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See detailAn easy and low-cost method for preprocessing and matching small-scale amateur aerial photography for assessing agricultural land use in Burkina Faso
Wellens, Joost ULg; Midekor, Akoly; Traore, Farid ULg et al

in International Journal of Applied Earth Observation and Geoinformation (2013), 23

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See detailMonitoring the evolution of irrigated areas with Landsat images using backward and forward change detection analysis in the Kou watershed
Traore, Farid ULg; Cornet, Yves ULg; Denis, Antoine ULg et al

in Geocarto International (2013)

The Kou watershed is characterized by important water resources used for drinking, agriculture (especially in the important irrigated areas), industry and the preservation of aquatic fauna and flora. For ... [more ▼]

The Kou watershed is characterized by important water resources used for drinking, agriculture (especially in the important irrigated areas), industry and the preservation of aquatic fauna and flora. For several decades there has been increasing pressure on the Kou’s water resources, partly because of the expansion of the irrigated agricultural areas. This study was conducted to examine this issue, focusing on one specific irrigated area. In order to monitor the expansion of irrigated areas in developing countries, a low-cost remote sensing method based on Landsat images and aerial photographs was developed. The method is based on maximum-likelihood classifications, followed by backward and forward change detection analysis requiring agronomic expertise. Using pixel trajectory analysis, the method connects all pixels to their consecutive states in order to correct their current states. The study showed that the irrigated area has expanded by almost 80% over 20 years, with most of this expansion occurring in the past 10 years. The approach, if validated, could be used to obtain information on past occupation in the rural irrigated areas for which there is no archived data. [less ▲]

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See detailOptimisation de l'utilisation des ressources en eau du bassin du Kou pour des usages agricoles
Traore, Farid ULg

Doctoral thesis (2012)

Water is a priceless natural resource very sensitive to external factors and environmental degradation. It becomes more valuable as competing uses multiply. Therefore, integrated and cooperative water ... [more ▼]

Water is a priceless natural resource very sensitive to external factors and environmental degradation. It becomes more valuable as competing uses multiply. Therefore, integrated and cooperative water resources management is essential within a watershed. The Kou watershed (Burkina Faso) has significant water resources which are divided between domestic (water supply, etc.), agricultural (irrigation) and industrial uses. The hydro-agricultural context of the Kou watershed is marked by a perennial river, along which are located several agricultural areas. Over time, once satisfying water needs degraded to irrigation water deficits, mainly due to a reduction in water supply and an increase in irrigated farmland. Irrigation water deficits are mostly encountered in the more downstream agricultural areas. The socio-economic context is characterized by a growing trend for highly profitable and water consuming crops (e.g. banana). This further increases the irrigation water deficits, as well as the upstream-downstream water-sharing inequalities. In the context of the study area, the main factor that may influence the agricultural water withdrawals is the farmers' production system. The main hypothesis of the study was to verify whether these agricultural production systems could be the lever to optimize irrigation water use. The methodology of the study was to provide a sufficiently accurate knowledge of the water management system, so that improvements could be proposed. A decision support tool based on the ‘multi-agent systems’ approach (MAS) was developed in order to provide an answer to the problems of the study area’s water management by simulating management scenarios. The findings of the study showed (using the MAS tool) that through actions on agricultural production systems it is possible to optimize irrigation water withdrawals. Within the production systems, it is mainly changes in irrigation practices that have led to an optimization of the water management. Finally, the study showed that the use of MAS in resolving agricultural water management issues in the Kou watershed could be the starting point for a new approach in water management. This approach allows the effective integration of the consequences of farmers' decisions regarding water management. More generally MAS-based natural resources management tools provide a common representation of the environment within a model that can help raise awareness concerning a better management of these natural resources. [less ▲]

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See detailAppropriation of decision support tools derived results in the private management of an irrigation scheme in Burkina Faso
Wellens, Joost ULg; Diallo, Mamadou; Nitcheu, Martial et al

Conference (2011, May 31)

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See detailOptimisation de l'utilisation des ressources en eau du bassin du Kou pour des usages agricoles
Traore, Farid ULg; Dembélé, Youssouf; Tychon, Bernard ULg

Scientific conference (2010, May 28)

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See detailRemote sensing assessement of irrigated areas extension in the Kou watershed
Traore, Farid ULg; Tychon, Bernard ULg

Scientific conference (2010, January 12)

The Kou watershed is a geographical space having important water resources, whose are used between: drinking water supply of Bobo-Dioulasso city (Burkina-Faso’s second most important city) and surrounding ... [more ▼]

The Kou watershed is a geographical space having important water resources, whose are used between: drinking water supply of Bobo-Dioulasso city (Burkina-Faso’s second most important city) and surrounding localities; agriculture through very important irrigated surfaces; industry; fauna and flora preservation, through a minimal sanitary debit guaranteed. Since some decades, one observes more and more increased pressure on Kou water resources. From an agricultural point of view, a comparative visual observation of irrigated surfaces during the years 1980 and during years 2000 shows an increase of surfaces. It would be then appropriate to establish a potential of irrigation of the set of available water resources in order to estimate maximal irrigable surfaces by water resources. Thus, this study has for goal the evaluation of Kou watershed irrigated zones surface, with the help of remote sensing. In order to facilitate irrigated zones detection, the study will focused on the period between January and June, where all cultures are irrigated with Kou watershed surface water and/or groundwater. The chosen methodology is images classification in order to extract irrigated zones surface. We had for this study a set of images and various data: Landsat-4 TM, Landsat-5 TM, Landsat-7 ETM+, SPOT 5, aerial views, agro meteorological data, cartographic data (GIS), data investigation reports, etc. Because of images various origins, we conducted images pretreatment that essentially consisted in image reflectance calibration. This operation appears to be indispensable when working with images from coming different sensors. Classification methods that we used are: a maximum likelihood classification, then a decision tree classification applied to images for which vegetation index (NDVI) has been calculated. The later classification method has been introduced in order to permit a better discrimination between natural vegetation and crops which can often react in similar spectral ranges. This method is based on threshold detection of vegetation classes. Classification methods used allowed us to estimate until a certain point irrigated surfaces, without having, however, a finer information. With 30 m spatial resolution images covering a survey zone with "reduced" to "mean" agricultural lands size, it is sometimes enough difficult to discern natural vegetation pixels from crop pixels. So, we should have considered mixed classes of pixels that strongly skewed our final results. The overall accuracy of our classifications are between 70% and 90%, with Kappa coefficients between 0.4 and 0.85. These Kappa coefficients our results between "tolerable" and "good". However, our evaluations seem to be near enough of those gotten by the means of hydro agricultural inventories led on the same zone. The committed mistakes remain in an interval of +/-20%. [less ▲]

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