A comparative study of elevation data from different sources for mapping the coastal inlets and their catchment boundaries

Abstract

Mapping coastal inlets and their catchment areas is essential for management of the coastal zone. The coastal inlets are important channels of exchange of nutrients, water and sediment between the land and sea. They are also important elements of the coastal hydrological system and play a vital role in controlling the water flow into the sea during floods. Blocking of the coastal inlets is one of the main causes of flooding in the lower reaches of the major rivers in Sri Lanka. Delineation of the boundaries of inlet catchments is essential for modelling the inlet processes and this is normally done using elevation data. The traditional sources of elevation data are the topographic maps. In Sri Lanka, detailed topographic maps (1:10,000) are available only for a limited area, and the rest of the country is covered by 1:50,000 and 1:63,360 maps. The low resolution maps are not sufficiently detailed in areas of low relief, such as the coastal lowlands. As a result, the catchment boundaries based on these data sources are not accurate enough for inlet studies. Two alternative sources of elevation data that can be used for this type of studies are the shuttle radar topography mission (SRTM) global data set and light detection and ranging (LiDAR) data (5 m) available for a limited area of the coastal belt. This study compares the traditional map data for the Galle district with the SRTM digital elevation models (DEM) at 30 m and 90 m resolutions and LiDAR DEMs. At first, the DEMs derived from all data sources were compared using the cross-sectional profiles. Secondly, a comparison was made using the spot heights obtained from 1:10,000 maps with the corresponding heights from the SRTM 30 m DEM. The 1:10,000 scale agricultural based mapping project (ABMP) (10 k ABMP) was used as the reference data set and all other data products were compared with that. The analysis of the data revealed that the LiDAR data set has the best match with the 10 k ABMP dataset. The SRTM 30 m DEM showed a high level of correlation with 10k ABMP maps at the high elevations, but the match at the low elevations was less as indicated by the low R2 values. However, the SRTM data is marginally better than the 50 k ABMP in the coastal area. This suggests that SRTM 30 m data set is the best data set available for the delineation of inlet boundaries in the coastal areas.