**6. Conclusions**

**Working steps Time investment (min)**

Preparation of basic data for the area in question (DEM, maps, orthophotos, images) 10 20 30 Choosing and fixing control points (CPs) 10 30 90 Camera calibration 5 15 30 Digitalizing target objects 5 15 20 Import/export 5 5 5 Total 35 90 175

**Table 2.** Average time investment for individual working steps when processing an image with the WSL monoplotting tool.

season of 2017/2018, which caused a partial blanketing of the snow bridges in the upper part of the area in question. On January 24, 2018, which was 2 days after the end of a heavy snowfall event, a helicopter recognition mission was organized and the snow bridge area was photo-

**Figure 8.** Snow bridges (Adelboden, 2018). (a) Original oblique image of the snow bridge constructions with control points. (b) Digitalization of the snow bridges. (c) Projection of the digitalized bridges on the current orthophoto

Through the georeferencing process of the MPT\_2.0 (**Figure 8b**), the bridges were digitalized and exported to a GIS file, making it possible to identify the blanketed snow bridge parts,

The MPT\_2.0 has proven to be a highly suitable instrument for georeferencing and documenting the impact of geophysical (landslides, avalanches) and hydrological (debris flows, floods) natural hazards. As reported in **Table 1**, the achieved theoretical precision for the presented study cases ranges from decimeters to a few meters, which is more than acceptable for practical purposes. In addition to the image quality and its resolution in particular, the precision of the system additionally depends on the DEM resolution and on the number, clarity, and

graphed in order to document the blanketed parts (**Figure 8a**).

which may fail in their protection function (**Figure 8c**).

highlighting in blue the parts covered by snow.

118 Natural Hazards - Risk Assessment and Vulnerability Reduction

**5. Discussion**

**Min Mean Max**

The main aim of using the WSL monoplotting tool (MPT\_2.0) is to document in real time and reconstruct the effects of natural events before damage and signs in the landscape are removed or disappear. In this respect, the tool was found to be very flexible, enabling the operator to combine images from different epochs, and points of view that describe the same event. The possibility of georeferencing such images by reconstructing the unknown shooting point enables the use of oblique aerial photographs taken from helicopters, which in turn, opens the door to documenting natural events in highly inaccessible sites (see Example 5, blanketed snow bridges).

When suitable photographic material exists, even events dating back more than a century can be reconstructed with very satisfactory precision (see Example 1, Sasso Rosso area, Airolo). Similarly, also the extent and the severity of past pest attacks, diseases or wildfires can be retrospectively reconstructed provided, there is a suitable photographic documentation. The MPT\_2.0 could also be very useful in combination with the surveillance system cameras for automatic wildfire detection. When oblique images of the landscape from such fixed cameras are georeferenced in the monoplotting system, the pixel coordinates of the fire detection can also be immediately expressed in real-world coordinates (including the possible error) when a fire ignition spot is detected.

[4] Klinke A, Renn O. Nachhaltiger Umgang mit natürlichen Risiken: antizipativ, integrativ und interdisziplinär. Schweizerische Zeitschrift für Forstwesen. 2011;**162**(12):442-453.

Using the Monoplotting Technique for Documenting and Analyzing Natural Hazard Events

http://dx.doi.org/10.5772/intechopen.77321

121

[5] Schwendtner B, Papathoma-Kohle M, Glade T. Risk evolution: How can changes in the built environment influence the potential loss of natural hazards? Natural Hazards and

[6] Frei CR, Schöll R, Fukutone S, Schmidli J. Vidale PL future changes of precipitation extremes in Europe. Journal of Geophysical Research. 2006;**111**:D06105. DOI: 10.1029/

[7] Fowler HJ, Ekström M, Blenkinsop S, Smith AP. Estimating change in extreme European precipitation using a multimodel ensemble. Journal of Geophysical Research. 2007;**112**:

[8] Beniston M, Stephenson DB, Christensen OB, Ferro CAT, Frei C, Goyette S, Halsnaes K, Holt T, Jylhä K, Koffi B, Palutikof J, Schöll R, Semmler T, Woth K. Future extreme events in European climate: An exploration of regional climate model projections. Climatic

[9] Marty C, Phillips M, Lehning M, Wilhelm C, Bauder A.Klimaänderung und Naturgefahren in Graubünden. Schweizerische Zeitschrift für Forstwesen. 2009;**160**(7):201-209. DOI:

[10] Papathoma-Köhle M, Promper C, Glade T. A common methodology for risk assessment and mapping of climate change related zazards—Implications for climate change adap-

[11] Hollenstein K, Hess J. Integrales Management von gravitativen Naturrisiken in der Schweiz. Schweizerische Zeitschrift für Forstwesen. 2011;**162**(12):454-463. DOI: 10.3188/

[12] Nquot I, Kulatunga U. Flood mitigation measures in the United Kingdom. In: Proceedings of the 4th International Conference on Building Resilience, Incorporating the 3rd Annual Conference of the Android Disaster Resilience Network, Manchester (United Kingdom).

[13] Garcia C, Blahut J, Angignard M, Pasuto A. The importance of the lessons learnt from past disasters for risk assessment. In: VanAsch T, Corominas J, Greiving S, Malet JP, Sterlacchini S, editors. Mountain Risks: From Prediction to Management and Governance.

[14] Uhlemann S, Thieken AH, Merz B. A quality assessment framework for natural hazard event documentation: Application to trans-basin flood reports in Germany. Natural Hazards and Earth System Sciences. 2014;**14**:189-208. DOI: 10.5194/nhess-14-189-2014

[15] Adams MS, Fromm R, Lechner V. High-resolution debris flow volume mapping with unmanned aerial systems (UAS) and photogrammetric techniques. July 12-19, 2016.

Earth System Sciences. 2013;**13**:2195-2207. DOI: 10.5194/nhess-13-2195-2013

DOI: 10.3188/szf.2011.0442

D18104. DOI: 10.1029/2007JD008619

Change. 2007;**81**:71-95. DOI: 10.1007/s10584-006-9226-z

tation policies. Climate. 2016;**4**(8):1-23. DOI: 10.3390/cli4010008

Springer; 2014. pp. 275-284. DOI: 10.1007/978-94-007-6769-0\_9

2005JD005965

10.3188/szf.2009.0201

szf.2011.0454

pp. 749-755

September 8-11, 2014. pp. 81-87

In contrast, less practicable is the use of the MPT\_2.0 for the real-time documentation of dynamic processes such as the localization of a fire line front in fast spreading, large wildfires. In such cases, unmanned aerial vehicles (UAVs, drones) may be most suitable for producing real-time, georeferenced images of the fire front, or residual burning.

At present, the 2.0 release of the WSL Monoplotting Tool (MPT 2.0) is available at the project site (www.wsl.ch/monoplotting) and freely usable for research purposes. Please refer to this webpage for details on the terms and conditions of use, services, and tutorial options.
