Author(s): Dr. Manzul Kumar Hazarika
Elements-at-risk are the objects such as buildings, infrastructures, population etc. that are exposed to one or more hazards and they are likely to be get adversely affected by the hazards. The way in which the amount of elements-at-risk are characterized (e.g. as number of buildings, number of people, economic value or the area of qualitative classes of importance) also defines the way in which the risk is presented to the end users. There are many different types of elements at risk, and also many different ways to classify them. Table below gives an example of such a classification.
Classification of elements at risk
Physical elements Buildings: Urban land use, construction types, building height, building age, total floor space, replacement costs. Monuments and cultural heritage |
Population Density of population, distribution in space, distribution in time, age distribution, gender distribution, handicapped, income distribution |
Essential facilities Emergency shelters, Schools, Hospitals, Fire Brigades, Police, |
Socio-economic aspects Organization of population, governance, community organization, government support, socio-economic levels. Cultural heritage and traditions. |
Transportation facilities Roads, railway, metro, public transportation systems, harbor facilities, airport facilities. |
Economic activities Spatial distribution of economic activities, input-output table, dependency, redundancy, unemployment, economic production in various sectors. |
Life lines Water supply, electricity supply, gas supply, telecommunications, mobile telephone network, sewage system. |
Environmental elements Ecosystems, protected areas, natural parks, environmentally sensitive areas, forests, wetlands, aquifers, flora, fauna, biodiversity. |
Source: Guidebook on Multi-hazard Risk Assessment, ITC.
Elements at risk inventories can be carried out at various scale levels, depending on the requirements of the risk study. The table below provides and an overview of scales in which the elements-at-risk can be mapped and the risk assessment can be done at these scales based on certain basic spatial units such as municipalities, wards or even individual buildings. However, risk assessments at individual building level are often avoided due to large volume of information required, high cost, uncertainty in data and models, and more importantly legal consequences.
Elements at risk mapping versus mapping scale
Elements at risk type |
Scale of analysis |
|||
---|---|---|---|---|
Small < 1:100,000 |
Medium 25,000-50,000 |
Large 10,000 |
Detailed >1:10,000 |
|
Buildings |
By Municipality
|
Mapping units
|
Building footprints
 |
Building footprints
|
Transportation networks |
General location of transportation networks |
Road & railway networks, with general traffic density information |
All transportation networks with detailed classification, including viaducts etc. & traffic data |
All transportation networks with detailed engineering works & detailed dynamic traffic data |
Lifelines |
Main power lines  |
Only main networks
 |
Detailed networks:
|
Detailed networks and related facilities:
|
Essential facilities |
By Municipality
|
As points
|
Individual building footprints
|
Individual building footprints
|
Population data |
By Municipality
 |
By ward
 |
By Mapping unit
|
People per building
|
Agriculture data |
By Municipality
|
By homogeneous unit,
|
By cadastral parcel
|
By cadastral parcel, for a given period of the year
|
Economic data |
By region
|
By Municipality
|
By Mapping unit
|
By building
 |
Ecological data |
Natural protected areas with international approval |
Natural protected area with national relevance |
General flora and fauna data per cadastral parcel. |
Detailed flora and fauna data per cadastral parcel |
Source: Guidebook on Multi-hazard Risk Assessment, ITC.
One of the most important spatial attributes for elements-at-risk inventory is the land use. The land use determines to a large extend the type of buildings that can be expected in the unit, the economic activities that are carried out, the density of the population in different periods of the day, etc.
(v. 27/3/2016. 13/6/2016)