References of "Mohamed Sallah, Abdoul-Hamid"
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See detailBatch-processing of AquaCrop plug-in for rainfed maize using satellite derived Fractional Vegetation Cover data
Mohamed Sallah, Abdoul-Hamid ULiege; Tychon, Bernard ULiege; Piccard, Isabelle et al

in Agricultural Water Management (2019), 217(346-355),

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See detailCiné-débat: Merci pour la pluie
Mohamed Sallah, Abdoul-Hamid ULiege

Conference given outside the academic context (2017)

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See detailAssessment of AquaCrop for winter wheat using satellite derived fCover data
Mohamed Sallah, Abdoul-Hamid ULiege; Wellens, Joost ULiege; Tychon, Bernard ULiege et al

in 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images (2017, June 29)

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See detailPerformance of similarity analysis in the estimation of forage yields in the Sahelian zone of Niger
Garba, Issa ULiege; Salifou, Illa; Djaby, Bakary ULiege et al

in International Journal of Scientific and Engineering Research (2017), 8(2), 1072-1088

The study aims to test the performance of similarity analysis in herbaceous fodder biomass estimate in the Nigerian pastoral zone, in a context of insecurity and precipitation spatiotemporal variability ... [more ▼]

The study aims to test the performance of similarity analysis in herbaceous fodder biomass estimate in the Nigerian pastoral zone, in a context of insecurity and precipitation spatiotemporal variability. It is carried out on the time series of NDVI decadal images of SPOT VEGETATION for the period from 2001 to 2012 and on fodder biomasses measured in situ during the same period. Similarity analysis compares NDVI seasonal patterns to detect similar years using three criteria: the RMSE (Root Mean squared error), the MAD (Mean absolute Deviation), and R². Exploratory statistical analyzes with bootstrap are carried out to better characterize the observations resulting from the simulation. Moreover, the analysis of the parametric and non-parametric correlations is carried out to evaluate the level of link between the simulated data and the real data. The t test and the Wilcoxon test are then carried out in order to compare the means of the actual biomasses with those obtained by the similarity analysis. At the local level, the results indicate that the R² is more efficient than the RMSE and the MAD which have almost the same performances. The results of the similarity calculated with R² can be used as a proxy to the herbaceous phytomass measured in situ, as there is no significant difference between the simulated mean and the mean measured at the 1% threshold. On the other hand, the results of the similarity calculated with the RMSE and the MAD are not exploitable. Parametric and nonparametric correlations are all significant at the 1% threshold. However, the R² are low and vary between 0.32 and 0.45. It therefore seems necessary to continue the research, as numerous studies have revealed very good links between certain indices like the FAPAR, the EVI and the LAI and the aerial phytomasse. [less ▲]

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