Multi-sensor mapping of West African land cover using MODIS, ASAR and TanDEM-X/TerraSAR-X data

Abstract Land cover information plays an elementary role for regional water and land management, and is an essential variable for the assessment of ecosystem services and regional climate impact. This paper describes the generation of a regionally optimized land cover dataset for West Africa with a spatial resolution of 250 m, which is based on earth observation data from three optical and radar instruments. The choice of sensors is based on their individual strengths and weaknesses in assessing specific land surface types. Annual profiles of the optical Moderate Resolution Imaging Spectroradiometer (MODIS) are analyzed for the classification of vegetated classes including agriculture. The classification approach builds on random forest classification with learning data extracted from higher resolution land cover maps. Envisat Advanced Synthetic Aperture Radar (ASAR) Wide Swath (WS) time series are used, in combination with MODIS data, to delineate permanent and seasonal water bodies. Here, an approach integrating threshold classification and morphological operations is applied. Built-up areas of different densities are identified based on a seamless coverage of radar imagery collected by the satellites TanDEM-X and TerraSAR-X. The detection of settlements is based on an unsupervised classification scheme which exploits texture metrics and backscattering amplitudes of the fine resolution radar sensors. The accuracy assessment of the multi-sensor land cover map yields an overall accuracy of 80% at legend level 1 (9 classes) and 73% at the more detailed legend level 2 (14 classes). Comparisons with available wall-to-wall datasets of the region demonstrate the valuable information content of the presented West African land cover map.

[1]  Damien Sulla-Menashe,et al.  MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets , 2010 .

[2]  René R. Colditz,et al.  Land cover classification with coarse spatial resolution data to derive continuous and discrete maps for complex regions , 2011 .

[3]  Steffen Fritz,et al.  Harmonizing and Combining Existing Land Cover/Land Use Datasets for Cropland Area Monitoring at the African Continental Scale , 2012, Remote. Sens..

[4]  N. Ramankutty,et al.  Modeling the hydrological impact of land-use change in West Africa , 2007 .

[5]  G. Powell,et al.  Terrestrial Ecoregions of the World: A New Map of Life on Earth , 2001 .

[6]  Stefan Dech,et al.  Characterisation of land surface phenology and land cover based on moderate resolution satellite data in cloud prone areas — A novel product for the Mekong Basin , 2013 .

[7]  Christopher Conrad,et al.  Standardized FAO-LCCS land cover mapping in heterogeneous tree savannas of West Africa , 2010 .

[8]  Arturo E. Hernandez,et al.  Generation and analysis of the 2005 land cover map for Mexico using 250m MODIS data , 2012 .

[9]  Millenium Ecosystem Assessment.  Ecosystems and human well-being: synthesis , 2005 .

[10]  M. Friedl,et al.  Mapping global urban areas using MODIS 500-m data: new methods and datasets based on 'urban ecoregions'. , 2010 .

[11]  P. Ciais,et al.  The carbon balance of Africa: synthesis of recent research studies , 2011, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[12]  C. Place,et al.  Classifying the Neotropical savannas of Belize using remote sensing and ground survey , 2006 .

[13]  Giles M. Foody,et al.  Status of land cover classification accuracy assessment , 2002 .

[14]  D. Civco,et al.  Mapping urban areas on a global scale: which of the eight maps now available is more accurate? , 2009 .

[15]  Guoqing Sun,et al.  Hierarchical mapping of Northern Eurasian land cover using MODIS data , 2011 .

[16]  G. Powers,et al.  A Description of the Advanced Research WRF Version 3 , 2008 .

[17]  Steffen Fritz,et al.  Geo-Wiki.Org: The Use of Crowdsourcing to Improve Global Land Cover , 2009, Remote. Sens..

[18]  Arona Diedhiou,et al.  The West African monsoon dynamics. Part I: Documentation of intraseasonal variability , 2003 .

[19]  Shuguang Liu,et al.  Historical and simulated ecosystem carbon dynamics in Ghana: land use, management, and climate , 2008 .

[20]  U. Gessner,et al.  Regional land cover mapping and change detection in Central Asia using MODIS time-series , 2012 .

[21]  F. Evrendilek,et al.  Boosted decision tree classifications of land cover over Turkey integrating MODIS, climate and topographic data , 2011 .

[22]  Tobias Landmann,et al.  Land Cover Analysis on Sub-Continental Scale: FAO LCCS Standard with 250 Meter MODIS Satellite Observations in West Africa , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.

[23]  Erkki Tomppo,et al.  A report to the food and agriculture organization of the united nations (FAO) in support of sampling study for National Forestry Resources Monitoring and Assessment (NAFORMA) in Tanzania , 2010 .

[24]  Stefan Dech,et al.  Land surface dynamics and environmental challenges of the Niger Delta, Africa: Remote sensing-based analyses spanning three decades (1986–2013) , 2014 .

[25]  Thomas Esch,et al.  Urban Footprint Processor—Fully Automated Processing Chain Generating Settlement Masks From Global Data of the TanDEM-X Mission , 2013, IEEE Geoscience and Remote Sensing Letters.

[26]  A. Belward,et al.  GLC2000: a new approach to global land cover mapping from Earth observation data , 2005 .

[27]  Lucy Bastin,et al.  A near real-time water surface detection method based on HSV transformation of MODIS multi-spectral time series data , 2014 .

[28]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[29]  John R. Townshend,et al.  A new global raster water mask at 250 m resolution , 2009, Int. J. Digit. Earth.

[30]  L. Nalley,et al.  Quantifying and mapping multiple ecosystem services change in West Africa , 2013 .

[31]  Martin Herold,et al.  On the Suitability of MODIS Time Series Metrics to Map Vegetation Types in Dry Savanna Ecosystems: A Case Study in the Kalahari of NE Namibia , 2009, Remote. Sens..

[32]  Stefan Dech,et al.  Land Cover Maps for Regional Climate Modeling in West Africa – a Comparison of Datasets , 2012 .

[33]  D. Lettenmaier,et al.  Measuring surface water from space , 2004 .

[34]  M. Boschetti,et al.  Land-use and land-cover change detection in a semi-arid area of Niger using multi-temporal analysis of Landsat images , 2013 .

[35]  E. Dinerstein,et al.  The Global 200: Priority ecoregions for global conservation , 2002 .

[36]  D. Barrett,et al.  Estimating fractional cover of photosynthetic vegetation, non-photosynthetic vegetation and bare soil in the Australian tropical savanna region upscaling the EO-1 Hyperion and MODIS sensors. , 2009 .

[37]  Victor Barrena Arroyo,et al.  A land cover map of Latin America and the Caribbean in the framework of the SERENA project , 2013 .

[38]  J. L. Parra,et al.  Very high resolution interpolated climate surfaces for global land areas , 2005 .

[39]  Bicheron Patrice,et al.  GlobCover - Products Description and Validation Report , 2008 .

[40]  Armel Thibaut Kaptué Tchuenté,et al.  Comparison and relative quality assessment of the GLC2000, GLOBCOVER, MODIS and ECOCLIMAP land cover data sets at the African continental scale , 2011, Int. J. Appl. Earth Obs. Geoinformation.

[41]  Gerhard Krieger,et al.  TanDEM-X: A Satellite Formation for High-Resolution SAR Interferometry , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[42]  Fawwaz T. Ulaby,et al.  Knowledge-based land-cover classification using ERS-1/JERS-1 SAR composites , 1996, IEEE Trans. Geosci. Remote. Sens..

[43]  Marian Vittek,et al.  Land Cover Change Monitoring Using Landsat MSS/TM Satellite Image Data over West Africa between 1975 and 1990 , 2014, Remote. Sens..

[44]  Hannes Taubenböck,et al.  TanDEM-X mission—new perspectives for the inventory and monitoring of global settlement patterns , 2012 .

[45]  P. V. Beukering,et al.  The Niger, a lifeline , 2005 .

[46]  Elmar Csaplovics,et al.  Flood monitoring in a semi-arid environment using spatially high resolution radar and optical data. , 2009, Journal of environmental management.

[47]  Claudia Kuenzer,et al.  Evaluation of seasonal water body extents in Central Asia over the past 27 years derived from medium-resolution remote sensing data , 2014, Int. J. Appl. Earth Obs. Geoinformation.

[48]  A. Roth,et al.  The shuttle radar topography mission—a new class of digital elevation models acquired by spaceborne radar , 2003 .

[49]  Thilo Wehrmann,et al.  Multi-sensoral and automated derivation of inundated areas using TerraSAR-X and ENVISAT ASAR data , 2012 .

[50]  T. Mitchell Aide,et al.  A scalable approach to mapping annual land cover at 250 m using MODIS time series data: A case study in the Dry Chaco ecoregion of South America , 2010 .

[51]  Christopher Conrad,et al.  Estimating the fractional cover of growth forms and bare surface in savannas. A multi-resolution approach based on regression tree ensembles. , 2013 .

[52]  Christopher Conrad,et al.  Integration of Optical and Synthetic Aperture Radar Imagery for Improving Crop Mapping in Northwestern Benin, West Africa , 2014, Remote. Sens..

[53]  B. Holben.  Characteristics of maximum-value composite images from temporal AVHRR data , 1986 .

[54]  Helko Breit,et al.  Interferometric processing of TanDEM-X data , 2011, 2011 IEEE International Geoscience and Remote Sensing Symposium.

[55]  Jordan G. Powers,et al.  A Description of the Advanced Research WRF Version 2 , 2005 .

[56]  R. Lunetta,et al.  Land-cover change detection using multi-temporal MODIS NDVI data , 2006 .