Recreating the 2005 lahar flow in Panabaj, Guatemala as a basis for assessing methods of merging DEMs of differing resolutions.

With the development of new technologies and methods for collecting elevation data, high resolution DEMs are becoming increasingly available, though limitations can often leave datasets incomplete. This project set out to assess methods for merging together multiple DEMs with varying resolutions for use in overland flow modelling. The study area for this project is Panabaj, Guatemala which saw significant loss of life and property as a result of a lahar flow in October 2005. In the years since, the population has begun to rebound, leading to an increased number of people at risk of a similar event. The first stage of this project was to recreate the 2005 lahar using the LaharFlow software using a complete 10m DEM, informed by on-site measurements and observations made soon after the lahar event. Following this, a number of DEMs would be produced using various merging techniques, combining 10m AW3D data with 30m SRTM data, across two scenarios where the high resolution data was used in either the Western or Eastern half of the flow area. By running the same LaharFlow parameters over these merged DEMs, and comparing results from models running on complete and merged DEMs, the effects of the merging techniques on overland flow simulations were be assessed. The results showed that the three DEM merging methods yielded similar results, however models where high resolution data was used in the Western half (containing the inundation area and flow terminus) yielded consistently better results, indicating that the accuracy of topographic data is plays a greater role in shallower areas where the flow is slower. In order to facilitate engagement with the local and external stakeholders with varying experience in using spatial data, Blender was used to attempt to produce more accessible model outputs, taking lessons learned from participatory mapping exercises in Guatemala

Improvements to DEM merging with r.mblend

r.mblend is an implementation of the MBlend method for merging Digital Elevation Models (DEMs). This method produces smooth transitions between contiguous DEMs of different spatial resolution, for instance, when acquired by different sensors. r.mblend is coded on the Python API provided by the Geographic Resources Analysis Support System (GRASS), being fully integrated in that GIS software. It introduces improvements to the original method and provides the user with various parameters to fine tune the merging procedure. This article showcases the main differences between r.mblend and two conventional DEM merge methods: Cover and Average.</p

Improvements to DEM merging with r.mblend

r.mblend is an implementation of the MBlend method for merging Digital Elevation Models (DEMs). This method produces smooth transitions between contiguous DEMs of different spatial resolution, for instance, when acquired by different sensors. r.mblend is coded on the Python API provided by the Geographic Resources Analysis Support System (GRASS), being fully integrated in that GIS software. It introduces improvements to the original method and provides the user with various parameters to fine tune the merging procedure. This article showcases the main differences between r.mblend and two conventional DEM merge methods: Cover and Average.</p