How can spatial decision support systems be used to prevent natural disasters in urban planning?

To protect against natural disaster in urban development works, we should assess the geographical survey data and prepare an action plan according to the place in which the geographical structure, soil type, surrounding rivers and their water level, as well as climate and earthquake zone data should be included in SDSS. Analysis, modeling, and visualization can be done through computer-based systems. In any city, drainage and pollution are the main problems. In such a situation, a plan can also be made for recycling of waste, for which SDSS are computer-based. systems play a very good role so that better planning can be prepared by combining experts with various data.

As an urban planner, my experience with SDSS is related to developing Land Use planning for local settlements in coastal areas of Iran. in this project, we developed an SDSS to evaluate three different scenarios of development considering environmental hazards, preserving the current state and conservation of environmentally valuable areas. the system was great and the decision- making system worked in the best way we expected, but to be honest, working with stakeholders and organizations who are not familiar with these systems and lack of availability of data turned not to be applicable in that region.

SDSS can be used to prevent natural disasters in urban planning by modeling urban resilience and selecting resilient zones in response to natural hazards. Urban planners can use SDSS to identify areas that are considered to have very low resilience depending on the risk attitude.

Until sdss data are not available. Go to every home and educate them what vulnerabilities they have at home and outside and which route is safe for evacuation. People are not sheep and planners are shepherds. People are people and they can apply common sense better than planners if they are sensitized a little bit; and that minimizes state and national rescue burden as well

A spatial planning starting from data collection to the plan formulation stage should also fulfill the rules of disaster analysis from the start of data collection to the plan formulation. When considering disasters, sometimes errors in plan formulation occur because the data being considered does not match. There is a need for big data on regional disasters, so that disaster considerations in spatial planning are better.

??? Integrating continuous flows of spatial data in SDSS (e.g. from IoT sensors and satellites) is essential to have live plans that can adapt as places change. ???? There are petabytes of data out there, however often planners are blinded by too much information. ?? Optimal Cities SDSS, for instance, takes terabytes of spatial data from satellites, authorities and GIS models and transforms them in simple web maps locating and prioritising vulnerabilities in relation to environmental and socio-economic risks.

the best practice for SDSS can be related to natural hazards. identifying the high-risk areas specifically in flood-related hazards or landslide-prone-slopes using this system can help planners prevent disasters for urban settlements and industrial zones. one of the applicable usages of SDSS in this field can be zoning, and land use regulations for each level of risk and probability of hazards.

All this is true, but I would add the SDSS really come into they own when you add dynamic, scenario-based features that render how spatial features will be influenced by climate change. Urban planners need to be able to say not only what goes where and why but whether you need something in the first place. For example, knowing that an area (e.g. southern Myanmar, coastal Jamaica, Jakarta etc. etc.) may be more frequently or constantly inundated should help guiding decisions on the type of investments required: would I need a road at all, if people need to be relocated in the long-run? Or should I invest in something else? Is it worth protecting a coastal stretch for people to inhabit those areas, or rather invest in guided migration?

one of the major benefits of using SDSS is that the results and the data are more tangible and practical when it comes to practice. interacting with different stakeholders, using SDSS can enhance the chance of their cooperation and involvement in the practice. and as it is mentioned in the text, the role of SDSS in the resilience of urban areas can be significant.

sharing my own experience, from the country of my residence, I think the main challenge is the availability of updated, accurate data. Living in Iran, we do not have access the the estate-of-the art and updated technology and data and most of the time, cleaning, updating, and validating data consumes major time and workforce and imposes a major cost to the project.

The best way to overcome these challenges is to be updated. An urban planner needs to keep up with the new technology, trends, applications, and Geographic systems available out there. I see that many of us planners, do not have real knowledge of spatial data or are not really confident with the GI products. on the other hand, the unattainability of data in the country of my residence has worsened the situation. So, I highly belive that the only way to overcome this issue is to be more engaged with the available data.

SDSS is a valuable tool that can help to prevent and mitigate the impacts of natural disasters. The tool can be used in a variety of ways like assessing the risk in urban areas which will give informed decision-making to avoid high-risk areas. The tool may also simulate numerous disaster scenarios to assist planners in understanding potential implications and developing readiness and response strategies. It teaches citizens about disaster risk and preparedness in order to better equip them to take proactive steps to safeguard themselves and their communities. In summary, the SDSS can guide proactive decision-making and improve disaster resilience in urban environments.