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Thank you for sharing!

thanx for sharing

Thanks for sharing

I'm sorry for the extremely delayed answer but I just saw it. Here's an alternative approach in case the requested clarification is still pending. It all depends on the scale of implementation: Regional (smaller than 1/25.000, ie. 1/50.000 etc), Local (greater than 1/25.000, ie. 1/10.000, 1/5.000) or even site-specific (greater than 1/5.000, ie 1/2.500 ,1/1000 etc) Data accuracy (especially regarding elevation) define in any cases the accuracy of outputs. I would suggest a two step procedure: use morphological models to define "flood prone" areas; for instance the Topographic Wetness Index or TWI. References: Beven, K. J., and M. J. Kirkby. "A physically based, variable contributing area model of basin hydrology/Un modèle à base physique de zone d'appel variable de l'hydrologie du bassin versant." Hydrological Sciences Journal 24.1 (1979): 43-69. Sørensen, R., U. Zinko, and J. Seibert. "On the calculation of the topographic wetness index: evaluation of different methods based on field observations." Hydrology and Earth System Sciences Discussions 2.4 (2005): 1807-1834. [12] Boehner, J., Koethe, R. Conrad, O., Gross, J., Ringeler, A., Selige, T.: Soil Regionalisation by Means of Terrain Analysis and Process Parameterisation. In: Micheli,E., Nachtergaele,F., Montanarella,L.[Ed.]: Soil Classification 2001. European Soil Bureau, Research Report No. 7, EUR 20398 EN, Luxembourg. pp.213-222, 2002 Manfreda S., Di Leo M., Sole A.: Detection of Flood-Prone Areas Using Digital Elevation Models. Journal of Hydrologic Engineering, 16 (10):781-790, 2011, (2011). Rafael De Risi (2013): “A Probabilistic bi-scale framework for Urban Flood Risk Assessment, PhD Thesis, Dept. of Structures for Engineering and Architecture, University of Naples Federico II, p.198, Naples. Papatheodorou K., Tzanou E., Ntouros K. "Flash Flood Hazard Prevention using Morphometric and Hydraulic models. An example implementation. "International Congress on “Green Infrastructure and Sustainable Socities/Cities” GreInSus’ 2014. Maftei C., Papatheodorou K., Flash flood prone area assessment using geomorphologic and hydraulic models, Journal of Environmental Protection and Ecology (JEPE), Vol. 16(1), pp. 63-75, ISSN 1311-5065, 2015. This procedure provides QUALITATIVE outputs; ie. consider the output as a map of the gradually flooded areas with increasing amounts of storm water. Data required include ONLY topography and the methodology provides reliable outputs with an accuracy relative to the input topographic data (the greater the scale the more accurate - but it's about defining susceptibility and NOT hazard). In case topographic maps of a large scale (1/2.500 or greater....1/1000 etc) are not available, this stage will help you focus in specific "Flood Prone" areas where (2nd stage) you are going to need large scale topo maps, in order to assess flooding parameters (re- occurrence period, flood water flow velocity, flood extend and flood depth). All these parameters will help you define the level of damage in the area. Data requirements for this 2nd stage, which can be implemented using HEC-RAS, also include rainfall intensity (and manning coeffcients). For the implementation, I would suggest using QGIS or ArcGIS for the 1st stage, since both include plug-ins to create HEC-RAS geometries (cross sections). To my opinion QGIS is far more efficient and stable.

There has been a lot of literature around this matter. Just google "lineament algorithm" or "lineament detection" and you'll find a whole lot of it. To my opinion, you'd better proceed with visual inspection and interpretation and in that case there's also a lot of literature too, regarding FCCs, band ratios and processes that "reveal" abrupt changes which correspond to lineaments.

It will work but you MUST have taken the photographs in a way that there is the SAME COMMON area in PAIRS of them (the pairs you will use to create a stereoscopic view-a real 3D solid). So, by taking photos with an overlapping area of about 60% of each photo will give you the ability to use, not just pairs but, series of them to create real 3D representations of the ground surface. Computer memory and processing power will be the limits of the 3D area you can produce each time.

GPR data have to be processed first (filtered, enhanced), then converted to image files (jpg, bmp, tif etc) and only then you can import those images as "slices" in some software that can create 3D representations using those "slices". An alternative solution is to define coordinates in every "slice" (relative will do) and use the nviz module of GRASS GIS to make a 3D representation of those "slices" (GPR recordings).