Disaster Management using Geospatial Technology

Introduction

Disaster mapping is the drawing of areas that have been through excessive natural or man-made troubles to the normal environment where there is a loss of life, property, and national infrastructures. Remote sensing has a deep-rooted application in disaster mapping and management. Various disasters like earthquakes, landslides, floods, fires, tsunamis, volcanic eruptions, and cyclones are natural hazards that kill lots of people and destroy property and infrastructures every year. Landslides are the most regular geological vulnerabilities in mountain regions. Remotely sensed data can be used very efficiently to assess the severity and impact of damage due to these disasters. In the disaster relief phase, GIS, grouped with a global positioning system (GPS) is extremely useful in search and rescue operations in areas that have been devastated and where it is difficult to find one’s bearings. It is also helpful in policy making related to disaster management such as NDRF etc.

 

Techniques

Remote sensing data is recorded in a wide spectrum of optical, radar, thermal, and lidar forms. All these contribute differently to mapping and assessing any damage. For instance, thermal data helps gauge any damage relating to heat signatures such as explosions or gas leaks, etc. Radar and lidar data can be effectively used to handle events such as earthquakes and landslides. Optical data is used to map surface damage such as destroyed buildings etc, digital elevation models and other indices are used to assess floods. Temporal change detection is one of the most used techniques to determine the severity of the damage. Pre and Post images of the disaster/event are compared to assess the change in terms of damage.

 

Flood Hazard mapping using Remote sensing and GIS

 Remote sensing and GIS help in flood hazard or risk mapping for land use planning in flood-prone areas. Flood hazard depends on various factors such as Surface slope, amount of rain, drainage density, soil type, and texture, etc. There are series of steps to generate a Flood hazard map. Calculate elevation accuracy using control points, calculate surface slope and drainage density using drainage network information, extract the main channel from the draining network. After all the calculations, a model can be prepared using GIS modelling tools and hydrological parameters can be calculated using any hydrological modelling software. The last step is to generate a Flood hazard map by integrating all the calculated parameters using any multi-criteria analysis tool provided by GIS software.

 

 

 

Forest fire risk zone analysis and mapping using Remote sensing

Forest fire is caused by either natural phenomenon such as high atmospheric temperature, lightning, etc., or by human activities. Forest fire risk zone analysis and mapping are necessary to prevent the spread of fire by detecting the areas where fire can start and easily spread. Remote sensing provides various techniques to find fire risk zone areas such as Vegetation indices. Biomass from plants and trees can be decreased due to fire and this reduced amount depends upon the harshness of fire. Vegetation indices of two satellite images (pre- and post-fire images) can be calculated to compare and analyse the change before and after the fire. The correlation between detected forest fire risk and actual forest fire risk zone can be calculated. Forest fire risk zone map can be generated using any Remote sensing software.

 

 

Application

The application of remote sensing and GIS has become a well-developed and successful tool in disaster management, as we have our location observation programmes and the requisite for hazard mitigation and monitoring rank high in the planning of new satellites. GIS allows for the combination of different kinds of data using models. It allows for the combination of the different kinds of spatial data with non-spatial data, attributes data, and uses them as useful information in the various stages of disaster management. Moreover, the government heavily relies on this data for disaster response-related policy making.

 

Conclusion

In the present context, due to scientific advances, it has become easier to carry out these operations efficiently. Studies have helped in making it possible to forecast and simulate disaster occurrences concerning specific locations – helping in the initial stages of search and rescue operations. Techniques like satellite imagery and GIS help to identify disaster-prone areas, zoning them according to risk magnitudes, inventory populations, and assets at risk, and simulating damage scenarios. These tools are even useful in managing disasters as they provide instant access to information required in management decisions.