOEG-UHFFFAOYSA-N 0.000 description 2
- 238000012876 topography Methods 0.000 description 2
- 208000027418 Wounds and injury Diseases 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000003628 erosive effect Effects 0.000 description 1
- 230000008595 infiltration Effects 0.000 description 1
- 238000001764 infiltration Methods 0.000 description 1
- 208000014674 injury Diseases 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 239000011229 interlayer Substances 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 239000010410 layer Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
Images
Classifications
-
- 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
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- 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
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Tourism & Hospitality (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- General Business, Economics & Management (AREA)
- Educational Administration (AREA)
- Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Alarm Systems (AREA)
Abstract
The invention relates to a natural disaster risk monitoring system based on a satellite remote sensing image, which comprises: an image acquisition device; a positioning device; the positioning information processing module is in information connection with the positioning device; the three-dimensional system is in information connection with the positioning information processing module; the data storage module is used for storing the natural disaster information of the existing target area; the spatial data processing module is in information connection with the data storage module and the three-dimensional system; the database establishing module is in information connection with the spatial data processing module; the model establishing module is in information connection with the database establishing module; the early warning standard setting module is in information connection with the model establishing module and the field disaster feedback module; the early warning information pushing module is in information connection with the early warning standard setting module; and the field disaster feedback module is in information connection with the early warning standard setting module. The natural disaster risk monitoring system based on the satellite remote sensing image can avoid the damage degree of the natural disaster to the extra-high voltage engineering to a great extent.
Description
Technical Field
The invention relates to the field of remote sensing monitoring, in particular to a natural disaster risk monitoring system based on a satellite remote sensing image.
Background
The overall principle of natural disaster early warning is that under the general field of Beidou remote sensing technology, a national network system, a meteorological system, a flood prevention system and a national soil resource system are organically integrated, and by relying on the advantages of data sharing and resource integration, the research of forecasting and early warning of natural disasters such as landslides, debris flows, reservoir and reservoir dam bursting, waterlogging and the like is realized, effective information and technical means of disaster prevention, disaster reduction and disaster avoidance are provided for owners, construction parties and managers, and powerful safety guarantee is provided for guaranteeing the safety construction of extra-high voltage engineering.
The extra-high voltage engineering is used as an important energy channel of the country, the construction safety of the extra-high voltage engineering has important economic, political and social meanings, and is highly emphasized by leaders at all levels, so that the safety is always put in an important position. In addition to safety management in construction, the extra-high voltage engineering safety enables a management layer to pay special attention to natural disasters in a construction area due to large influence range, serious consequences and irresistibility, and therefore forecasting, early warning and early danger avoidance of the natural disasters become important contents in extra-high voltage construction.
The landforms passing through the extra-high voltage path along the line mainly include three categories of plateau low mountain landforms, low mountain-middle mountain landforms and alluvial plains. The analysis is carried out according to the geographical characteristics along the line, and the existing natural disasters mainly comprise geological disasters, flood disasters and northern wind disasters. In partial low mountain and high hilly area, the topography is more complicated, the volcaniclastic rock is widely distributed, the lithology of the stratum is complicated, the weak interlayer is more, the fracture structure is developed, the rock is broken and easily weathers, the slope foot of the mountain front area and the valley is larger, the thickness of the loose accumulation is larger, especially when certain rainfall is met, the loose accumulation is easily collapsed, slides and mudslide under the erosion and infiltration of rainwater, and the danger is brought to the extra-high voltage construction; in a plain area densely distributed in rivers and lakes, part of extra-high voltage towers are positioned in a flood area, a stagnant flood area and a flood diversion area, waterlogging and river and lake water level rising are often caused by rainfall, so that river banks and reservoir dams are threatened, and once bursting and overflow occur, the extra-high voltage towers and construction are influenced; in the north of the line, because the ground is in the north and the topography is high, the wind power is large and durable, and the adverse effect can be brought to extra-high voltage construction.
Meanwhile, because the extra-high voltage engineering line is long, the construction units are multiple, personnel are centralized, construction roads, cableways and large-scale construction machines are distributed, material stacking places are scattered, and the like, river flood disaster early warning, reservoir bursting disaster early warning, plain waterlogging disaster early warning and landslide debris flow disaster early warning are very necessary, the early warning time is longer and more accurate, the early emergency plan is started, the more active the risk avoidance measures are taken, and the probability of group death and group injury accidents is greatly reduced.
Some extra-high voltage engineering transmission lines pass through areas with much forest and grassland coverage, if the snow fall amount is less in winter, the temperature rises quickly in spring, the wind is strong, the number of days is large, and the fire risk is increased and increased at the beginning of a rainy season. In early summer, if dry weather occurs, forest and grassland fires are easy to occur, so that the weather early warning on the forest and grassland fires is very important.
By utilizing the Beidou remote sensing geographic information technology and combining various collected geological, water conservancy, meteorological data and other data, geographic identification is carried out on the area where disasters are likely to occur, and the disaster range is divided. The method comprises the steps of carrying out geological disaster analysis on areas prone to landslide and debris flow, setting disaster occurrence grades, carrying out deep research on disaster positions, scales, stability, damage degree and prevention requirements, and forming an area disaster risk map. The method is characterized by analyzing regional flood and waterlogging risks by combining meteorological and rainfall data, calculating the water converging amount of the river, lake and reservoir, comprehensively evaluating the probability of flood, classifying the grade, realizing forecast and early warning and avoiding the damage degree of natural disasters to the engineering to a great extent.
Disclosure of Invention
In order to provide a comprehensive and accurate disaster situation prediction system, the invention provides a natural disaster risk monitoring system based on a satellite remote sensing image, which comprises:
the image acquisition device is used for acquiring a remote sensing image of the target area;
the positioning device is in information connection with the image acquisition device and is used for checking the geographic positions and the actual environments of various target areas and knowing the existing state and the development trend of the target areas;
the positioning information processing module is in information connection with the positioning device and is used for marking key dangerous sections and dangerous points, namely poles and towers, roads, mechanical equipment, cableways, material stacking yards and construction personnel residences of reservoirs, gate dams, landslide points, debris flow areas, air ports and line construction areas;
the three-dimensional system is in information connection with the positioning information processing module and is used for storing the information identified by the positioning information processing module;
the data storage module is connected with the three-dimensional system information and used for storing the natural disaster information of the existing target area;
the spatial data processing module is connected with the data storage module and the three-dimensional system information and is used for integrating the information in the data storage module and the three-dimensional system;
the database establishing module is in information connection with the spatial data processing module and is used for establishing a natural disaster risk source database according to the information integrated by the spatial data processing module;
the model establishing module is in information connection with the database establishing module and is used for establishing a natural disaster risk source database in the module according to the database, dividing the monitoring range into different sections along the line according to geological and topographic conditions and the distribution of the risk sensitive areas, and establishing natural disaster early warning models for the different sections;
the early warning standard setting module is in information connection with the model establishing module and the field disaster feedback module and is used for establishing a natural disaster early warning standard according to a set region and level by combining a natural disaster risk source database, a natural disaster early warning model and a field disaster;
the early warning information pushing module is in information connection with the early warning standard setting module and is used for making different avoidance measures aiming at different early warning levels;
and the on-site disaster feedback module is in information connection with the early warning standard setting module and is used for analyzing the on-site disaster condition fed back by the constructors and feeding back the information to the early warning standard setting module.
Wherein, positioner includes big dipper satellite positioning system or GPS positioning system.
Wherein the data storage module comprises:
the system comprises a national soil resource storage module, a geological disaster risk point distribution module, a geological disaster prone distribution map, landslide displacement data and mud-rock flow monitoring and forecasting data, wherein the national soil resource storage module is used for storing geological disaster risk point distribution conditions, geological disaster prone distribution maps, landslide displacement data and mud-rock flow monitoring and forecasting data which are provided by a national soil resource department;
the water conservancy flood prevention storage module is used for storing water conservancy facility data, reservoir gate dam flood prevention water level data, riverway reservoir real-time water level and rain condition data which are provided by a water conservancy flood prevention department;
the forestry department storage module is used for storing forest grassland coverage data provided by a forestry department;
and the meteorological department storage module is used for storing the one-hour cloud picture, the one-hour real-time precipitation, the 24-hour precipitation forecast, the wind power forecast and the wind power actual measurement data provided by the meteorological department.
Wherein the database establishing module comprises:
the homeland resource database is used for storing data in the homeland resource storage module and data integrated by information in the three-dimensional system;
the water conservancy flood prevention database is used for storing data in the water conservancy flood prevention storage module and data integrated with information in the three-dimensional system;
the forestry department database is used for storing data in the storage module of the forestry department and data integrated by information in the three-dimensional system;
and the meteorological department database is used for storing the data in the meteorological department storage module and the data integrated by the information in the three-dimensional system.
The early warning standard setting module comprises a geological disaster early warning standard setting module, a water conservancy flood prevention disaster early warning standard setting module, a forest disaster early warning standard setting module and a meteorological disaster early warning standard setting module.
The system also comprises an information management query module which is connected with the data storage module and the three-dimensional system information and is used for managing the information in the data storage module and the three-dimensional system.
Wherein, the image acquisition device comprises a high-resolution second satellite.
According to the natural disaster risk monitoring system based on the satellite remote sensing image, the Beidou remote sensing geographic information technology is utilized, and the collected data of various geology, water conservancy, meteorology and the like are combined, so that the area where disasters are likely to occur is identified geographically, and the disaster range is divided. The method comprises the steps of carrying out geological disaster analysis on areas prone to landslide and debris flow, setting disaster occurrence grades, carrying out deep research on disaster positions, scales, stability, damage degree and prevention requirements, and forming an area disaster risk map. The method is characterized in that the method is combined with meteorological and precipitation data, regional flood and waterlogging risks are analyzed, the combined water yield of rivers, lakes and reservoirs is calculated, the probability of flood occurrence is comprehensively evaluated, grades are defined, forecast and early warning are realized, and the damage degree of natural disasters to the extra-high voltage engineering can be avoided to a great extent.
Drawings
FIG. 1: the invention has a structure schematic diagram.
Detailed Description
In order to further understand the technical scheme and the beneficial effects of the present invention, the following detailed description of the technical scheme and the beneficial effects thereof is provided with the accompanying drawings.
As shown in fig. 1, the natural disaster risk monitoring system based on satellite remote sensing images provided by the invention comprises:
the image acquisition device is used for acquiring a remote sensing image of the target area;
the positioning device is in information connection with the image acquisition device and is used for checking the geographic positions and the actual environments of various target areas and knowing the existing state and the development trend of the target areas;
the positioning information processing module is in information connection with the positioning device and is used for marking key dangerous sections and dangerous points, namely poles and towers, roads, mechanical equipment, cableways, material stacking yards and construction personnel residences of reservoirs, gate dams, landslide points, debris flow areas, air ports and line construction areas;
the three-dimensional system is in information connection with the positioning information processing module and is used for storing the information identified by the positioning information processing module;
the data storage module is connected with the three-dimensional system information and used for storing the natural disaster information of the existing target area;
the spatial data processing module is connected with the data storage module and the three-dimensional system information and is used for integrating the information in the data storage module and the three-dimensional system;
the database establishing module is in information connection with the spatial data processing module and is used for establishing a natural disaster risk source database according to the information integrated by the spatial data processing module;
the model establishing module is in information connection with the database establishing module and is used for establishing a natural disaster risk source database in the module according to the database, dividing the monitoring range into different sections along the line according to geological and topographic conditions and the distribution of the risk sensitive areas, and establishing natural disaster early warning models for the different sections;
the early warning standard setting module is in information connection with the model establishing module and the field disaster feedback module and is used for establishing a natural disaster early warning standard according to a set region and level by combining a natural disaster risk source database, a natural disaster early warning model and a field disaster;
the early warning information pushing module is in information connection with the early warning standard setting module and is used for making different avoidance measures aiming at different early warning levels;
and the on-site disaster feedback module is in information connection with the early warning standard setting module and is used for analyzing the on-site disaster condition fed back by the constructors and feeding back the information to the early warning standard setting module.
Wherein, the image acquisition device comprises a high-resolution second satellite.
Wherein, positioner includes big dipper satellite positioning system or GPS positioning system.
Wherein the data storage module comprises:
the system comprises a national soil resource storage module, a geological disaster risk point distribution module, a geological disaster prone distribution map, landslide displacement data and mud-rock flow monitoring and forecasting data, wherein the national soil resource storage module is used for storing geological disaster risk point distribution conditions, geological disaster prone distribution maps, landslide displacement data and mud-rock flow monitoring and forecasting data which are provided by a national soil resource department;
the water conservancy flood prevention storage module is used for storing water conservancy facility data, reservoir gate dam flood prevention water level data, riverway reservoir real-time water level and rain condition data which are provided by a water conservancy flood prevention department;
the forestry department storage module is used for storing forest grassland coverage data provided by a forestry department;
and the meteorological department storage module is used for storing the one-hour cloud picture, the one-hour real-time precipitation, the 24-hour precipitation forecast, the wind power forecast and the wind power actual measurement data provided by the meteorological department.
Wherein the database establishing module comprises:
the homeland resource database is used for storing data in the homeland resource storage module and data integrated by information in the three-dimensional system;
the water conservancy flood prevention database is used for storing data in the water conservancy flood prevention storage module and data integrated with information in the three-dimensional system;
the forestry department database is used for storing data in the storage module of the forestry department and data integrated by information in the three-dimensional system;
and the meteorological department database is used for storing the data in the meteorological department storage module and the data integrated by the information in the three-dimensional system.
The early warning standard setting module comprises a geological disaster early warning standard setting module, a water conservancy flood prevention disaster early warning standard setting module, a forest disaster early warning standard setting module and a meteorological disaster early warning standard setting module.
The system also comprises an information management query module which is connected with the data storage module and the three-dimensional system information and is used for managing the information in the data storage module and the three-dimensional system.
Based on the natural disaster risk monitoring system based on the satellite remote sensing image, the process for realizing natural disaster early warning in the invention is as follows:
s1: and collecting the remote sensing image by using an image collecting device.
S2: by utilizing the positioning device, remote sensing general investigation and analysis are carried out on areas such as rivers, flood diversion areas, flood stagnation areas, wind areas, landslide areas, slope dump areas and the like which pass through the engineering construction line, the geographical positions and the actual environments of various objects are checked, the existing state and the development trend of the objects are known, and on-site photos are collected.
S3: and (4) identifying key dangerous sections and dangerous points, namely identifying towers, roads, mechanical equipment, cableways, material yards and construction personnel residences of reservoirs, gate dams, landslide points, debris flow areas, air ports and line construction areas.
S4: the results of the identification are stored in a three-dimensional system.
S5: acquiring geological disaster risk point distribution conditions, geological disaster prone distribution maps, landslide displacement data and debris flow monitoring and forecasting data from a homeland resource department; acquiring water conservancy facility data, reservoir gate dam flood prevention water level data, and riverway reservoir real-time water level and rain condition data from a water conservancy flood prevention department; acquiring forest grassland coverage data from a forestry department; acquiring one-hour cloud pictures, one-hour real-time rainfall, 24-hour rainfall forecast, wind forecast and wind actual measurement data from a meteorological department; the system comprises a homeland resource storage module, a water conservancy flood prevention storage module, a forestry department storage module and a meteorological department storage module which are respectively stored in a data storage module.
S6: the data identified in step S3 and the data stored in step S5 are integrated.
S7: establishing a natural disaster risk source database according to the data integrated in the step S6, wherein the natural disaster risk source database respectively includes:
the homeland resource database comprises data in a homeland resource storage module and data integrated with information in the three-dimensional system;
the water conservancy flood prevention database comprises data in the water conservancy flood prevention storage module and data integrated with information in the three-dimensional system;
the forestry department database comprises data in a forestry department storage module and data integrated with information in the three-dimensional system;
and the meteorological department database comprises data in the meteorological department storage module and data integrated with information in the three-dimensional system.
S8: and according to the natural disaster risk source database in the step S7, dividing the monitoring range into different sections along the line by combining geological terrain conditions and the distribution of the risk sensitive areas, and establishing natural disaster early warning models for the different sections.
S9: the method comprises the steps of combining a natural disaster risk source database, a natural disaster early warning model and a field disaster situation, establishing natural disaster early warning standards according to set regions and levels, wherein the early warning standards respectively comprise geological disaster early warning standards, water conservancy flood prevention disaster early warning standards, forest disaster early warning standards and meteorological disaster early warning standards, and the early warning standards are respectively set to be blue, yellow, orange and red levels from low to high.
S10: and making different avoidance measures aiming at different early warning levels.
S11: and pushing the early warning result and the evasion measure to a user.
S12: and the site constructors feed back the site disaster situation in time, analyze the disaster scale and the disaster occurrence factors, and store the disaster scale and the disaster occurrence factors in a warehouse as a reference basis for establishing an early warning standard.
According to the natural disaster risk monitoring system based on the satellite remote sensing image, the Beidou remote sensing geographic information technology is utilized, and the collected data of various geology, water conservancy, meteorology and the like are combined, so that the area where disasters are likely to occur is identified geographically, and the disaster range is divided. The method comprises the steps of carrying out geological disaster analysis on areas prone to landslide and debris flow, setting disaster occurrence grades, carrying out deep research on disaster positions, scales, stability, damage degree and prevention requirements, and forming an area disaster risk map. The method is characterized in that the method is combined with meteorological and precipitation data, regional flood and waterlogging risks are analyzed, the combined water yield of rivers, lakes and reservoirs is calculated, the probability of flood occurrence is comprehensively evaluated, grades are defined, forecast and early warning are realized, and the damage degree of natural disasters to the extra-high voltage engineering can be avoided to a great extent.
Although the present invention has been described with reference to the preferred embodiments, it should be understood that the scope of the present invention is not limited thereto, and those skilled in the art will appreciate that various changes and modifications can be made without departing from the spirit and scope of the present invention.
Claims (7)
1. The utility model provides a natural disasters risk monitoring system based on satellite remote sensing image which characterized in that: the method comprises the following steps:
the image acquisition device is used for acquiring a remote sensing image of the target area;
the positioning device is in information connection with the image acquisition device and is used for checking the geographic positions and the actual environments of various target areas and knowing the existing state and the development trend of the target areas;
the positioning information processing module is in information connection with the positioning device and is used for marking key dangerous sections and dangerous points, namely poles and towers, roads, mechanical equipment, cableways, material stacking yards and construction personnel residences of reservoirs, gate dams, landslide points, debris flow areas, air ports and line construction areas;
the three-dimensional system is in information connection with the positioning information processing module and is used for storing the information identified by the positioning information processing module;
the data storage module is connected with the three-dimensional system information and used for storing the natural disaster information of the existing target area;
the spatial data processing module is connected with the data storage module and the three-dimensional system information and is used for integrating the information in the data storage module and the three-dimensional system;
the database establishing module is in information connection with the spatial data processing module and is used for establishing a natural disaster risk source database according to the information integrated by the spatial data processing module;
the model establishing module is in information connection with the database establishing module and is used for establishing a natural disaster risk source database in the module according to the database, dividing the monitoring range into different sections along the line according to geological and topographic conditions and the distribution of the risk sensitive areas, and establishing natural disaster early warning models for the different sections;
the early warning standard setting module is in information connection with the model establishing module and the field disaster feedback module and is used for establishing a natural disaster early warning standard according to a set region and level by combining a natural disaster risk source database, a natural disaster early warning model and a field disaster;
the early warning information pushing module is in information connection with the early warning standard setting module and is used for making different avoidance measures aiming at different early warning levels;
and the on-site disaster feedback module is in information connection with the early warning standard setting module and is used for analyzing the on-site disaster condition fed back by the constructors and feeding back the information to the early warning standard setting module.
2. The natural disaster risk monitoring system based on satellite remote sensing images as claimed in claim 1, characterized in that: the positioning device comprises a Beidou satellite positioning system or a GPS positioning system.
3. The natural disaster risk monitoring system based on satellite remote sensing images as claimed in claim 1, characterized in that: the data storage module includes:
the system comprises a national soil resource storage module, a geological disaster risk point distribution module, a geological disaster prone distribution map, landslide displacement data and mud-rock flow monitoring and forecasting data, wherein the national soil resource storage module is used for storing geological disaster risk point distribution conditions, geological disaster prone distribution maps, landslide displacement data and mud-rock flow monitoring and forecasting data which are provided by a national soil resource department;
the water conservancy flood prevention storage module is used for storing water conservancy facility data, reservoir gate dam flood prevention water level data, riverway reservoir real-time water level and rain condition data which are provided by a water conservancy flood prevention department;
the forestry department storage module is used for storing forest grassland coverage data provided by a forestry department;
and the meteorological department storage module is used for storing the one-hour cloud picture, the one-hour real-time precipitation, the 24-hour precipitation forecast, the wind power forecast and the wind power actual measurement data provided by the meteorological department.
4. The natural disaster risk monitoring system based on satellite remote sensing images as claimed in claim 1, characterized in that: the database building module comprises:
the homeland resource database is used for storing data in the homeland resource storage module and data integrated by information in the three-dimensional system;
the water conservancy flood prevention database is used for storing data in the water conservancy flood prevention storage module and data integrated with information in the three-dimensional system;
the forestry department database is used for storing data in the storage module of the forestry department and data integrated by information in the three-dimensional system;
and the meteorological department database is used for storing the data in the meteorological department storage module and the data integrated by the information in the three-dimensional system.
5. The natural disaster risk monitoring system based on satellite remote sensing images as claimed in claim 1, characterized in that: the early warning standard setting module comprises a geological disaster early warning standard setting module, a water conservancy flood prevention disaster early warning standard setting module, a forest disaster early warning standard setting module and a meteorological disaster early warning standard setting module.
6. The natural disaster risk monitoring system based on satellite remote sensing images as claimed in claim 1, characterized in that: the system also comprises an information management and query module which is connected with the data storage module and the three-dimensional system information and is used for managing the information in the data storage module and the three-dimensional system.
7. The natural disaster risk monitoring system based on satellite remote sensing images as claimed in claim 1, characterized in that: the image acquisition device comprises a high-resolution second satellite.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610248227.7A CN105809372B (en) | 2016-04-20 | 2016-04-20 | Natural disaster risk monitoring system based on satellite remote sensing image |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610248227.7A CN105809372B (en) | 2016-04-20 | 2016-04-20 | Natural disaster risk monitoring system based on satellite remote sensing image |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105809372A CN105809372A (en) | 2016-07-27 |
| CN105809372B true CN105809372B (en) | 2022-01-21 |
Family
ID=56457360
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610248227.7A Expired - Fee Related CN105809372B (en) | 2016-04-20 | 2016-04-20 | Natural disaster risk monitoring system based on satellite remote sensing image |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105809372B (en) |
Families Citing this family (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106651166B (en) * | 2016-12-15 | 2020-06-30 | 中国南方电网有限责任公司电网技术研究中心 | Natural disaster risk processing method and system based on Internet of things |
| CN108268972A (en) * | 2017-12-13 | 2018-07-10 | 江苏励维逊电气科技有限公司 | Led to based on day and monitor prewarning analysis system and method on-line with the aviation integral admittance electric power facility of big-dipper satellite |
| CN108111340B (en) * | 2017-12-13 | 2022-03-04 | 山东创智信息科技有限公司 | Space-to-air integrated communication emergency communication command cluster communication application system and method based on skynet and Beidou satellite |
| CN109034588A (en) * | 2018-07-18 | 2018-12-18 | 湖北思高科技发展有限公司 | A kind of geological disasters analysis method Internet-based |
| CN108984755A (en) * | 2018-07-18 | 2018-12-11 | 湖北思高科技发展有限公司 | A kind of geological geographic information system processing method |
| CN109783473A (en) * | 2018-12-26 | 2019-05-21 | 上海师范大学 | A kind of information processing method automatically creating Rainfall Disaster data-base recording |
| CN109766815A (en) * | 2019-01-03 | 2019-05-17 | 银河航天（北京）科技有限公司 | A kind of pair of object event carries out pre-warning system and method |
| CN111508192A (en) * | 2020-03-19 | 2020-08-07 | 陕西理工大学 | Ecological environment and tourism monitoring platform |
| CN111476176B (en) * | 2020-04-09 | 2023-04-07 | 云南电网有限责任公司电力科学研究院 | Early warning system and early warning method for power grid waterlogging area identification |
| CN114005252A (en) * | 2021-10-12 | 2022-02-01 | 嘉应学院 | Monitoring system and method based on multi-source information of mountain torrent disasters |
| CN117037425A (en) * | 2023-08-07 | 2023-11-10 | 齐鲁高速(山东)装配有限公司 | Mine slope stability and environment monitoring and early warning method, system and terminal |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104408900A (en) * | 2014-11-10 | 2015-03-11 | 柳州师范高等专科学校 | Dynamic optimization based neural network flood warning device and method |
| CN104881834A (en) * | 2015-06-25 | 2015-09-02 | 辽宁有色勘察研究院 | Mud-rock flow geological disaster identification and determination method based on 3S technology |
| CN205581960U (en) * | 2016-04-20 | 2016-09-14 | 国家电网公司 | Natural disasters risk monitoring system based on satellite remote sensing image |
-
2016
- 2016-04-20 CN CN201610248227.7A patent/CN105809372B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104408900A (en) * | 2014-11-10 | 2015-03-11 | 柳州师范高等专科学校 | Dynamic optimization based neural network flood warning device and method |
| CN104881834A (en) * | 2015-06-25 | 2015-09-02 | 辽宁有色勘察研究院 | Mud-rock flow geological disaster identification and determination method based on 3S technology |
| CN205581960U (en) * | 2016-04-20 | 2016-09-14 | 国家电网公司 | Natural disasters risk monitoring system based on satellite remote sensing image |
Non-Patent Citations (2)
| Title |
|---|
| 基于数字滑坡技术的暴雨滑坡、泥石流预警、监测模型研究;王治华等;《地学前缘》;20110915(第05期);全文 * |
| 基于电力大数据的输电线路防灾减灾分析系统设计――以贵州电网为例;虢韬等;《灾害学》;20160120(第01期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105809372A (en) | 2016-07-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105809372B (en) | Natural disaster risk monitoring system based on satellite remote sensing image | |
| Watson et al. | Characterization of peak streamflows and flood inundation of selected areas in southeastern Texas and southwestern Louisiana from the August and September 2017 flood resulting from Hurricane Harvey | |
| Cooper et al. | Assessing vulnerability due to sea-level rise in Maui, Hawai ‘i using LiDAR remote sensing and GIS | |
| CN205581960U (en) | Natural disasters risk monitoring system based on satellite remote sensing image | |
| Wang et al. | Monitoring and early warning system of Cirenmaco glacial lake in the central Himalayas | |
| Pan et al. | Evaluation of ecological sensitivity in Karamay, Xinjiang, China | |
| Hu et al. | Risk assessment of soil erosion by application of remote sensing and GIS in Yanshan Reservoir catchment, China | |
| Musser et al. | Characterization of peak streamflows and flood inundation at selected areas in North Carolina following Hurricane Matthew, October 2016 | |
| Nouri et al. | Assessment of Land Use and Land Cover Changes on Soil Erosion Potential Based on RS and GIS, Case Study: Gharesou | |
| Budhathoki et al. | Assessment of Imja Glacier Lake outburst flood (GLOF) risk in Dudh Koshi River Basin using remote sensing techniques | |
| Yildirim et al. | A GIS‐based siting technique for automatic weather stations in Trabzon, Turkey | |
| Jin et al. | Hydrometeorological-modeling-based analysis and risk assessment of a torrential rainfall flash flood in a data deficient area in Wenchuan County, Sichuan Province, China | |
| Cosgrove et al. | Overview and initial evaluation of the Distributed Hydrologic Model Threshold Frequency (DHM-TF) flash flood forecasting system | |
| Bizimana et al. | Cadastral information and erosion modeling for monitoring gullies in mpazi catchment area, Kigali city | |
| Verdin et al. | Probability and volume of potential postwildfire debris flows in the 2012 High Park Burn Area near Fort Collins, Colorado | |
| Bjerklie et al. | Assessment of the spatial extent and height of flooding in Lake Champlain during May 2011, using satellite remote sensing and ground-based information | |
| Bajracharya | Glacial lake outburst flood disaster risk reduction activities in Nepal | |
| Brown et al. | What is the appropriate RAWS network | |
| Abiri | Assessment of Flood Risks in Ifo Local Government Area of Ogun State | |
| Choi | Flood-inundation maps created using a synthetic rating curve for a 10-mile reach of the Sabinal River and a 7-mile reach of the West Sabinal River near Utopia, Texas, 2021 | |
| Jawaid | Glacial lake flood hazard assessment and modelling: a GIS perspective | |
| Thayyen et al. | Visual evidence of constrained area of a cloudburst, 12 June 2018, Tirisha village, Nubra valley, Ladakh, India | |
| Fitzpatrick et al. | Flood of July 2016 in Northern Wisconsin and the Bad River Reservation | |
| Chanda et al. | Glacial Lake Outflow Hazard and Risk Probability in Sikkim | |
| River | Flood Hazard Study Nelansa (Manell) River |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20220121 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |