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Natural disasters that cause tremendous material harm and threaten human lives, infrastructure, and economic and social activities become more frequent. While most material and human casualties are the effects of sudden and brief natural disasters, it is not possible to disregard long-term disasters, most frequently triggered by climate change. Damage from long-term disasters is quite significant and hampers the sustainability of the economy and life in densely populated cities. Following climate change, it is concluded that special attention should be paid to coastal cities, cities along rivers and the potential risks of possible disasters should be reduced before they materialize. The reduction of disaster risk is an endeavor involving various professional fields, viewpoints, and stakeholders. An integrated approach that brings together all the necessary elements is therefore required. The planning for protection against natural disasters and in the very moments when it occurs, it is necessary to quickly obtain reliable data to coordinate activities in the field well. However, there are problems in the field with the availability, access, and spatial data use. In this sense, the Spatial Data Infrastructure (SDI) can provide an appropriate framework for sharing spatial data through the cooperation of administration, public, and private institutions and citizens.

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When reconstructing existing or constructing completely new intersections, the main problem is determining the type of future intersection. Capacity is one of the key indicators that influence the choice of traffic control type. In this paper, using different scenarios of theoretical traffic flow distributions and traffic volume scenarios, the authors have determined the applicability area of two-lane roundabouts. The results obtained were used to improve the existing applicability diagrams of the various intersection types presented in several issues of US Highway Capacity Manuals (US HCM). Capacity in each scenario is determined using HCM 2010 and Hagring methods with practically obtained values of the time gap acceptance parameters.

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