Ecosystem mapping at the African continent scale using a hybrid clustering approach based on 1-km resolution multi-annual data from SPOT/VEGETATION

Tchuenté, Armel Thibaut Kaptué; Jong, S.M. de; Roujean, Jean‐Louis; Favier, Charly; Méring, Catherine

doi:10.1016/j.rse.2010.09.015

Cited by 27 publications

(21 citation statements)

References 48 publications

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“…In order to update the former ECOCLIMAP global land cover map (Champeaux et al, 2005;Masson et al, 2003), the Centre National de Recherches Météorologiques, recently developed an innovative classification approach for ecosystems over Africa (ECOCLIMAP-II here after) (Kaptué et al, 2010a). The map was produced at 1/112 • GSD on the basis of a hybrid-unsupervised classifier using 8 years (from January 1, 2000 to December 31, 2007) of normalized difference vegetation index (NDVI) images acquired by SPOT VEGETATION.…”

Section: Ecoclimap-ii Classification (Fig 1d)mentioning

confidence: 99%

“…Consistency assessment was performed on a per-pixel basis at national and continental scale. At the continental scale, errors statistics produce Kappa coefficients of 0.505, 0.430 and 0.420 when compared with GLC2000, GLOBCOVER and MODIS LC-I, respectively (Kaptué et al, 2010a). In this study, ECOCLIMAP-II at level II that contains 21 classes was considered.…”

Section: Ecoclimap-ii Classification (Fig 1d)mentioning

confidence: 99%

“…MODIS, SPOT VEGETATION, and MERIS ENVISAT), the scientific community has witnessed a significant increase in the availability of land cover maps arising from several initiatives. Based on satellite sensor observations acquired in the 2000s, available land cover data products at the African continental scale include: (i) the Global Land Cover 2000 database or GLC2000 (Mayaux et al, 2004) produced by the EC Joint Research Centre, (ii) GLOBCOVER produced by the European Space Agency product (Arino et al, 2008), (iii) the first layer of the MODIS Land Cover Map or MODIS LC-I, a yearly available map produced by Boston University and (iv) ECOCLIMAP-II developed at Météo France (Kaptué et al, 2010a).…”

Section: Introductionmentioning

confidence: 99%

“…(a) GLC2000(Mayaux et al, 2004), (b) GLOBCOVER(Arino et al, 2008), (c) MODIS LC-I, and (d) ECOCLIMAP-II(Kaptué et al, 2010a).…”

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Comparison and relative quality assessment of the GLC2000, GLOBCOVER, MODIS and ECOCLIMAP land cover data sets at the African continental scale

Tchuenté

Roujean

Jong

2011

International Journal of Applied Earth Observation and Geoinfor

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145

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Section: Ecoclimap-ii Classification (Fig 1d)mentioning

confidence: 99%

Section: Ecoclimap-ii Classification (Fig 1d)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…(a) GLC2000(Mayaux et al, 2004), (b) GLOBCOVER(Arino et al, 2008), (c) MODIS LC-I, and (d) ECOCLIMAP-II(Kaptué et al, 2010a).…”

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Comparison and relative quality assessment of the GLC2000, GLOBCOVER, MODIS and ECOCLIMAP land cover data sets at the African continental scale

Tchuenté

Roujean

Jong

2011

International Journal of Applied Earth Observation and Geoinfor

Self Cite

145

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“…Our study suggests that data scarcity due to sensor errors or frequent cloud/snow cover could be reduced by including imagery from neighbouring years. Furthermore, classification errors due to considerable intra-annual variations in dryland vegetation can be largely avoided by including multi-annual time series data from remote sensing observations 72 .…”

Section: Discussionmentioning

confidence: 99%

Forest cover mapping in post-Soviet Central Asia using multi-resolution remote sensing imagery

Yin

Khamzina

Pflugmacher

et al. 2017

Sci Rep

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Despite rapid advances and large-scale initiatives in forest mapping, reliable cross-border information about the status of forest resources in Central Asian countries is lacking. We produced consistent Central Asia forest cover (CAFC) maps based on a cost-efficient approach using multi-resolution satellite imagery from Landsat and MODIS during 2009–2011. The spectral-temporal metrics derived from 2009–2011 Landsat imagery (overall accuracy of 0.83) was used to predict sub-pixel forest cover on the MODIS scale for 2010. Accuracy assessment confirmed the validity of MODIS-based forest cover map with a normalized root-mean-square error of 0.63. A general paucity of forest resources in post-Soviet Central Asia was indicated, with 1.24% of the region covered by forest. In comparison to the CAFC map, a regional map derived from MODIS Vegetation Continuous Fields tended to underestimate forest cover, while the Global Forest Change product matched well. The Global Forest Resources Assessments, based on individual country reports, overestimated forest cover by 1.5 to 147 times, particularly in the more arid countries of Turkmenistan and Uzbekistan. Multi-resolution imagery contributes to regionalized assessment of forest cover in the world’s drylands while developed CAFC maps (available at https://data.zef.de/) aim to facilitate decisions on biodiversity conservation and reforestation programs in Central Asia.

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Spatial and temporal characteristics of rainfall in Africa: Summary statistics for temporal downscaling

Kaptué

Hanan

Prihodko

et al. 2015

Water Resources Research

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An understanding of rainfall characteristics at multiple spatiotemporal scales is of great importance for hydrological, biogeochemical, and land surface modeling studies. In the present study, patterns of rainfall are analyzed over the African continent based on 3 hourly 0.25Tropical Rainfall Measuring Mission (TRMM) estimates between 1998 and 2012 to produce monthly statistical summaries. The selected rain event properties are multiyear means of precipitation total amount (mm), event frequency (number), rate (mm/h), and duration (h) calculated independently for each calendar month. Analysis of 3 hourly and daily events in the 1998-2012 period suggests that rainfall amount can be summarized using gamma probability density functions. Assuming stationarity, gamma probability density functions of the total depth of 3 hourly and daily events are estimated and then used for temporal downscaling of monthly rainfall estimates (past or future). As a result, we generate 3 hourly and daily rainfall estimates that are pixelwise statistically indistinguishable from the observations while preserving monthly totals. Example scripts are provided that can be used to access monthly statistics and implement downscaling using archival (or projected) monthly rainfall estimates. These statistics could also be utilized for the assessment of rainfall from atmospheric models.

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Ecosystem mapping at the African continent scale using a hybrid clustering approach based on 1-km resolution multi-annual data from SPOT/VEGETATION

Cited by 27 publications

References 48 publications

Comparison and relative quality assessment of the GLC2000, GLOBCOVER, MODIS and ECOCLIMAP land cover data sets at the African continental scale

Comparison and relative quality assessment of the GLC2000, GLOBCOVER, MODIS and ECOCLIMAP land cover data sets at the African continental scale

Forest cover mapping in post-Soviet Central Asia using multi-resolution remote sensing imagery

Spatial and temporal characteristics of rainfall in Africa: Summary statistics for temporal downscaling

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