CN107239910A - The urban waterlogging risk assessment index for coupling population and POI points is built - Google Patents
The urban waterlogging risk assessment index for coupling population and POI points is built Download PDFInfo
- Publication number
- CN107239910A CN107239910A CN201710497484.9A CN201710497484A CN107239910A CN 107239910 A CN107239910 A CN 107239910A CN 201710497484 A CN201710497484 A CN 201710497484A CN 107239910 A CN107239910 A CN 107239910A
- Authority
- CN
- China
- Prior art keywords
- urban
- population
- urban waterlogging
- waterlogging
- city
- 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.)
- Pending
Links
- 238000012502 risk assessment Methods 0.000 title claims abstract description 23
- 230000008878 coupling Effects 0.000 title claims abstract description 7
- 238000010168 coupling process Methods 0.000 title claims abstract description 7
- 238000005859 coupling reaction Methods 0.000 title claims abstract description 7
- 238000004458 analytical method Methods 0.000 abstract description 3
- 230000002265 prevention Effects 0.000 abstract 1
- 241001269238 Data Species 0.000 description 2
- 239000000370 acceptor Substances 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000000034 method Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 206010033799 Paralysis Diseases 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 239000000872 buffer Substances 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000013481 data capture Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000013210 evaluation model Methods 0.000 description 1
- 230000001939 inductive effect Effects 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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
- G06Q50/265—Personal security, identity or safety
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Health & Medical Sciences (AREA)
- Computer Security & Cryptography (AREA)
- Primary Health Care (AREA)
- General Health & Medical Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
A kind of urban waterlogging risk assessment index structure for coupling population and POI points, including step：A, urban waterlogging risk assessment index built based on population and POI points；B, urban waterlogging risk assessment Index Content include：Urban population quantity, urban population density, city POI points quantity, city POI point distribution densities；C, the fragility for assessing with urban population quantity and city POI point quantity two indices urban waterlogging disaster；D, the exposed property for assessing with urban population density and city POI point distribution densities two indices urban waterlogging disaster.The present invention is the important acceptor based on urban waterlogging risk --- urban population and urban public utilities, on the sign exposure basis of analysis urban population and communal facility to urban waterlogging risk, build urban waterlogging risk assessment index, assessment more objective to urban waterlogging security risk, comprehensive is realized, science support is provided for urban waterlogging disaster prevention and reduction management.
Description
Technical field
The present invention relates to a kind of structure of urban waterlogging security risk assessment index, belong to the skill of urban safety risk assessment
Art field.
Background technology
In recent years domestic multiple cities are influenceed by heavy rain, and urban waterlogging occurs again and again, urban transportation paralysis, residential building and public affairs
Build together to build and flooded, serious influence is caused to urban safety and resident living.Research on urban waterlogging risk assessment is more
To be based on GIS technology, simulation model, the problems such as urban waterlogging dangerous, disaster fragility are studied by Scene Simulation, assess and
Predict that waterlogging is dangerous.The index that these research institutes use includes landform, rainfall, draining, road, flooding area, depth of the water submerging, residence
House owed by a citizen room, indoor property etc..
Urban population and urban public utilities are the important acceptors of urban waterlogging disaster, are the weights for assessing urban waterlogging risk
Key element is wanted, it is by the important sign that waterlogging influence degree is urban waterlogging risk.But existing waterlogging risk assessment study is less to be related to
And the communal facility key element that population and city are widely present, Shortcomings are influenceed on waterlogging.Cause one of the reason for this is not enough
It is larger to quantity and distribution situation the progress statistics difficulty of a large amount of communal facilitys in city.City big data develops into solution
This problem provides approach.City big data has the advantages that easily acquisition, quantification degree are high, can make up conventional survey number
According to deficiency.POI points in city are the big datas obtained from network open source information, quantity, position comprising urban public utilities
The information such as put.
The content of the invention
The present invention is based on urban population and POI points, builds urban waterlogging risk assessment index, to assess urban waterlogging peace
Full blast danger.
Problem of the present invention is realized with following technical proposals：With urban population quantity, urban population density, city
POI points quantity, city POI points distribution density build urban waterlogging Risk Assessment Index System.
These parameters build and specifically include following steps：
A, the fragility for assessing with urban population quantity and city POI point quantity two indices urban waterlogging disaster.
B, the exposed property for assessing with urban population density and city POI point distribution densities two indices urban waterlogging disaster.
C, the quantity of city POI points and position represent position and the quantity of the urban public utilities influenceed by waterlogging.
D, with the size of population in urban waterlogging risk area and POI point quantity plus and value represent the crisp of urban waterlogging disaster
Weak property.
E, with urban population density and POI point distribution densities plus and value represent the exposed property of urban waterlogging disaster.
Brief description of the drawings
Fig. 1 Xiamen City 2013-2015 waterloggings space of points is distributed；
Fig. 2 Xiamen City waterlogging risk area.
Embodiment
The present invention assesses the waterlogging risk in each area of Xiamen City using Xiamen waterlogging risk assessment as case, illustrates coupling
The urban waterlogging risk assessment index construction method of population and POI points.Specifically, comprise the following steps：
A, in terms of Flood inducing factors, fragility and exposed property 3 urban waterlogging calamity source is estimated, sees formula 1：
R=H × V × E (1)
Wherein R is risk；H is the danger of natural phenomena；V is fragility；E is exposed property.
Assuming that the same with rainfall intensity of the heavy rain in each area, i.e. heavy rain danger is identical, then waterlogging risk is with fragility
Property and exposed property are estimated.
B, structure urban waterlogging risk assessment index, content include：Urban population quantity, urban population density, city POI
Point quantity, city POI point distribution densities.With urban population quantity and POI point quantity plus and value represent urban waterlogging disaster
Fragility；With the density of population of urban waterlogging risk area and POI point distribution densities plus and value represent the sudden and violent of urban waterlogging disaster
Dew property.
C, urban waterlogging risk evaluation model is set up, see formula 2.
Wherein RiFor the waterlogging value-at-risk in i areas；PijFor the size of population of j-th of the waterlogging risk area in i areas；FijFor in j-th of i areas
The education and medical care facility quantity of flooded risk area；PiaFor the density of population (ten thousand people/square kilometre) in i areas；FitPublic for i areas sets
Apply distribution density (individual/square kilometre).
D, acquisition data.Each Community Population data in Xiamen City are obtained, data provide for Xiamen Bureau of Civil Affairs.Obtain Xiamen City
The POI point datas such as education, medical treatment, data capture method captures for Baidu map.Obtained by high score 1 and Google earth
Satellite remote-sensing image figure.By extracting the data that 2013-2015 networks open press is reported, Xiamen City's waterlogging point letter is obtained
Breath, and digitized by ArcGIS10 softwares, see Fig. 1.
E, the waterlogging risk area for analyzing each area of Xiamen City.Be risk source by waterlogging point, with produce influence it is the most significant away from
As risk area in 0.5 kilometer from risk source border, analyzed using ArcGIS space buffers technological expression, see Fig. 2.
F, calculating each desired value of Xiamen City's waterlogging risk.With reference to Xiamen City's population distribution figure and POI point distribution maps, utilize
The method such as ArcGIS Overlap Analysis and space calculating obtains population and education and medical care communal facility quantity in risk area, is shown in Table
1.The density of population and education and medical care distribution of facilities density in each area of Xiamen City are calculated, 1 is shown in Table.
G, the calculating each area's waterlogging value-at-risk in Xiamen City, are shown in Table 1.
Each desired value of waterlogging risk assessment of table 1 and waterlogging value-at-risk
H, according to result of calculation, assess the waterlogging risk in each area of Xiamen City.
The urban waterlogging risk assessment index that the present invention is set up, is important acceptor --- the urban human based on urban waterlogging risk
Mouth and communal facility, on the sign exposure basis of analysis urban population and communal facility to urban waterlogging risk, build city
Waterlogging risk assessment index, realizes assessment more objective to urban waterlogging security risk, comprehensive, is that urban waterlogging is prevented and reduced natural disasters
The support of offer science is provided.
Claims (3)
1. one kind coupling population and POI（Point of interest）The urban waterlogging risk assessment index of point is built, its feature
It is to comprise the following steps：
A, urban waterlogging risk assessment index built based on urban population and city POI points；
B, urban waterlogging risk assessment Index Content include：Urban population quantity, urban population density, city POI points quantity, city
City POI point distribution densities；
C, the fragility for assessing with urban population quantity and city POI point quantity two indices urban waterlogging disaster；
D, the exposed property for assessing with urban population density and city POI point distribution densities two indices urban waterlogging disaster.
2. the urban waterlogging risk assessment index of coupling population according to claim 1 and POI points is built, its feature exists
In：The quantity of city POI points and position represent position and the quantity of the urban public utilities influenceed by waterlogging.
3. the urban waterlogging risk assessment index of coupling population according to claim 1 and POI points is built, its feature exists
In：With the size of population in urban waterlogging risk area and POI point quantity plus and value represent the fragility of urban waterlogging disaster；With
The exposed property for adding and being worth expression urban waterlogging disaster of urban population density and POI point distribution densities.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710497484.9A CN107239910A (en) | 2017-06-27 | 2017-06-27 | The urban waterlogging risk assessment index for coupling population and POI points is built |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710497484.9A CN107239910A (en) | 2017-06-27 | 2017-06-27 | The urban waterlogging risk assessment index for coupling population and POI points is built |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107239910A true CN107239910A (en) | 2017-10-10 |
Family
ID=59987736
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710497484.9A Pending CN107239910A (en) | 2017-06-27 | 2017-06-27 | The urban waterlogging risk assessment index for coupling population and POI points is built |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107239910A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107832931A (en) * | 2017-10-31 | 2018-03-23 | 上海市政工程设计研究总院（集团）有限公司 | A kind of Modularity analysis method of plain river network region waterlogging risk |
| US10505708B2 (en) | 2018-12-28 | 2019-12-10 | Alibaba Group Holding Limited | Blockchain transaction speeds using global acceleration nodes |
| US10664469B2 (en) | 2018-12-28 | 2020-05-26 | Alibaba Group Holding Limited | Accelerating transaction deliveries in blockchain networks using acceleration nodes |
| US11082239B2 (en) | 2018-12-28 | 2021-08-03 | Advanced New Technologies Co., Ltd. | Accelerating transaction deliveries in blockchain networks using transaction resending |
| CN113282877A (en) * | 2021-07-22 | 2021-08-20 | 中国科学院地理科学与资源研究所 | Natural disaster key hidden danger risk assessment method and device |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103235978A (en) * | 2013-04-01 | 2013-08-07 | 民政部国家减灾中心 | Disaster monitoring and early warning system and method for establishing disaster monitoring and early warning system |
| CN105160889A (en) * | 2015-09-29 | 2015-12-16 | 中山大学 | Multi-source-point collaborative dispersion method for road network traffic flow in urban waterlogging situation |
| CN106156949A (en) * | 2016-06-30 | 2016-11-23 | 广东工业大学 | A kind of rainwater based on waterlogging risk assessment is low affects development project method |
-
2017
- 2017-06-27 CN CN201710497484.9A patent/CN107239910A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103235978A (en) * | 2013-04-01 | 2013-08-07 | 民政部国家减灾中心 | Disaster monitoring and early warning system and method for establishing disaster monitoring and early warning system |
| CN105160889A (en) * | 2015-09-29 | 2015-12-16 | 中山大学 | Multi-source-point collaborative dispersion method for road network traffic flow in urban waterlogging situation |
| CN106156949A (en) * | 2016-06-30 | 2016-11-23 | 广东工业大学 | A kind of rainwater based on waterlogging risk assessment is low affects development project method |
Non-Patent Citations (1)
| Title |
|---|
| 陈鹏等: "城市暴雨积涝灾害风险评价指标体系与概念模型", 《商业经济》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107832931A (en) * | 2017-10-31 | 2018-03-23 | 上海市政工程设计研究总院（集团）有限公司 | A kind of Modularity analysis method of plain river network region waterlogging risk |
| CN107832931B (en) * | 2017-10-31 | 2022-03-29 | 上海市政工程设计研究总院（集团）有限公司 | Modularized analysis method for waterlogging risk in plain water network region |
| US10505708B2 (en) | 2018-12-28 | 2019-12-10 | Alibaba Group Holding Limited | Blockchain transaction speeds using global acceleration nodes |
| US10664469B2 (en) | 2018-12-28 | 2020-05-26 | Alibaba Group Holding Limited | Accelerating transaction deliveries in blockchain networks using acceleration nodes |
| US11032057B2 (en) | 2018-12-28 | 2021-06-08 | Advanced New Technologies Co., Ltd. | Blockchain transaction speeds using global acceleration nodes |
| US11042535B2 (en) | 2018-12-28 | 2021-06-22 | Advanced New Technologies Co., Ltd. | Accelerating transaction deliveries in blockchain networks using acceleration nodes |
| US11082239B2 (en) | 2018-12-28 | 2021-08-03 | Advanced New Technologies Co., Ltd. | Accelerating transaction deliveries in blockchain networks using transaction resending |
| US11082237B2 (en) | 2018-12-28 | 2021-08-03 | Advanced New Technologies Co., Ltd. | Accelerating transaction deliveries in blockchain networks using transaction resending |
| US11151127B2 (en) | 2018-12-28 | 2021-10-19 | Advanced New Technologies Co., Ltd. | Accelerating transaction deliveries in blockchain networks using acceleration nodes |
| CN113282877A (en) * | 2021-07-22 | 2021-08-20 | 中国科学院地理科学与资源研究所 | Natural disaster key hidden danger risk assessment method and device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107239910A (en) | The urban waterlogging risk assessment index for coupling population and POI points is built | |
| Yu et al. | View-based greenery: A three-dimensional assessment of city buildings’ green visibility using Floor Green View Index | |
| Tran et al. | GIS and local knowledge in disaster management: a case study of flood risk mapping in Viet Nam | |
| Song et al. | Resilience-vulnerability balance to urban flooding: A case study in a densely populated coastal city in China | |
| Gaillard et al. | Participatory three-dimensional mapping for disaster risk reduction | |
| Lin et al. | Urban waterlogging risk assessment based on internet open data: A case study in China | |
| Calka et al. | Fine scale population density data and its application in risk assessment | |
| Wamsler et al. | The role of individual adaptive practices for sustainable adaptation | |
| Jessup et al. | Planting Stormwater Solutions: A methodology for siting nature-based solutions for pollution capture, habitat enhancement, and multiple health benefits | |
| Rumbach et al. | Urban disasters beyond the city: Environmental risk in India’s fast-growing towns and villages | |
| Mabrouk et al. | Urban resilience assessment: A multicriteria approach for identifying urban flood-exposed risky districts using multiple-criteria decision-making tools (MCDM) | |
| Abbas et al. | GIS‐based disaster management: A case study for Allahabad Sadar sub‐district (India) | |
| de Mendonca et al. | Integration of census data based vulnerability in landslide risk mapping-The case of Angra dos Reis, Rio de Janeiro, Brazil | |
| Giuliani et al. | Unpacking seismic risk in Italian historic centres: A critical overview for disaster risk reduction | |
| Magarotto et al. | Methodology for the development of 3D GIS models in the Coastal Zone | |
| Akinci | The aftermath of disaster in urban areas: An evaluation of the 1999 earthquake in Turkey | |
| Ndiaye et al. | Detection and ranking of vulnerable areas to urban flooding using GIS and ASMC (spatial analysis multicriteria): a case study in dakar, Senegal | |
| Sathiparan | An assessment of building vulnerability to a tsunami in the Galle coastal area, Sri Lanka | |
| Zahid et al. | Disaster management and Good governance: a review on chattogram landslides | |
| Freire et al. | When the tsunami comes to town-Improving evacuation modeling by integrating high-resolution population exposure. | |
| Owoeye | Assessing Urban Growth Dynamics and Depletion of Agricultural Land Use in Akure Region, Nigeria | |
| Yangki | Impact of urban greening and verticalization on the outdoor thermal comfort: a case study of Thimphu city, Bhutan | |
| de Leon et al. | Physical Vulnerability Assessment to Flooding of Residential Houses Along the Coastal Areas in Santa Rosa City, Laguna, Philippines | |
| Tran et al. | Enhancing community resilience through information management: Flood risk mapping in Central Viet Nam | |
| Naik et al. | Multi-Hazard Risk Vulnerability Assessment, Case of Dehradun, Uttarakhand, India |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20171010 |