Assessing Land Degradation/Recovery in the African Sahel from Long-Term Earth Observation Based Primary Productivity and Precipitation Relationships

Fensholt, Rasmus; Rasmussen, Kjeld; Kaspersen, Per Skougaard; Huber, Silvia; Horion, Stéphanie; Swinnen, Else

doi:10.3390/rs5020664

Cited by 183 publications

(197 citation statements)

References 56 publications

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“…Combining vegetation greenness and rainfall data, postulate that the greening exceeds what can be explained by increases in rainfall alone and suggest the contribution of other factors, which may be related to land management. Analyzing rain-use efficiencies, Fensholt et al (2013) also found no indication for widespread nonrainfall-related land degradation, which corroborates earlier findings by Prince et al (1998).…”

Section: The Greening Conundrumsupporting

confidence: 81%

People and pixels in the Sahel: a study linking coarse-resolution remote sensing observations to land users' perceptions of their changing environment in Senegal

Herrmann¹,

Sall²,

Sy³

2014

E&S

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ABSTRACT. Mounting evidence from satellite observations of a re-greening across much of the Sahel and Sudan zones over the past three decades has raised questions about the extent and reversibility of desertification. Historical ground data that could help in interpreting the re-greening are scarce. To fill that void, we tapped into the collective memories of local land users from central and western Senegal in 39 focus groups and assessed the spatial association between their perceptions of vegetation changes over time and remote sensing-derived trends. To provide context to the vegetation changes, we also explored the land users' perspective on the evolution of other environmental and human variables that are potentially related to the greening, using participatory research methods. While increases in vegetation were confirmed by the study participants for certain areas, which spatially corresponded to satellite-observed re-greening, vegetation degradation dominated their perceptions of change. This degradation, although spatially extensive according to land users, flies under the radar of coarse-resolution remote sensing data because it is not necessarily associated with a decrease in biomass but rather with undesired changes in species composition. Few significant differences were found in the perceived trends of population pressure, environmental, and livelihood variables between communities that have greened up according to satellite data and those that have not. Our findings challenge the prevailing chain of assumptions of the satellite-observed greening trend indicating an improvement of environmental conditions in the sense of a rehabilitation of the vegetation cover after the great droughts of the 1970s and 1980s, and the improvement of environmental conditions possibly translating into more stable livelihoods and greater well-being of the populations. For monitoring desertification and rehabilitation, there is a need to develop remote sensing-based indicators that better reflect the changes in the biophysical environment that matter most to the land users.

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Section: The Greening Conundrumsupporting

confidence: 81%

People and pixels in the Sahel: a study linking coarse-resolution remote sensing observations to land users' perceptions of their changing environment in Senegal

Herrmann¹,

Sall²,

Sy³

2014

E&S

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“…Timesat has been widely used in the Sahel area to detect seasonal dynamics related to the phenology of vegetation and describing the shape of the annual vegetation curve reflected in satellite data (e.g. Horion et al, 2014;Herrmann et al, 2013;Fensholt et al, 2013). The derived seasonal metrics are summarized in Table 1 and illustrated in Fig.…”

Section: Extraction Of Satellite Seasonal Metricsmentioning

confidence: 99%

Woody plant cover estimation in drylands from Earth Observation based seasonal metrics

Brandt

Hiernaux

Tagesson

et al. 2016

Remote Sensing of Environment

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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 r 2 /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.

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“…Several researchers have applied these non-parametric methods to remote sensing applications [13,[45][46][47]], yet this is still questionable (i.e., not removing serial correlation from the series).…”

Section: Serial Correlation Effectmentioning

confidence: 99%

Evaluation of Spatiotemporal Variations of Global Fractional Vegetation Cover Based on GIMMS NDVI Data from 1982 to 2011

Zhao

et al. 2014

Remote Sensing

143

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Fractional vegetation cover (FVC) is an important biophysical parameter of terrestrial ecosystems. Variation of FVC is a major problem in research fields related to remote sensing applications. In this study, the global FVC from 1982 to 2011 was estimated by GIMMS NDVI data, USGS global land cover characteristics data and HWSD soil type data with a modified dimidiate pixel model, which considered vegetation and soil types and mixed pixels decomposition. The evaluation of the robustness and accuracy of the GIMMS FVC with MODIS FVC and Validation of Land European Remote sensing Instruments (VALERI) FVC show high reliability. Trends of the annual FVC max and FVC mean datasets in the last 30 years were reported by the Mann-Kendall method and Sen's slope estimator. The results indicated that global FVC change was 0.20 and 0.60 in a year with obvious seasonal variability. All of the continents in the world experience a change in the annual FVC max and FVC mean , which represents biomass production, except for Oceania, which exhibited a significant increase based on a significance level of p = 0.001 with the Student's t-test. Global annual maximum and mean FVC growth rates are 0.14%/y and 0.12%/y, respectively. The trends of the annual FVC max and FVC mean based on pixels also illustrated that the global vegetation had turned green in the last 30 years. A significant trend on the p = 0.05 level was found for 15.36% of the GIMMS FVC max pixels on a global scale (excluding permanent OPEN ACCESSRemote Sens. 2014, 6 4218 snow and ice), in which 1.8% exhibited negative trends and 13.56% exhibited positive trends. The GIMMS FVC mean similarly produced a total of 16.64% significant pixels with 2.28% with a negative trend and 14.36% with a positive trend. The North Frigid Zone represented the highest annual FVC max significant increase (p = 0.05) of 25.17%, which may be caused mainly by global warming, Arctic sea-ice loss and an advance in growing seasons. Better FVC predictions at large regional scales, with high temporal resolution (month) and long time series, would advance our ability to understand the characteristics of the global FVC changes in the last 30 years and predict the response of vegetation to global climate change.

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Assessing Land Degradation/Recovery in the African Sahel from Long-Term Earth Observation Based Primary Productivity and Precipitation Relationships

Cited by 183 publications

References 56 publications

People and pixels in the Sahel: a study linking coarse-resolution remote sensing observations to land users' perceptions of their changing environment in Senegal

People and pixels in the Sahel: a study linking coarse-resolution remote sensing observations to land users' perceptions of their changing environment in Senegal

Woody plant cover estimation in drylands from Earth Observation based seasonal metrics

Evaluation of Spatiotemporal Variations of Global Fractional Vegetation Cover Based on GIMMS NDVI Data from 1982 to 2011

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