Volume XLII-3/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 375-381, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-375-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 375-381, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-375-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  06 Mar 2018

06 Mar 2018

GEOINFORMATION APPROACH FOR COMPLEX ANALYSIS OF MULTIPLE NATURAL HAZARD

V. Nikolova1 and P. Zlateva2 V. Nikolova and P. Zlateva
  • 1Department of Geology and Geoinformatics, University of Mining and Gelogy, 1700 Sofia, Bulgaria
  • 2Institute of Robotics, Bulgarian Academy of Sciences, Sofia, Bulgaria

Keywords: Natural hazards, Geoinformation, GIS, Floods, Landslides, Complex analysis

Abstract. Natural hazards are existence of natural components and processes, which create a situation that could negatively affect people, the economy and the environment. In this concern, they are associated with the probability of negative impacts and they are considered as limiting factors for people's lives and activities. Rising public awareness about natural hazards could improve the quality of life, save financial resources and even save lives. Methodological issues of complex analysis of multiple natural hazards in geographic information system (GIS) environment are presented in the current paper on the example of floods and landslide assessment. The complicated nature of natural hazards and the interrelations between natural components require a complex analysis of natural hazard factors and an integrated assessment taking into account all aspects of different hazards as well as the overall hazard resulting from a probable simultaneous occurrence of several adverse natural phenomena. A special attention is given to the data as one of the most important component of the analysis. Different data formats and particularities of spatial data interpretation in GIS environment are considered. Having regard the nature of the data and the phenomenon being evaluated, different GIS spatial analysis tools (fuzzy overlay, weighted sum, interpolation) are applied together with mathematical analyses. The results of the current research and suggested approach could support decision makers in territorial planning and risk management.