Analysis of vegetation seasonality in Sahelian environments using MODIS LAI, in association with land cover and rainfall

Bobee, Cécilia; Ottlé, Catherine; Maignan, Fabienne; Noblet‐Ducoudré, Nathalie de; Maugis, Pascal; Lézine, Anne Marie; Ndiaye, Mamadou Lamine

doi:10.1016/j.jaridenv.2012.03.005

Cited by 37 publications

(32 citation statements)

References 47 publications

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“…Our results show that the spatial pattern seen in satellite trend maps show regional differences that can partly be explained by soil and land-cover differences [9,51]. The sandy Seno Plain in Mali can be distinguished from the rocky Dogon Plateau.…”

Section: Discussionmentioning

confidence: 64%

Local Vegetation Trends in the Sahel of Mali and Senegal Using Long Time Series FAPAR Satellite Products and Field Measurement (1982–2010)

et al. 2014

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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 Remote Sens. 2014, 6 2409 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.

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Section: Discussionmentioning

confidence: 64%

Local Vegetation Trends in the Sahel of Mali and Senegal Using Long Time Series FAPAR Satellite Products and Field Measurement (1982–2010)

et al. 2014

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“…It is projected onto a 10˝sinusoidal grid and is distributed in HDF-EOS format. The product is subjected to extensive quality control and has been found to work well in the Sahel [25], with a minimum uncertainty of about˘0.2 m 2¨m´2 during the dry season ( [14,24]). Zhang et al [26] also used this product to monitor the vegetation growth.…”

Section: Laimentioning

confidence: 99%

“…Several methods have been proposed for determining these phenological dates, such as the sigmoid [25], the Gaussian Asymmetric (AG), and the Savitzky-Golay (SG) ( [22,52]) functions. However, these methods do not allow one to globally adjust the phenological cycle.…”

Section: Vegetation Phenology Parametersmentioning

confidence: 99%

Rainfall Intra-Seasonal Variability and Vegetation Growth in the Ferlo Basin (Senegal)

et al. 2016

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During the monsoon season, the spatiotemporal variability of rainfall impacts the growth of vegetation in the Sahel. This study evaluates this effect for the Ferlo basin in central northern Senegal. Relationships between rainfall, soil moisture (SM), and vegetation are assessed using remote sensing data (TRMM3B42 and RFE 2.0 for rainfall, ESA-CCI.SM for soil moisture and MODIS Leaf Area Index (LAI)). The principal objective was to analyze the response of vegetation growth to water availability during the rainy season using statistical criteria at the scale of homogeneous vegetation-soil zones. The study covers the period from June to September for the years 2000 to 2010. The surface SM is well correlated with both rainfall products. On ferruginous soils, better correlation of intra-seasonal variations and stronger sensitivity of the vegetation to rainfall are found compared to lithosols soils. LAI responds, on average, two to three weeks after a rainfall anomaly. Moreover, dry spells (negative anomalies) of seven days' length (three days for SM anomaly) significantly affect vegetation growth (maximum LAI within the season). A strong and significant link is also found between total precipitation and the number of dry spells. These datasets proved to be sufficiently reliable to assess the impacts of rainfall variability on vegetation dynamics.

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“…Very few studies, like Bobee et al [13], tried other indices like Leaf Area Index (LAI) to study the response of vegetation to rainfall in northwest Senegal.…”

Section: Introductionmentioning

confidence: 99%

Land Use/Cover Response to Rainfall Variability: A Comparing Analysis between NDVI and EVI in the Southwest of Burkina Faso

Zoungrana

Christopher

Amekudzi

et al. 2014

Climate

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Analysis of vegetation seasonality in Sahelian environments using MODIS LAI, in association with land cover and rainfall

Cited by 37 publications

References 47 publications

Local Vegetation Trends in the Sahel of Mali and Senegal Using Long Time Series FAPAR Satellite Products and Field Measurement (1982–2010)

Local Vegetation Trends in the Sahel of Mali and Senegal Using Long Time Series FAPAR Satellite Products and Field Measurement (1982–2010)

Rainfall Intra-Seasonal Variability and Vegetation Growth in the Ferlo Basin (Senegal)

Land Use/Cover Response to Rainfall Variability: A Comparing Analysis between NDVI and EVI in the Southwest of Burkina Faso

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