Mapping and classifying drainage ditches in forested landscapes usingLiDAR data

Most of the long-term operational infrastructure, including the drainage ditch network, has been developed before compliance with climate change was included in the planning process. Therefore, it is essential to obtain accurate data on the location and condition of the ditch network in order to be able to assess its suitability for foreseeable conditions and the need for improvement measures. The aim of this study is to develop a mapping method for identification and classification of the drainage ditch network, which can be used for surface runoff modeling and to increase accuracy of estimation of greenhouse gas (GHG) and carbon emissions. The study area consists of 20 objects throughout Latvia with a total area of 175 km². Digital elevation models (DEMs) in two resolutions, which were created using three different interpolation methods, were used for the analysis. Several multi-level data filtering methods were applied to identify and classify ditch network, including flow patterns, which can be used in surface runoff process. The method we developed correctly identified 85–89 % of ditches, depending on the DEM used, in comparison to the reference data. Mapped ditches are located within 3 m range of the reference data in 89–93% of cases. Ditch properties were identified within DEM resolution accuracy. The elaborated model is robust and uses openly available source data and can be used for large scale ditch mapping with sufficient accuracy necessary for hydrological modelling and GHG accounting in the national inventories.