What four decades of earth observation tell us about land degradation in the Sahel?

Research output: Contribution to journal › Journal article › peer-review

Standard

What four decades of earth observation tell us about land degradation in the Sahel? / Mbow, Cheikh; Brandt, Martin Stefan; Ouedraogo, Issa; de Leeuw, Jan; Marshall, Michael.

In: Remote Sensing, Vol. 7, No. 4, 01.04.2015, p. 4048-4067.

Research output: Contribution to journal › Journal article › peer-review

Harvard

Mbow, C, Brandt, MS, Ouedraogo, I, de Leeuw, J & Marshall, M 2015, 'What four decades of earth observation tell us about land degradation in the Sahel?', Remote Sensing, vol. 7, no. 4, pp. 4048-4067. https://doi.org/10.3390/rs70404048

APA

Mbow, C., Brandt, M. S., Ouedraogo, I., de Leeuw, J., & Marshall, M. (2015). What four decades of earth observation tell us about land degradation in the Sahel? Remote Sensing, 7(4), 4048-4067. https://doi.org/10.3390/rs70404048

Vancouver

Mbow C, Brandt MS, Ouedraogo I, de Leeuw J, Marshall M. What four decades of earth observation tell us about land degradation in the Sahel? Remote Sensing. 2015 Apr 1;7(4):4048-4067. https://doi.org/10.3390/rs70404048

Author

Mbow, Cheikh ; Brandt, Martin Stefan ; Ouedraogo, Issa ; de Leeuw, Jan ; Marshall, Michael. / What four decades of earth observation tell us about land degradation in the Sahel?. In: Remote Sensing. 2015 ; Vol. 7, No. 4. pp. 4048-4067.

Bibtex

@article{95894cb63e474861bd96c446636f9e7b,
title = "What four decades of earth observation tell us about land degradation in the Sahel?",
abstract = "The assessment of land degradation and the quantification of its effects on land productivity have been both a scientific and political challenge. After four decades of Earth Observation (EO) applications, little agreement has been gained on the magnitude and direction of land degradation in the Sahel. The large number of EO datasets and methods associated with the complex interactions among biophysical and social drivers of ecosystem changes make it difficult to apply aggregated EO indices for these non-linear processes. Hence, while many studies stress that the Sahel is greening, others indicate no trend or browning. The different generations of sensors, the granularity of studies, the study period, the applied indices and the assumptions and/or computational methods impact these trends. Consequently, many uncertainties exist in regression models between rainfall, biomass and various indices that limit the ability of EO science to adequately assess and develop a consistent message on the magnitude of land degradation. We suggest several improvements: (1) harmonize time-series data, (2) promote knowledge networks, (3) improve data-access, (4) fill data gaps, (5) agree on scales and assumptions, (6) set up a denser network of long-term field-surveys and (7) consider local perceptions and social dynamics. To allow multiple perspectives and avoid erroneous interpretations, we underline that EO results should not be interpreted without contextual knowledge.",
keywords = "Desertification, drylands, land degradation, NDVI, Productivity, Remote sensing, Sahel, vegetation indices",
author = "Cheikh Mbow and Brandt, {Martin Stefan} and Issa Ouedraogo and {de Leeuw}, Jan and Michael Marshall",
note = "00000",
year = "2015",
month = apr,
day = "1",
doi = "10.3390/rs70404048",
language = "English",
volume = "7",
pages = "4048--4067",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "M D P I AG",
number = "4",

}

RIS

TY - JOUR

T1 - What four decades of earth observation tell us about land degradation in the Sahel?

AU - Mbow, Cheikh

AU - Brandt, Martin Stefan

AU - Ouedraogo, Issa

AU - de Leeuw, Jan

AU - Marshall, Michael

N1 - 00000

PY - 2015/4/1

Y1 - 2015/4/1

N2 - The assessment of land degradation and the quantification of its effects on land productivity have been both a scientific and political challenge. After four decades of Earth Observation (EO) applications, little agreement has been gained on the magnitude and direction of land degradation in the Sahel. The large number of EO datasets and methods associated with the complex interactions among biophysical and social drivers of ecosystem changes make it difficult to apply aggregated EO indices for these non-linear processes. Hence, while many studies stress that the Sahel is greening, others indicate no trend or browning. The different generations of sensors, the granularity of studies, the study period, the applied indices and the assumptions and/or computational methods impact these trends. Consequently, many uncertainties exist in regression models between rainfall, biomass and various indices that limit the ability of EO science to adequately assess and develop a consistent message on the magnitude of land degradation. We suggest several improvements: (1) harmonize time-series data, (2) promote knowledge networks, (3) improve data-access, (4) fill data gaps, (5) agree on scales and assumptions, (6) set up a denser network of long-term field-surveys and (7) consider local perceptions and social dynamics. To allow multiple perspectives and avoid erroneous interpretations, we underline that EO results should not be interpreted without contextual knowledge.

AB - The assessment of land degradation and the quantification of its effects on land productivity have been both a scientific and political challenge. After four decades of Earth Observation (EO) applications, little agreement has been gained on the magnitude and direction of land degradation in the Sahel. The large number of EO datasets and methods associated with the complex interactions among biophysical and social drivers of ecosystem changes make it difficult to apply aggregated EO indices for these non-linear processes. Hence, while many studies stress that the Sahel is greening, others indicate no trend or browning. The different generations of sensors, the granularity of studies, the study period, the applied indices and the assumptions and/or computational methods impact these trends. Consequently, many uncertainties exist in regression models between rainfall, biomass and various indices that limit the ability of EO science to adequately assess and develop a consistent message on the magnitude of land degradation. We suggest several improvements: (1) harmonize time-series data, (2) promote knowledge networks, (3) improve data-access, (4) fill data gaps, (5) agree on scales and assumptions, (6) set up a denser network of long-term field-surveys and (7) consider local perceptions and social dynamics. To allow multiple perspectives and avoid erroneous interpretations, we underline that EO results should not be interpreted without contextual knowledge.

KW - Desertification, drylands, land degradation, NDVI, Productivity, Remote sensing, Sahel, vegetation indices

U2 - 10.3390/rs70404048

DO - 10.3390/rs70404048

M3 - Journal article

VL - 7

SP - 4048

EP - 4067

JO - Remote Sensing

JF - Remote Sensing

SN - 2072-4292

IS - 4

ER -

ID: 138394591