GIS-based route planning in landslide-prone areas
Many parts of the world with young mountain chains, such as the Himalayas, are highly susceptible to landslides. Due to general ruggedness and steep slopes, roads provide the only way of transportation and connectivity in such terrains. Generally, landslide hazards are overlooked during route planning. In this study, in a test area in the Himalayas, various thematic layers, viz. landslide distribution, landslide hazard zonation, landuse/landcover, drainage order and lithology are generated and integrated using Remote Sensing - GIS techniques. The integrated data layer in raster form has been called a `thematic cost map' and provides an estimate of the cost of route development and maintenance. The relative cost assignment is based on experts' knowledge. Route planning is based on neighbourhood analysis to find various movement possibilities from a pixel to its immediate neighbours. A number of patterns such as those analogous to movements in chess games have been considered. Two new neighbourhood patterns, named here Knight31 and Knight32, have been conceived in addition to commonly used Rook, Bishop and Knight patterns. The neighbourhood movement cost for moving from one pixel to a connected neighbour has been calculated for a 767 pixel window considering distance, gradient cost and thematic cost. Dijkstra's algorithm has been applied to compute the least-cost route between source and destination points. A few examples are presented to show the utility of this approach for a landslide-safe automatic route planning for a highly rugged hilly terrain.
gis route planning landslide remote sensing