References of "Garba, Issa"
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See detailImproving fodder biomass modeling in the sahelian zone of Niger using the multiple linear regression method
Garba, Issa ULiege; Djaby, Bakary ULiege; Salifou, Illa et al

in International Journal for Research in Applied Science and Engineering Technology (2017), 5(5), 1627-1639

This study was carried out in Niger and aims to propose an improved fodder biomass estimate model using the Multiple Linear Regression (MRM) method. The work was carried out with measurements of ... [more ▼]

This study was carried out in Niger and aims to propose an improved fodder biomass estimate model using the Multiple Linear Regression (MRM) method. The work was carried out with measurements of herbaceous mass (in situ) made from 2001 to 2012 by the Ministry of Livestock and Animal Industry of Niger MEIA); rainfalls observed by the Niger Meteorological Office and the meteorological variables from the European Center for Medium - Range Weather Forecasts (ECMWF), processed in AgrometShell (AMS) to derive the agro- meteorological variables; the SPOT VEGETATION NDVI satellite images processed in the "Vegetation Analysis in Space and Time" (VAST) program to derive biophysical variables from the annual NDVI decadal series and finally the estimated rainfall known as RFE from the American institution "Famine Early Warning Systems Network "(FEWSNET) for the calculation of annual rainfall totals. The model was performed by multiple linear regressions with the ascending step – by - step procedure for the selection of variables based on the adjusted R² and the RMSE. Leave One Out Cross Validation (LOOICV) was used to calculate the validation R² and a systematic diagnosis of residues to better characterize the model. Throughout the (national) study area, MRM performed an adjusted R² of 0.68 and a RMSE of 282 kg. Ha-1, the difference between the RMSE of the calibration and that of the validation is 3.72 kg.ha-1. However, it is necessary to continue this research with other indices such as LAI and FAPAR and EVI. Also, it would be interesting to explore ways such as: taking into account the foliage of the trees, adjusting the metrics to the phenology of the herbaceous plants, and those of the woody ones. This work will improve the quality of information used to plan development actions in favor of Niger society in order to protect it against pastoral crises. [less ▲]

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See detailValidation of herbaceous biomass assessment model for sahelian rangelands (biomasah) in Niger.
Garba, Issa ULiege; Salifou, Illa; Djaby, Bakary ULiege et al

in International Journal of Current Research (2017), 9(4), 48992-48999

This study was carried out in the pastoral zone of Niger with the aim of validating outputs of the BIOMASAH model developed by the AGRHYMET Regional Centre (ARC) relative to real data collected over the ... [more ▼]

This study was carried out in the pastoral zone of Niger with the aim of validating outputs of the BIOMASAH model developed by the AGRHYMET Regional Centre (ARC) relative to real data collected over the 2001-2011 period by the Ministry Livestock and Animal Industries (MEIA) of Niger. We used parametric tests (t-tests) and nonparametric tests (Wilcoxon and sign tests) for mean comparisons. A correlation analysis was performed by calculating Pearson’s r, Spearman’s ρ, Kendall’s T and Hoeffding’s D correlation coefficients. The results showed that the BIOMASAH model generally overestimated biomass (983.17 vs. 591.17 kg/ha) with a highly significant difference relative to the field findings (P <.0001). Pearson’s r (0.15), Spearman’sρ (0.22) Kendall’s T (0.13) and Hoeffding’s D (0.1) correlation coefficients were low but highly significant (p <.0001). Grazing pressure and spatiotemporal variability of rainfall helped explain the noted differences. [less ▲]

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See detailMapping of zones at risk (ZAR) in West Africaby using NGI, VCI and SNDVI from the e-station.
Garba, Issa ULiege; Salifou, Illa; Sallah, Abdoul Hamid et al

in International Journal of Advanced Research (2017), 5(4), 1376-1386

This work is carried out at the AGRHYMET Regional Centre (ARC)-CILSS as part of the African Monitoring of Environment for Sustainable Development (AMESD) project. The analysis protocol has been improved ... [more ▼]

This work is carried out at the AGRHYMET Regional Centre (ARC)-CILSS as part of the African Monitoring of Environment for Sustainable Development (AMESD) project. The analysis protocol has been improved under the Monitoring of Environment for Security in Africa (MESA) project. The MESA Project has been designed on the achievements of AMESD; its overall objective is to provide African countries with access to Earth Observation data for environmental monitoring and sustainable development. The specific objective of this study is to develop an operational analysis protocol for vegetation monitoring in general and especially for crops and pastures. Three vegetation indices were used: Vegetation Condition Index (VCI), Normalized Growth Index (NGI) and Standardized Normalized Difference Vegetation Index (SNDVI). The analysis of these drought indices is based on taking into account the agro-climatic characteristics of the Sahelian region, the comparison of the NGI profile (per administrative unit) from year X (in progress) to the maximum NGI profiles, minimum and average of the time series data (1998 to year x-1) and evidence convergence. Six years of application of the method and validation actions carried out concluded that it is possible to determine the zones at risk (ZAR) in order to anticipate food crises. [less ▲]

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See detailModélisation spatiale de la production fourragère en zone pastorale nigérienne
Garba, Issa ULiege

Doctoral thesis (2017)

This work was carried out on the pastoral zone of Niger, the main objective was to contribute to the improvement of the methods of forage yields predicting mainly in the Sahel and especially in Niger ... [more ▼]

This work was carried out on the pastoral zone of Niger, the main objective was to contribute to the improvement of the methods of forage yields predicting mainly in the Sahel and especially in Niger. This is specifically to validate the model BIOMASAH of ARC; test the MEIA model; to establish a reference model by multiple linear regression; test the similarity method and finally compare the methods. The work was carried out on the one hand with the data measured on the ground by the MEIA from 2001 to 2012, reel rainfall of Niger observations network, meteorological parameters from ECMWF and also with satellite images as SPOT NDVI VEGETATION and MODIS, RFE2 of FEWS NET. Validation of BIOMASAH model was made by t and Wilcoxon tests to compare reel biomass and outputs of the model. Pearson, Kendall and Spearman correlation testing was also made. The MEIA model performance was tested by confronting the results between and within SPOT VEGETATION and MODIS sensors, by comparing R² and RMSE from the integral and maximum NDVI as a predictor of forage yield. Average comparisons by parametric and nonparametric tests were also made to compare the results. The reference model (RM) was produced by multiple linear regression with stepwise method. The selection of variables was based on adjusted R² and RMSE and the LOOCV leave one out cross validation to calculate R² for validation, we made also systematic diagnosis of residues for better characterization of the model. The similarity method was performed using the R², MAD and RMSE as a criterion, the profile of the vegetation growth period of each pixel was plotted for all years. Then we compare the profile of the target year with those of other years to identify the similar year. One hand the results of similarity were compared with actual data with the Pearson correlation test, Spearman and Kendall and secondly using t and Wilcoxon tests to compare means. Comparison of models was made on the basis of R², Adjusted R² and RMSE. Model BIOMASAH result on significant difference between average (p <0.001). Pearson correlations, Kendall and Spearman are low. Regarding the MEIA model, globally R² (0.56) is best, there’s no difference to use MODIS NDVI or SPOT vegetation, the RMSE is 367 kg.ha-1. R² and RMSE vary greatly from one year to another. On a global scale the multiple linear model gave a good R² adjusted (0.69) and RMSE (282 kg / ha) the difference between the calculated and the RMSE of validation is 2.72 kg. Comparing averages of the similarity to the real ones showed that there are no significant differences (p <0.001) for R² with the differences are significant against the same threshold for the MAD and RMSE. The Comparison of the models shows that the multiple linear regression one (reference model) is the best. Research should continue with index like LAI, FARAR and EVI. [less ▲]

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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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See detailLIVESTOCK SYSTEMS--TECHNICAL REPORT
Minet, Julien ULiege; Diouf, Abdoul Aziz ULiege; Garba, Issa ULiege et al

Report (2015)

Detailed reference viewed: 46 (7 ULiège)