ANALYSIS AND VALIDATION OF GRID DEM GENERATION BASED ON GAUSSIAN MARKOV RANDOM FIELD
| Autor: | Jose-Luis Blanco, A. M. García Lorca, Manuel A. Aguilar, Fernando J. Aguilar, Abderrahim Nemmaoui |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
lcsh:Applied optics. Photonics
010504 meteorology & atmospheric sciences 0211 other engineering and technologies Terrain 02 engineering and technology Classification of discontinuities Linear interpolation lcsh:Technology 01 natural sciences Computer vision Digital elevation model 021101 geological & geomatics engineering 0105 earth and related environmental sciences lcsh:T business.industry Elevation lcsh:TA1501-1820 Triangulation (social science) Geography Lidar lcsh:TA1-2040 Artificial intelligence lcsh:Engineering (General). Civil engineering (General) business Algorithm Interpolation |
| Zdroj: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B2, Pp 277-284 (2016) |
| ISSN: | 2194-9034 |
| Popis: | Digital Elevation Models (DEMs) are considered as one of the most relevant geospatial data to carry out land-cover and land-use classification. This work deals with the application of a mathematical framework based on a Gaussian Markov Random Field (GMRF) to interpolate grid DEMs from scattered elevation data. The performance of the GMRF interpolation model was tested on a set of LiDAR data (0.87 points/m2) provided by the Spanish Government (PNOA Programme) over a complex working area mainly covered by greenhouses in Almería, Spain. The original LiDAR data was decimated by randomly removing different fractions of the original points (from 10% to up to 99% of points removed). In every case, the remaining points (scattered observed points) were used to obtain a 1 m grid spacing GMRF-interpolated Digital Surface Model (DSM) whose accuracy was assessed by means of the set of previously extracted checkpoints. The GMRF accuracy results were compared with those provided by the widely known Triangulation with Linear Interpolation (TLI). Finally, the GMRF method was applied to a real-world case consisting of filling the LiDAR-derived DSM gaps after manually filtering out non-ground points to obtain a Digital Terrain Model (DTM). Regarding accuracy, both GMRF and TLI produced visually pleasing and similar results in terms of vertical accuracy. As an added bonus, the GMRF mathematical framework makes possible to both retrieve the estimated uncertainty for every interpolated elevation point (the DEM uncertainty) and include break lines or terrain discontinuities between adjacent cells to produce higher quality DTMs. |
| Databáze: | OpenAIRE |
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