References of "Ouedraogo, Mohamar"
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See detailExactitude du positionnement numérique des axes de ruissellement dans les bassins versants agricoles
Ouedraogo, Mohamar ULg

Doctoral thesis (2014)

Des études récentes menées en Belgique estiment les dommages causés par les inondations et les coulées boueuses entre 12,5 et 122 millions d’euros par an pour les infrastructures publiques, et entre 1,6 ... [more ▼]

Des études récentes menées en Belgique estiment les dommages causés par les inondations et les coulées boueuses entre 12,5 et 122 millions d’euros par an pour les infrastructures publiques, et entre 1,6 et 16,5 millions d’euros par an pour les habitations. La carte des zones à risque potentiel de ruissellement concentré est l’un des outils mis en place par la Wallonie pour lutter contre ces phénomènes de plus en plus fréquents. Cependant, la résolution (10 × 10 m) du MNT utilisé pour extraire les axes de ruissellement est trop faible pour prendre en compte les détails de la microtopographie (travail du sol, résidus de cultures, cultures…) des parcelles agricoles. De plus, elle ne tient pas compte des incertitudes inévitables, présentes dans les données altimétriques utilisées. L’objectif de cette thèse est d’envisager l’utilisation des nouvelles technologies d’acquisition des données altimétriques de haute densité (plusieurs points/m²), i.e., le scanner laser terrestre (TLS) et la photogrammétrie à partir d’un véhicule non piloté (VNP) pour créer un modèle numérique de terrain (MNT) de meilleure exactitude et de haute résolution spatiale (maille de dimensions ± 1 x 1 m). Cela permet de tenir compte de la variabilité altimétrique des parcelles agricoles, et d’analyser son impact sur le positionnement numérique des axes de ruissellement. Dans un premier temps, un TLS et un VNP à voilure fixe ont été utilisés pour acquérir des données altimétriques sur un bassin versant agricole de 12 ha. Deux logiciels photogrammétriques ont permis de générer le MNTPSC (Agisoft PhotoScan) et le MNTMCM (MicMac) ; tandis que des traitements statistiques ont été nécessaires pour supprimer les erreurs systématiques présentes dans les nuages de points obtenus au TLS avant de les fusionner pour générer le MNTTLS. La comparaison des MNT avec des points de contrôle (GCP) positionnés au récepteur GNSS (Global Navigation Satellite System) en mode RTK (Real Time Kinematic) a montré que le MNTTLS est le plus exact avec un RMSE (Root Mean Square Error) de 4,5 cm, suivi par le MNTMCM et le MNTPSC avec des RMSE valant respectivement 9,0 et 13,9 cm. Dans un second temps, la méthode de Monte Carlo a été utilisée pour générer à partir du MNTTLS, des MNT équiprobables. L’extraction des axes de ruissellement à partir des MNT équiprobables a permis de définir pour chaque maille du MNT, la probabilité d’appartenir à l’axe de ruissellement, et de définir une zone contenant l’axe de ruissellement extrait du MNTTLS avec une probabilité définie. Une telle zone peut être utilisée pour la mise en place de solutions telles que les bandes et les chenaux enherbés. La comparaison des algorithmes de suppressions des dépressions fermées d’une part, et des algorithmes d’extraction de la direction de l’eau d’autre part, a montré peu de différence au niveau de la probabilité d’appartenance des mailles à l’axe de ruissellement lorsque le MNT est de haute résolution spatiale (± 1 m). Enfin, les analyses statistiques ont montré que les altitudes des GCP utilisés dans la méthode de Monte Carlo sont influencées par l’état d’ameublissement et par la rugosité des sols des parcelles agricoles. Les études futures, e.g., à l’échelle de la Wallonie, devront prendre en compte l’impact de ces erreurs. [less ▲]

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See detailSynthèse bibliographique : le modèle numérique de terrainde haute résolution, ses erreurs et leur propagation
Ouedraogo, Mohamar ULg; Degré, Aurore ULg; Debouche, Charles ULg

in Biotechnologie, Agronomie, Société et Environnement = Biotechnology, Agronomy, Society and Environment [=BASE] (2014), 18(3), 407

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See detailThe evaluation of unmanned aerial systems-based photogrammetry and terrestrial laser scanning to generate DEMs of agricultural watersheds
Ouedraogo, Mohamar ULg; Degré, Aurore ULg; Debouche, Charles ULg et al

in Geomorphology (2014)

Agricultural watersheds tend to be places of intensive farming activities that permanently modify their microtopography. The surface characteristics of the soil vary depending on the crops that are ... [more ▼]

Agricultural watersheds tend to be places of intensive farming activities that permanently modify their microtopography. The surface characteristics of the soil vary depending on the crops that are cultivated in these areas. Agricultural soil microtopography plays an important role in the quantification of runoff and sediment transport because the presence of crops, crop residues, furrows and ridges may impact the direction of water flow. To better assess such phenomena, 3-D reconstructions of high-resolution agricultural watershed topography is essential. Fine-resolution topographic data collection technologies can be used to discern highly detailed elevation variability in these areas. Knowledge of the strengths and weaknesses of existing technologies used for data collection on agricultural watersheds may be helpful in choosing an appropriate technology. This study assesses the suitability of terrestrial laser scanning (TLS) and unmanned aerial system (UAS) photogrammetry for collecting the fine-resolution topographic data required to generate accurate, high-resolution digital elevation models (DEMs) in a small watershed area (12 ha). Because of farming activity, 14 TLS scans (≈ 25 points m− 2) were collected without using high-definition surveying (HDS) targets, which are generally used to mesh adjacent scans. To evaluate the accuracy of the DEMs created from the TLS scan data, 1,098 ground control points (GCPs) were surveyed using a real time kinematic global positioning system (RTK-GPS). Linear regressions were then applied to each DEM to remove vertical errors from the TLS point elevations, errors caused by the non-perpendicularity of the scanner’s vertical axis to the local horizontal plane, and errors correlated with the distance to the scanner’s position. The scans were then meshed to generate a DEMTLS with a 1 × 1 m spatial resolution. The Agisoft PhotoScan and MicMac software packages were used to process the aerial photographs and generate a DEMPSC (Agisoft PhotoScan) and DEMMCM (MicMac), respectively, with spatial resolutions of 1 × 1 m. Comparing the DEMs with the 1,098 GCPs showed that the DEMTLS was the most accurate data product, with a root mean square error (RMSE) of 4.5 cm, followed by the DEMMCM and the DEMPSC, which had RMSE values of 9.0 and 13.9 cm, respectively. The DEMPSC had absolute errors along the border of the study area that ranged from 15.0 to 52.0 cm, indicating the presence of systematic errors. Although the derived DEMMCM was accurate, an error analysis along a transect showed that the errors in the DEMMCM data tended to increase in areas of lower elevation. Compared with TLS, UAS is a promising tool for data collection because of its flexibility and low operational cost. However, improvements are needed in the photogrammetric processing of the aerial photographs to remove non-linear distortions. [less ▲]

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See detailModeling the uncertainty of runoff flow path on a small agricultural watershed
Ouedraogo, Mohamar ULg

Scientific conference (2013, July 01)

Recently, many munipalities have been concerned by muddy floods in Belgium after rain events. Unfortunately they lead to many consequences related to financial and emotional aspects. For many years the ... [more ▼]

Recently, many munipalities have been concerned by muddy floods in Belgium after rain events. Unfortunately they lead to many consequences related to financial and emotional aspects. For many years the government have been trying to find solutions by helping municipalities by providing them with technical support through projects like ERRUISSOL and GISER. To implement solutions, it is necessary to be able to predict runoff flow path on agricultural watersheds. This is done by applying water flow direction algorithms on digital elevation model (DEM) built from elevation data. However, digital elevation models are not free of errors, and therefore they can impact the extracted flow path position. Our aim is to present the Monte Carlo simulation that is used to model the uncertainty of runoff flow path extracted from high resolution DEM built from terrestrial laser scanner. [less ▲]

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See detailComparaison de MNTs générés à partir de données LiDAR terrestre et de photographies aériennes prises à basse altitude
Ouedraogo, Mohamar ULg

Scientific conference (2012, November 29)

In this presentation we compare DEMs generated using terrestrial LIDAR and UAV data. The study site is a small agricultural watershed located near the region of Gembloux in Belgium. Terresttrial LiDAR ... [more ▼]

In this presentation we compare DEMs generated using terrestrial LIDAR and UAV data. The study site is a small agricultural watershed located near the region of Gembloux in Belgium. Terresttrial LiDAR data was collected using Trimble GX trought 14 scans. After correcting errors by using statistical approach, scans are meshed to generate a DEM of 1 m x 1 m resolution. UAV data was collected using the X100 UAV commercialized by gatewing. Data was processed in the open source MICMAC software to generate a DEM of 1 m x 1 m resolution. DEMs comparison to ground control points surveyed by RTK GPS, showed that DEM generated using terrestrial LiDAR data is the most precise with a RMSE of 4.9 cm compare to the DEM from UAV data which RMSE was 9.0 cm. [less ▲]

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See detailInfluence de l'état d'ameublissement et de la rugosité du sol des parcelles agricoles sur l'exactitude de l'altitude des points de contrôle positionnés au GPS
Ouedraogo, Mohamar ULg; Debouche, Charles ULg; Degre, Aurore ULg

in Biotechnologie, Agronomie, Société et Environnement = Biotechnology, Agronomy, Society and Environment [=BASE] (2012), 16(1), 33-44

Our goal in this study is to estimate through ranges of variation, the impact of agricultural parcels soil’s tilth and roughness, due to cultivation techniques, on the exactness of ground control points ... [more ▼]

Our goal in this study is to estimate through ranges of variation, the impact of agricultural parcels soil’s tilth and roughness, due to cultivation techniques, on the exactness of ground control points elevation surveyed by RTK (Real Time Kinematic) GPS (Global Positioning System). So, 16 point’s elevations which were located each 100 mm on a transect have been surveyed first by using a total station (TS), and then a RTK GPS in 2 parcels (3 transects per parcel). Cultivation techniques on those parcels were different. The parcel 1 was tilled, and the soil of parcel 2 was prepared for cereal cropping. Then, the analysis of variance has been applied on the differences of TS and RTK GPS elevations data to estimate the confidence interval of ground control points elevation due (i) to soil tilth, whereas the times series statistical method have been applied on elevation data to estimate the confidence interval due (ii) to soil roughness. The confidence intervals of points elevation are estimated being (i) [51 mm; 57 mm], (ii) [-4 mm; 4 mm] for parcel 1, and (i) [97 mm; 113 mm], (ii) [-35 mm; 23 mm], for parcel 2. Results show that ground control point’s elevations exactness is influenced by soil tilth and soil roughness. In conclusion, we can admit that soil tilth and soil roughness have significant impact on the exactness of ground control points located on agricultural parcels. This impact must be considered in DEM errors evaluation of agricultural watershed. [less ▲]

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See detailA methodology to assess the exactness of Stream Network modeling process on agricultural watersheds
Ouedraogo, Mohamar ULg; Degre, Aurore ULg; Beckers, Eléonore ULg et al

in Geophysical Research Abstracts (2011)

The goal of our study is to evaluate the exactness of stream network modeling process on agricultural watersheds. Agricultural watersheds topography is always changing, making it difficult to be modeled ... [more ▼]

The goal of our study is to evaluate the exactness of stream network modeling process on agricultural watersheds. Agricultural watersheds topography is always changing, making it difficult to be modeled. According to the standard ISO-7078 (ISO-7078, 1985) of the Inernational Organization of Standardization, the exactness of a measurement process or a modeled process can be defined as the difference between results obtained from the measurement process and a reference accepted as the «true value». A small watershed of a dozen hectares size has been surveyed by terrestrial LiDAR (Light Detecting And Ranging) scanner and photogrammetrical techniques to produce a row data of 30 cm resolution. Three interpolation techniques i.e. natural neighbourg, multiquadratic radial basis function and inverse distance weighted have been applied on the original data to create original digital elevation models (DEM) of 1 m resolution. RTK (Real Time Kinematics) GPS (Global Positionning System) ground control points have been surveyed on the watershed to evaluate DEM errors and fit a variogram that is used by a conditional sequencial gaussian simulation model to generate error maps. However, ground control point’s elevations accuracy is depending on the microtopography of parcels in an agricultural watershed. Depending on the crop that is planned by the farmer, the soil tillage will be different, and soil structure and roughness can considerably influence ground control point’s elevation. Analysis of variance and geostatistical methods have been applied on total station and RTK GPS data to estimate intervals in which, ground control points elevations vary. These intervals have been estimated for two parcels that soils are tilled in different ways. These errors are added to the generated errors maps to create final error maps. The final errors maps are added to the original DEM to create likely DEM realizations for the watershed (Temme and al., 2007). Then, two spurious sinks filtering methods (Colson 2006; Lindsay and Creed, 2005) and one flat area treatment method (Jenson and Domingue, 1988) are applied on each DEM realization for preprocessing. Finally, the three common flow direction extraction methods (D8, D-infity and Multiple Flow Direction) are applied on each preprocessed DEM to extract stream Network. The extracted stream network is overlapped with RTK GPS field positioned stream network i.e. a polyline format data. To estimate the exactness of the stream extraction methods, the polyline format is converted in raster format. That allows to compute for each pixel of the observed stream network, the distance to the extracted stream network. Then, for each pixel the mean distance can be calculated, and can be represented through the stream network. LiDAR technology is becoming useful for environment modeling because of his accuracy. Such quantity of data is not free of errors. This research will allow us to estimate the uncertainty of stream network modeled from agricultural watersheds by considering the main sources of errors that are propagated through computing processes. [less ▲]

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