Wie tragen Satellitenbilder zu einer effektiven Katastrophenplanung bei?

Satellite data provide up-to-date synoptic view of an area, that help to identify vulnerable population and critical infrastructure. Additionally, satellite data can integrated with other ancillary data to model and predict the level of vulnerability of an area.

Satellite images offer up-to-date, detailed information on disaster-stricken regions, helping responders gauge damage severity and locate crucial infrastructure issues. This data assists in prioritizing aid efforts by pinpointing areas requiring urgent attention and directing resource distribution. Moreover, it supports ongoing monitoring of evolving conditions like weather changes or additional risks, enabling adaptive response tactics. Overall, satellite imagery improves the effectiveness and organization of disaster response planning by providing a thorough grasp of on-ground circumstances.

When GIS is used with other existing Machine learning Models/Algorithms the prediction element is brought out well and the accuracy level can be determined.

Satellite imagery combined with environmental and weather data will enable the identification of places that are vulnerable to disaster and their degree of vulnerability. Disaster vulnerability assessment can be carried out using GIS multi-criteria analysis, and results presented in raster format. Results of disaster vulnerability assessment can be overlaid on satellite imagery to have a better understanding of the areas/elements at risk, and this will enhance the understanding of (non-technical) policymakers and drive them to take proactive measures like modification of building structures, improved early warning system and expansion of drainage and waterways.

Satellite images are crucial in disaster management as they enable rescuers to get swift information about the extent of the disaster damage, affected population and land cover (features and properties) during a disaster, facilitating search and rescue operations. Also, using satellite images will provide results on the degree of damages and prompt effective post-disaster compensation/support for the affected people. For example, using pre and post-disaster images after a flood disaster with a land cover map will provide quantitative and visual information on the damaged features and infrastructures. Satellite imagery is more efficient than the survey-based approach, which is time-consuming and inefficient with large-scale disasters.

During and after a disaster, satellite images provide high-resolution, real-time data of affected areas, allowing emergency responders to assess the extent and severity of damage quickly. By analyzing satellite imagery, responders can identify critical infrastructure damage, such as roads, bridges, and buildings, and prioritize areas for intervention. Furthermore, satellite imagery aids in assessing the impact on natural resources, such as forests, water bodies, and agricultural land, facilitating informed decision-making for resource allocation and environmental recovery efforts.

Remote Sensing/ Photogrammetry data can be analysed and the output will be of good quality without having to go to the ground to confirm or check on the status

Satellite imagery with high temporal frequency can help to know safe routes for evacuation plans during a disaster and prevent traffic congestion. Also, near-real-time imagery can help motorists trying to navigate during a disaster to avoid danger by letting them identify roads or bridges that have been affected or damaged during a disaster.

There exists numerous indices that can be used to monitor the status of the environment such as; NDVI(Normalized Difference Vegetation Index), NDWI(Normalized Difference water Index), LST(Land Surface Temperature), SMI(Soil Moisture Index), SBI(Soil Bareness Index) among others that can be computed through the use of satellite images to determine the status of the environment health, growth or deterioration.