An efficient assignment of drainage direction over flat surfaces in raster digital elevation models (original) (raw)
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The assignment of drainage direction over flat surfaces in raster digital elevation models
Journal of Hydrology, 1997
Drainage direction assignment over flat surfaces in raster Digital Elevation Models (DEM) has been a stubborn problem for DEM processing methods. A new approach that improves upon current methods of flat surface treatment is presented. The approach is based on the recognition that in natural landscapes drainage is generally away from higher and towards lower terrain. To produce such a drainage, DEM elevations of a flat surface are modified to impose two gradients: one away from higher terrain, and one towards lower terrain. Subsequent processing of the DEM produces a drainage pattern over the flat surface that is topographically consistent and exhibits flow convergence properties. The proposed approach is not restricted by the shape of the flat surface, the number of outlets on its edge, or the complexity of the surrounding topography. A comparison with the drainage pattern of an established method that displays the 'parallel flow' problem shows significant improvements in producing realistic drainage patterns. The proposed approach extends automated DEM processing to digital landscapes for which existing methods cannot provide adequate flow directions over flat surfaces to conduct a drainage analysis. The necessary algorithmic details for implementation of the approach are provided. © 1997 Elsevier Science B.Y.
Computers & Geosciences, 2016
Depressions are common features in raster digital elevation models (DEMs) and they are usually filled for the automatic extraction of drainage networks. Among existing algorithms for filling depressions, the Priority-Flood algorithm substantially outperforms other algorithms in terms of both time complexity and memory requirement. The Priority-Flood algorithm uses a priority queue to process cells. This study proposes an efficient variant of the Priority-Flood algorithm, which considerably reduces the number of cells processed by the priority queue by using region-growing procedures to process the majority of cells not within depressions or flat regions. We present three implementations of the proposed variant: twopass implementation, one-pass implementation and direct implementation. Experiments are conducted on thirty DEMs with a resolution of 3m. All three implementations run faster than existing variants of the algorithm for all tested DEMs. The one-pass implementation runs the fastest and the average speed-up over the fastest existing variant is 44.6%.
2014
Depressions (or pits) are low areas within a digital elevation model that are surrounded by higher terrain, with no outlet to lower areas. Filling them so they are level, as fluid would fill them if the terrain were impermeable, is often necessary in preprocessing DEMs. The depression-filling algorithm presented here—called Priority-Flood—unifies and improves on the work of a number of previous authors who have published similar algorithms. The algorithm operates by flooding DEMs inwards from their edges using a priority queue to determine the next cell to be flooded. The resultant DEM has no depressions or digital dams: every cell is guaranteed to drain. The algorithm is optimal for both integer and floating-point data, working in O(n) and O(n log2 n) time, respectively. It is shown that by using a plain queue to fill depressions once they have been found, an O(m log2 m) time-complexity can be achieved, where m does not exceed the number of cells n. This is the lowest time complexity of any known floating-point depression-filling algorithm. In testing, this improved variation of the algorithm performed up to 37% faster than the original. Additionally, a parallel version of an older, but widely-used depression-filling algorithm required six parallel processors to achieve a run-time on par with what the newer algorithm's improved variation took on a single processor. The Priority-Flood Algorithm is simple to understand and implement: the included pseudocode is only 20 lines and the included C++ reference implementation is under a hundred lines. The algorithm can work on irregular meshes as well as 4-, 6-, 8-, and n-connected grids. It can also be adapted to label watersheds and determine flow directions through either incremental elevation changes or depression carving. In the case of incremental elevation changes, the algorithm includes safety checks not present in other algorithms.
A flooding algorithm for extracting drainage networks from unprocessed digital elevation models
Computers & Geosciences, 2013
A new method for extracting the drainage network from a digital elevation model (DEM) is presented. It is based on the well-known D8 approach that simulates the overland flow but uses a more elaborate water transfer model that is inspired by the natural behaviour of water. The proposed solution has several advantages: it works on unprocessed DEMs avoiding the problems caused by pits and flats, can generate watercourses with a width greater than one cell and detects fluvial landforms like lakes, marshes or river islands that are not directly handled by most previous solutions.
Carving and adaptive drainage enforcement of grid digital elevation models
Water Resources Research, 2003
1] An effective and widely used method for removing spurious pits in digital elevation models consists of filling them until they overflow. However, this method sometimes creates large flat regions which in turn pose a problem for the determination of accurate flow directions. In this study, we propose to suppress each pit by creating a descending path from it to the nearest point having a lower elevation value. This is achieved by carving, i.e., lowering, the terrain elevations along the detected path. Carving paths are identified through a flooding simulation starting from the river outlets. The proposed approach allows for adaptive drainage enforcement whereby river networks coming from other data sources are imposed to the digital elevation model only in places where the automatic river network extraction deviates substantially from the known networks. An improvement to methods for routing flow over flat regions is also introduced. Detailed results are presented over test areas of the Danube basin.
Parallel identification and filling of depressions in raster digital elevation models
International Journal of Geographical Information Science, 2016
With the increasing sizes of digital elevation models (DEMs), there is a growing need to design parallel schemes for existing sequential algorithms that identify and fill depressions in raster DEMs. The Priority-Flood algorithm is the fastest sequential algorithm in the literature for depression identification and filling of raster DEMs, but it has had no parallel implementation since it was proposed approximately a decade ago. A parallel Priority-Flood algorithm based on the fastest sequential variant is proposed in this study. The algorithm partitions a DEM into stripes, processes each stripe using the sequential variant in many rounds, and progressively identifies more slope cells that are misidentified as depression cells in previous rounds. Both Open Multi-Processing (OpenMP)and Message Passing Interface (MPI)-based implementations are presented. The speed-up ratios of the OpenMP-based implementation over the sequential algorithm are greater than four for all tested DEMs with eight computing threads. The mean speed-up ratio of our MPI-based implementation is greater than eight over TauDEM, which is a widely used MPI-based library for hydrologic information extraction. The speed-up ratios of our MPI-based implementation generally become larger with more computing nodes. This study shows that the Priority-Flood algorithm can be implemented in parallel, which makes it an ideal algorithm for depression identification and filling on both single computers and computer clusters.
Drainage networks from grid digital elevation models
Water resources research, 1991
Current algorithms that deduce the drainage network from a digital elevation model (DEM) represented by a regular array of surface elevations share a fault: Unless the terrain is rugged, the derived water channels tend to flow in parallel lines along preferred directions engendered by the ...
Computing the drainage network on huge grid terrains
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, 2012
We present a very efficient algorithm, named EMFlow , and its implementation to compute the drainage network, that is, the flow direction and flow accumulation on huge terrains stored in external memory. It is about 20 times faster than the two most recent and most efficient published methods: TerraFlow and r.watershed.seg. Since processing large datasets can take hours, this improvement is very significant. The EMFlow is based on our previous method RWFlood which uses a flooding process to compute the drainage network. And, to reduce the total number of I/O operations, EMFlow is based on grouping the terrain cells into blocks which are stored in a special data structure managed as a cache memory. Also, a new strategy is adopted to subdivide the terrains in islands which are processed separately. Because of the recent increase in the volume of high resolution terrestrial data, the internal memory algorithms do not run well on most computers and, thus, optimizing the massive data processing algorithm simultaneously for data movement and computation has been a challenge for GIS.
GeoInformatica, 2015
We present EMFlow , a very efficient algorithm and its implementation, to compute the drainage network (i.e. the flow direction and flow accumulation) on huge terrains stored in external memory. Its utility lies in processing the large volume of high resolution terrestrial data newly available, which internal memory algorithms cannot handle efficiently. EMFlow computes the flow direction using an adaptation of our previous method RWFlood that uses a flooding process to quickly remove internal depressions or basins. Flooding, proceeding inward from the outside of the terrain, works oppositely to the common method of computing downhill flow from the peaks. To reduce the total number of I/O operations, EMFlow adopts a new strategy to subdivide the terrain into islands that are processed separately. The terrain cells are grouped into blocks that are stored in a special data structure managed as a cache memory. EMFlow 's execution time was compared against the two most recent and most efficient published methods: TerraFlow and r.watershed.seg. It was, on average, 27 times faster than both methods, and EMFlow could process larger datasets. Processing a 50000x50000 terrain on a machine with 2GB of internal memory took only 3000 seconds, compared to 87000 seconds for TerraFlow while r.watershed.seg failed on terrains larger than 15000x15000. On very small, say 1000x1000 terrains, EMFlow takes under a second, compared to 6 to 20 seconds, so it could be a component of a future interactive system where a user could modify terrain and immediately see the new hydrography.
Estimating Flow Distribution over Digital Elevation Models Using a Form-Based Algorithm
Annals of GIS, 1998
This paper discusses a new approach to estimate flow distribution over a continuous surface. This approach is based on the analysis of topographic form of a surface facet that dictates the flow distribution. In the case of a raster Digital Elevation Model (DEM), the facet consists of a centre cell and its eight neighbouring cells. If the form of the facet is convex, the water flow is divergent; thus the amount of flow is distributed to all cells that have a lower elevation. In the case of a concave or flat surface, the convergent flow is directed to the main drainage direction. Comparison between the results of this algorithm with the traditional 'eight-move' algorithm, which is widely used in today's commercial GIS software, indicated that the form-based algorithm yielded a more realistic results in estimating flow accumulation over the land surface, but produced less convincing results in deriving a drainage network.