References of "Diouf, Abdoul Aziz"
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See detailImproving fungal disease forecasts in winter wheat: A critical role of intra-day variations of meteorological conditions in the development of Septoria leaf blotch
El Jarroudi, Moussa ULiege; Kouadio, Amani Louis ULiege; El Jarroudi, Mustapha et al

in Field Crops Research (2017), 213

Meteorological conditions are important factors in the development of fungal diseases in winter wheat and are the main inputs of the decision support systems used to forecast disease and thus determine ... [more ▼]

Meteorological conditions are important factors in the development of fungal diseases in winter wheat and are the main inputs of the decision support systems used to forecast disease and thus determine timing for efficacious fungicide application. This study uses the Fourier transform method (FTM) to characterize temporal patterns of meteorological conditions between two neighbouring experimental sites used in a regional fungal disease monitoring and forecasting experiment in Luxembourg. Three meteorological variables (air temperature, relative humidity, and precipitation) were included, all conducive to infection of wheat by Zymoseptoria tritici cause of Septoria leaf blotch (STB) in winter wheat, from 2006 to 2009. The intraday, diurnal, dekadal and intra-seasonal variations of the meteorological variables were assessed using FTM, and the impact of existing contrasts between sites on the development of STB was analyzed. Although STB severities varied between sites and years (P ≤ 0.0003), the results indicated that the two sites presented the same patterns of meteorological conditions when compared at larger temporal scales (diurnal to intra-seasonal scales, with time periods >11 h). However, the intraday variations of all the variables were well discriminated between the sites and were highly correlated to STB severities. Our findings highlight and confirm the importance of intraday meteorological variation in the development of STB in winter wheat fields. Furthermore, the FTM approach has potential for identifying microclimatic conditions prevailing at given sites and could help in improving the prediction of disease forecast models used in regional warning systems. [less ▲]

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See detailAssessment of fodder biomass in Senegalese rangelands using earth observation and field data
Diouf, Abdoul Aziz ULiege

Doctoral thesis (2016)

Senegalese livestock size has largely increased during the last three decades in relation to the population growth. The fodder biomass stock available at the end of the growing season, therefore, becomes ... [more ▼]

Senegalese livestock size has largely increased during the last three decades in relation to the population growth. The fodder biomass stock available at the end of the growing season, therefore, becomes increasingly limited to meet feeding needs of pastoral livestock which provides third of the national agricultural wealth. With the reduction of natural grazing lands mostly generated by the expansion of croplands, and the reduction of fodder biomass production due to drought effects, the increase of the livestock size leads to the rangelands overload whose persistence can lead in turn to their degradation. A technique based on a simple linear relationship between the temporal integration of the Normalized Difference Vegetation Index (NDVI) and the ground biomass data, developed in the 1980s, has been operationally applied by the Centre de Suivi Ecologique (CSE) of Dakar (Senegal) to assess the fodder biomass available in rangelands at the end of the growing season. The derived map of total biomass production enables to help pastoral livestock managers as well as national stakeholders against food insecurity and natural resources degradation. Carried out annually, this approach comprises unfortunately some uncertainties as: (1) the saturation drawback of NDVI in areas with high biomass productivity, (2) the temporal scale which is restricted to biomass data of the ongoing year not being used again in the following year, (3) the low predictive ability due to the large time gap between data collection and published results, and (4) the high costs for annual data collection. In addition, although the earth observation (EO) data have largely progressed during the last three decades, this technique has not changed over this period and consequently is not state-of-the-art. To tackle these limitations and advance the traditional method, new statistical models that include new earth observations datasets and historical in situ plant biomass data were developed for estimating and / or predicting the forage availability at the end of the growing season in Senegalese semi-arid rangelands. A backward analysis of the linear regression approach currently applied in Senegal provided evidence that nonlinear regression functions such as Exponential and Power are more suited to estimate the end-of-season total biomass in this region using annual data solely. A completely new methodology using multiple-linear models which include various phenological metrics from the time series of the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) and 14 years of in situ total biomass samples was developed. The proposed approach provided more reliable and accurate estimates as compared to the current CSE biomass product. Multiple-linear models developed with specific metrics adapted to ecosystem properties increased the overall accuracy of the fodder biomass estimates and mitigated the saturation of FAPAR obtained with models run across the whole study area. With this new approach, timely information about possible deficits/surplus of total fodder biomass can be provided to stakeholders using phenological metrics that are available relatively early in the growing season. Another new approach based on a machine learning algorithm (i.e., Cubist) was developed, as never done before, to assess herbaceous biomass in Senegalese Sahel. Three Cubist models using FAPAR seasonal metrics and/or agrometeorological variables (i.e., soil water status indicators) were established and compared. The Cubist model including both FAPAR and agrometeorological variables provided the best estimation performance. This model enabled to mitigate the saturation affecting optical remotely sensed vegetation data in areas of high plant productivity as well as the discrepancy between herbaceous biomass and greenness, and corrected therefore for herbaceous biomass underestimations observed with the sole FAPAR based model, particularly in sparsely vegetated areas. In contrast to the date of the growing season onset retrieved from FAPAR seasonal dynamics, the rainy season onset was significantly related to the herbaceous biomass and its inclusion in models could constitute a significant improvement in forecasting risks of fodder biomass deficit. The methods developed in this research provide tools to assess Senegalese forage resources at two levels: herbaceous and total fodder biomass (Herbaceous + woody leaf biomass). They require limited data and free available software and therefore can be easily replicated in other countries of the West African Sahel. [less ▲]

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See detailDo Agrometeorological Data Improve Optical Satellite-based Estimations of Herbaceous Yield in Sahelian Semi-Arid Ecosystems?
Diouf, Abdoul Aziz ULiege; Hiernaux, Pierre; Brandt, Martin et al

in Remote Sensing (2016), 8

Quantitative estimates of forage availability at the end of the growing season in rangelands are helpful for pastoral livestock managers and for local, national and regional stakeholders in natural ... [more ▼]

Quantitative estimates of forage availability at the end of the growing season in rangelands are helpful for pastoral livestock managers and for local, national and regional stakeholders in natural resource management. For this reason, remote sensing data such as the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) have been widely used to assess Sahelian plant productivity for about 40 years. This study combines traditional FAPAR-based assessments with agrometeorological variables computed by the geospatial water balance program, GeoWRSI, using rainfall and potential evapotranspiration satellite gridded data to estimate the annual herbaceous yield in the semi-arid areas of Senegal. It showed that a machine-learning model combining FAPAR seasonal metrics with various agrometeorological data provided better estimations of the in situ annual herbaceous yield (R² = 0.69; RMSE = 483kg•DM/ha) than models based exclusively on FAPAR metrics (R² = 0.63; RMSE = 550kg•DM/ha) or agrometeorological variables (R² = 0.55; RMSE = 585kg•DM/ha). All the models provided reasonable outputs and showed a decrease in the mean annual yield with increasing latitude, together with an increase in relative inter-annual variation. In particular, the additional use of agrometeorological information mitigated the saturation effects that characterize the plant indices of areas with high plant productivity. In addition, the date of the onset of the growing season derived from smoothed FAPAR seasonal dynamics showed no significant relationship (0.05 p-level) with the annual herbaceous yield across the whole studied area. The date of the onset of rainfall however, was significantly related to the herbaceous yield and its inclusion in fodder biomass models could constitute a significant improvement in forecasting risks of a mass herbaceous deficit at an early stage of the year. [less ▲]

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See detailRemote sensing of vegetation dynamics in drylands: Evaluating vegetation optical depth (VOD) using AVHRR NDVI and in situ green biomass data over West African Sahel
Tian, Feng; Brandt, Martin; Liu, Yi Y. et al

in Remote Sensing of Environment (2016), 177

Monitoring long-term biomass dynamics in drylands is of great importance for many environmental applications including land degradation and global carbon cycle modeling. Biomass has extensively been ... [more ▼]

Monitoring long-term biomass dynamics in drylands is of great importance for many environmental applications including land degradation and global carbon cycle modeling. Biomass has extensively been estimated based on the normalized difference vegetation index (NDVI) as a measure of the vegetation greenness. The vegetation optical depth (VOD) derived from satellite passive microwave observations is mainly sensitive to the water content in total aboveground vegetation layer. VOD therefore provides a complementary data source to NDVI for monitoring biomass dynamics in drylands, yet further evaluations based on ground measurements are needed for an improved understanding of the potential advantages. In this study, we assess the capability of a long-term VOD dataset (1992–2011) to capture the temporal and spatial variability of in situ measured green biomass (herbaceous mass and woody plant foliage mass) in the semi-arid Senegalese Sahel. Results show that the magnitude and peak time of VOD are sensitive to the woody plant foliage whereas NDVI seasonality is primarily governed by the green herbaceous vegetation stratum in the study area. Moreover, VOD is found to be more robust against typical NDVI drawbacks of saturation effect and dependence on plant structure (herbaceous and woody compositions) across the study area when used as a proxy for vegetation productivity. Finally, both VOD and NDVI well reflect the spatial and inter-annual dynamics of the in situ green biomass data; however, the seasonal metrics showing the highest degree of explained variance differ between the two data sources. While the observations in October (period of in situ data collection) perform best for VOD (r2 = 0.88), the small growing season integral (sensitive to recurrent vegetation) have the highest correlations for NDVI (r2 = 0.90). Overall, in spite of the coarse resolution, the study shows that VOD is an efficient proxy for estimating green biomass of the entire vegetation stratum in the semi-arid Sahel and likely also in other dryland areas. [less ▲]

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See detailWoody plant cover estimation in drylands from Earth Observation based seasonal metrics
Brandt, Martin; Hiernaux, Pierre; Tagesson, Torbern et al

in Remote Sensing of Environment (2016), 172

From in situ measured woody cover we develop a phenology driven model to estimate the canopy cover of woody species in the Sahelian drylands at 1 km scale. The model estimates the total canopy cover of ... [more ▼]

From in situ measured woody cover we develop a phenology driven model to estimate the canopy cover of woody species in the Sahelian drylands at 1 km scale. The model estimates the total canopy cover of all woody phanerophytes and the concept is based on the significant difference in phenophases of dryland trees, shrubs and bushes as compared to that of the herbaceous plants. Whereas annual herbaceous plants are only green during the rainy season and senescence occurs shortly after flowering towards the last rains, most woody plants remain photosynthetically active over large parts of the year. We use Moderate Resolution Imaging Spectroradiometer (MODIS) and Satellite pour l'Observation de la Terre (SPOT) — VEGETATION (VGT) Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) time series and test 10 metrics representing the annual FAPAR dynamics for their ability to reproduce in situ woody cover at 43 sites (163 observations between 1993 and 2013) in the Sahel. Both multi-year field data and satellite metrics are averaged to produce a steady map. Multiple regression models using the integral of FAPAR from the onset of the dry season to the onset of the rainy season, the start date of the growing season and the rate of decrease of the FAPAR curve achieve a cross validated r2/RMSE (in % woody cover) of 0.73/3.0 (MODIS) and 0.70/3.2 (VGT). The extrapolation to Sahel scale shows agreement between VGT and MODIS at an almost nine times higher woody cover than in the global tree cover product MOD44B which only captures trees of a certain minimum size. The derived woody cover map of the Sahel is made publicly available and represents an improvement of existing products and a contribution for future studies of drylands quantifying carbon stocks, climate change assessment, as well as parametrization of vegetation dynamic models. [less ▲]

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See detailZonage phénoclimatique et caractérisation des parcours naturels du Sénégal avec les données de télédétection satellitaire
Diouf, Abdoul Aziz ULiege; Faye, G.; Minet, Julien ULiege et al

in XXVIIIème Colloque de l’Association Internationale de Climatologie, Liège 1-5 juillet 2015 (2015, July 02)

Les métriques phénologiques qui expriment certains événements du cycle de vie des plantes, tels que l'émergence, la croissance et la sénescence, principalement liées aux conditions météorologiques et au ... [more ▼]

Les métriques phénologiques qui expriment certains événements du cycle de vie des plantes, tels que l'émergence, la croissance et la sénescence, principalement liées aux conditions météorologiques et au climat, ont été utilisées afin : (i) de déterminer, à travers les parcours naturels du Sénégal, des entités "phénoclimatiques" homogènes ou phénorégions par classification non-supervisée des images de la série temporelle (1999-2013); (ii) d’analyser l’homogénéité des phénorégions en comparant l’évolution interannuelle de l’indice et des quantités de précipitation et (iii) de donner leurs principales caractéristiques biophysiques. Les résultats obtenus montrent que le domaine pastoral sénégalais peut être subdivisé en trois phénorégions à partir de la grande intégrale du NDVIS10 qui donne les entités spatiales les plus homogènes dans lesquelles les paramètres biophysiques comportent une variation latitudinale caractéristique du Sahel [less ▲]

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See detailFodder Biomass Monitoring in Sahelian Rangelands Using Phenological Metrics from FAPAR Time Series
Diouf, Abdoul Aziz ULiege; Brandt, Martin; Verger, Aleixandre et al

in Remote Sensing (2015), 7(9122-9148),

Timely monitoring of plant biomass is critical for the management of forage resources in Sahelian rangelands. The estimation of annual biomass production in the Sahel is based on a simple relationship ... [more ▼]

Timely monitoring of plant biomass is critical for the management of forage resources in Sahelian rangelands. The estimation of annual biomass production in the Sahel is based on a simple relationship between satellite annual Normalized Difference Vegetation Index (NDVI) and in situ biomass data. This study proposes a new methodology using multi-linear models between phenological metrics from the SPOT-VEGETATION time series of Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) and in situ biomass. A model with three variables—large seasonal integral (LINTG), length of growing season, and end of season decreasing rate—performed best (MAE = 605 kg·DM/ha; R2 = 0.68) across Sahelian ecosystems in Senegal (data for the period 1999–2013). A model with annual maximum (PEAK) and start date of season showed similar performances (MAE = 625 kg·DM/ha; R2 = 0.64), allowing a timely estimation of forage availability. The subdivision of the study area in ecoregions increased overall accuracy (MAE = 489.21 kg·DM/ha; R2 = 0.77), indicating that a relation between metrics and ecosystem properties exists. LINTG was the main explanatory variable for woody rangelands with high leaf biomass, whereas for areas dominated by herbaceous vegetation, it was the PEAK metric. The proposed approach outperformed the established biomass NDVI-based product (MAE = 818 kg·DM/ha and R2 = 0.51) and should improve the operational monitoring of forage resources in Sahelian rangelands. [less ▲]

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

Report (2015)

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See detailGround and satellite based evidence of the biophysical mechanisms behind the greening Sahel
Brandt, Martin; Mbow, Cheikh; Diouf, Abdoul Aziz ULiege et al

in Global Change Biology (2015)

After a dry period with prolonged droughts in the 1970s and 1980s, recent scientific outcome suggests that the decades of abnormally dry conditions in the Sahel have been reversed by positive anomalies in ... [more ▼]

After a dry period with prolonged droughts in the 1970s and 1980s, recent scientific outcome suggests that the decades of abnormally dry conditions in the Sahel have been reversed by positive anomalies in rainfall. Various remote sensing studies observed a positive trend in vegetation greenness over the last decades which is known as the re-greening of the Sahel. However, little investment has been made in including long-term ground-based data collections to evaluate and better understand the biophysical mechanisms behind these findings. Thus, deductions on a possible increment in biomass remain speculative. Our aim is to bridge these gaps and give specifics on the biophysical background factors of the re-greening Sahel. Therefore, a trend analysis was applied on long time series (1987–2013) of satellite-based vegetation and rainfall data, as well as on ground-observations of leaf biomass of woody species, herb biomass, and woody species abundance in different ecosystems located in the Sahel zone of Senegal. We found that the positive trend observed in satellite vegetation time series (+36%) is caused by an increment of in situ measured biomass (+34%), which is highly controlled by precipitation (+40%). Whereas herb biomass shows large inter-annual fluctuations rather than a clear trend, leaf biomass of woody species has doubled within 27 years (+103%). This increase in woody biomass did not reflect on biodiversity with 11 of 16 woody species declining in abundance over the period. We conclude that the observed greening in the Senegalese Sahel is primarily related to an increasing tree cover that caused satellite-driven vegetation indices to increase with rainfall reversal. [less ▲]

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See detailFonctions d’ajustement pour l’estimation de la production fourragère herbacée des parcours naturels du Sénégal à partir du NDVI s10 de SPOT-vegetation
Diouf, Abdoul Aziz ULiege; Djaby, Bakary ULiege; Diop, Mouhamadou Bamba et al

in XXVIIe Colloque de l’Association Internationale de Climatologie (2014, July 04)

Face à la situation actuelle de changement climatique et ses conséquences sur l’homme et les ressources naturelles, les Systèmes d’Alerte Précoce (SAP) sur le disponible fourrager en zones pastorales ... [more ▼]

Face à la situation actuelle de changement climatique et ses conséquences sur l’homme et les ressources naturelles, les Systèmes d’Alerte Précoce (SAP) sur le disponible fourrager en zones pastorales constituent des stratégies essentielles dans la lutte contre l’insécurité alimentaire, notamment au niveau des pays du Sahel ouest-africains comme le Sénégal. L’évaluation du stock de fourrage s’y effectue habituellement à partir d’une régression linéaire entre les données de biomasse mesurée sur le terrain et l’indice de végétation par différence normalisée (NDVI) issu du satellite SPOT VEGETATION. Mais, compte tenu de la nature non-linéaire de la relation NDVI-biomasse herbacée, cinq autres fonctions d’ajustement sont testées afin de déterminer celles qui traduisent au mieux cette relation.Les données de biomasse ont été collectées au niveau de cinquante-et-un Sites de Contrôle au Sol (SCS) dont trente-six ont servi à la calibration et quinze pour évaluer la précision des modèles. Les variables utilisées sont le NDVI moyen et le NDVI maximum, enregistrés au cours de la saison. Les résultats obtenus montrent que les modèles Exponentiel et Puissance sont les plus cohérents et précis pour l’estimation de la biomasse herbacée à partir du NDVI. Toutefois, cette approche empirique par régression simple reste globalement imprécise pour l’évaluation de la biomasse herbacée au Sénégal vu les valeurs relativement élevées du RMSE qui varient entre 324,07 et 858 kg/ha selon l’année. [less ▲]

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See detailLocal Vegetation Trends in the Sahel of Mali and Senegal Using Long Time Series FAPAR Satellite Products and Field Measurement (1982–2010)
Brandt, Martin; Verger, Aleixandre; Diouf, Abdoul Aziz ULiege et al

in Remote Sensing (2014), 6(3), 2408-2434

Local vegetation trends in the Sahel of Mali and Senegal from Geoland Version 1 (GEOV1) (5 km) and the third generation Global Inventory Modeling and Mapping Studies (GIMMS3g) (8 km) Fraction of Absorbed ... [more ▼]

Local vegetation trends in the Sahel of Mali and Senegal from Geoland Version 1 (GEOV1) (5 km) and the third generation Global Inventory Modeling and Mapping Studies (GIMMS3g) (8 km) Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) time series are studied over 29 years. For validation and interpretation of observed greenness trends, two methods are applied: (1) a qualitative approach using in-depth knowledge of the study areas and (2) a quantitative approach by time series of biomass observations and rainfall data. Significant greening trends from 1982 to 2010 are consistently observed in both GEOV1 and GIMMS3g FAPAR datasets. Annual rainfall increased significantly during the observed time period, explaining large parts of FAPAR variations at a regional scale. Locally, GEOV1 data reveals a heterogeneous pattern of vegetation change, which is confirmed by long-term ground data and site visits. The spatial variability in the observed vegetation trends in the Sahel area are mainly caused by varying tree- and land-cover, which are controlled by human impact, soil and drought resilience. A large proportion of the positive trends are caused by the increment in leaf biomass of woody species that has almost doubled since the 1980s due to a tree cover regeneration after a dry-period. This confirms the re-greening of the Sahel, however, degradation is also present and sometimes obscured by greening. GEOV1 as compared to GIMMS3g made it possible to better characterize the spatial pattern of trends and identify the degraded areas in the study region. [less ▲]

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