Definitions and Mapping of East African Wetlands: A Review <s> From Land Use/Land Cover Classification to Class-Specific Inventory: The Rationale of Wetland Mapping <s> From foreword: "This report represents the most current methodology available for wetland classification and culminates a long-term effort involving many wetland scientists." <s> BIB001 </s> Definitions and Mapping of East African Wetlands: A Review <s> From Land Use/Land Cover Classification to Class-Specific Inventory: The Rationale of Wetland Mapping <s> A global data base of wetlands at 1° resolution has been developed from the integration of three independent global, digital sources: (1) vegetation, (2) soil properties and (3) fractional inundation in each 1° cell. The integration yielded a global distribution of wetland sites identified with in situ ecological and environmental characteristics. The wetland sites have been classed into five major wetland groups on the basis of environmental characteristics governing methane emissions. The global wetland area derived in this study is ∼5.3 × 1012m2, approximately twice the wetland area previously used in methane-emission studies. Methane emission was calculated using methane fluxes for the major wetland groups, and simple assumptions about the duration of the methane production season. The annual methane emission from wetlands is ∼110 Tg, well within the range of previous estimates (11-300 Tg). Tropical/subtropical peat-poor swamps from 20°N-30°S account from ∼30% of the global wetland area and ∼25% of the total methane emission. About 60% of the total emission comes from peat-rich bogs concentrated from 50°-7O°N, suggesting that the highly seasonal emission from these ecosystems is the major contributor to the large annual oscillations observed in atmospheric methane concentrations at these latitudes. <s> BIB002 </s> Definitions and Mapping of East African Wetlands: A Review <s> From Land Use/Land Cover Classification to Class-Specific Inventory: The Rationale of Wetland Mapping <s> Researchers from the U.S. Geological Survey, University of Nebraska-Lincoln and the European Commission's Joint Research Centre, Ispra, Italy produced a 1 km resolution global land cover characteristics database for use in a wide range of continental-to global-scale environmental studies. This database provides a unique view of the broad patterns of the biogeographical and ecoclimatic diversity of the global land surface, and presents a detailed interpretation of the extent of human development. The project was carried out as an International Geosphere-Biosphere Programme, Data and Information Systems (IGBP-DIS) initiative. The IGBP DISCover global land cover product is an integral component of the global land cover database. DISCover includes 17 general land cover classes defined to meet the needs of IGBP core science projects. A formal accuracy assessment of the DISCover data layer will be completed in 1998. The 1 km global land cover database was developed through a continent-by-continent unsupervised ... <s> BIB003 </s> Definitions and Mapping of East African Wetlands: A Review <s> From Land Use/Land Cover Classification to Class-Specific Inventory: The Rationale of Wetland Mapping <s> Abstract Wetland extent was mapped for the central Amazon region, using mosaicked L-band synthetic aperture radar (SAR) imagery acquired by the Japanese Earth Resources Satellite-1. For the wetland portion of the 18×8° study area, dual-season radar mosaics were used to map inundation extent and vegetation under both low-water and high-water conditions at 100-m resolution, producing the first high-resolution wetlands map for the region. Thematic accuracy of the mapping was assessed using high-resolution digital videography acquired during two aerial surveys of the Brazilian Amazon. A polygon-based segmentation and clustering was used to delineate wetland extent with an accuracy of 95%. A pixel-based classifier was used to map wetland vegetation and flooding state based on backscattering coefficients of two-season class combinations. Producer's accuracy for flooded and nonflooded forest classes ranged from 78% to 91%, with lower accuracy (63–65%) for flooded herbaceous vegetation. Seventeen percent of the study quadrat was occupied by wetlands, which were 96% inundated at high water and 26% inundated at low water. Flooded forest constituted nearly 70% of the entire wetland area at high water, but there are large regional variations in the proportions of wetland habitats. The SAR-based mapping provides a basis for improved estimates of the contribution of wetlands to biogeochemical and hydrological processes in the Amazon basin, a key question in the Large-Scale Biosphere–Atmosphere Experiment in Amazonia. <s> BIB004 </s> Definitions and Mapping of East African Wetlands: A Review <s> From Land Use/Land Cover Classification to Class-Specific Inventory: The Rationale of Wetland Mapping <s> Aim In the framework of the Global Land Cover 2000 (GLC 2000), a land-cover map of Africa has been produced at a spatial resolution of 1 km using data from four sensors on-board four different Earth observing satellites. ::: ::: Location The map documents the location and distribution of major vegetation types and non-vegetated land surface formations for the entire African continent plus Madagascar and the other surrounding islands. ::: ::: Methods The bulk of these data were acquired on a daily basis throughout the year 2000 by the VEGETATION sensor on-board the SPOT-4 satellite. The map of vegetation cover has been produced based upon the spectral response and the temporal profile of the vegetation cover. Digital image processing and geographical information systems techniques were employed, together with local knowledge, high resolution imagery and expert consultation, to compile a cartographic map product. Radar data and thermal sensors were also used for specific land-cover classes. ::: ::: Results A total of 27 land cover categories are documented, which has more thematic classes than previously published land cover maps of Africa contain. Systematic comparison with existing land cover data and 30-m resolution imagery from Landsat are presented, and the map is also compared with other pan-continental land cover maps. The map and digital data base are freely available for non-commercial uses from http://www.gvm.jrc.it/tem/africa/products.htm ::: ::: Main conclusions The map improves our state of knowledge of the land-cover of Africa and presents the most spatially detailed view yet published at this scale. This first version of the map should provide an important input for regional stratification and planning purposes for natural resources, biodiversity and climate studies. <s> BIB005 </s> Definitions and Mapping of East African Wetlands: A Review <s> From Land Use/Land Cover Classification to Class-Specific Inventory: The Rationale of Wetland Mapping <s> Abstract Monitoring and understanding the physical, chemical and biological status of global inland waters are immensely important to scientists and policy makers alike. Whereas conventional monitoring approaches tend to be limited in terms of spatial coverage and temporal frequency, remote sensing has the potential to provide an invaluable complementary source of data at local to global scales. Furthermore, as sensors, methodologies, data availability and the network of researchers and engaged stakeholders in this field develop, increasingly widespread use of remote sensing for operational monitoring of inland waters can be envisaged. This special issue on Remote Sensing of Inland Waters comprises 16 articles on freshwater ecosystems around the world ranging from lakes and reservoirs to river systems using optical data from a range of in situ instruments as well as airborne and satellite platforms. The papers variably focus on the retrieval of in-water optical and biogeochemical parameters as well as information on the biophysical properties of shoreline and benthic vegetation. Methodological advances include refined approaches to adjacency correction, inversion-based retrieval models and in situ inherent optical property measurements in highly turbid waters. Remote sensing data are used to evaluate models and theories of environmental drivers of change in a number of different aquatic ecosystems. The range of contributions to the special issue highlights not only the sophistication of methods and the diversity of applications currently being developed, but also the growing international community active in this field. In this introductory paper we briefly highlight the progress that the community has made over recent decades as well as the challenges that remain. It is argued that the operational use of remote sensing for inland water monitoring is a realistic ambition if we can continue to build on these recent achievements. <s> BIB006
The compilation of coarse/medium spatial resolution regional and global land use/land cover classifications (LUCs) utilizing optical satellite data began when the NOAA-AVHRR sensor system became operational in the 1980s. Table 3 lists important LUCs that have been generated since that time, principally using optical satellite data and classification schemes. A wetland land cover class is frequently omitted in these classification systems BIB004 . One or more wetlands or similar class(es) is present in only 58% (15 of 26) of these schemes. This lack of precision regarding wetlands in LUCs results from a number of factors. Difficulties in the definition of wetlands on a global scale and lack of standardization hamper the merging of wetland types into a single classification scheme. The complexity of wetland systems  means that they may evolve in many different types of habitats, complicating their delineation from uplands. Cowardin et al. BIB001 maintained that "…(f)or example, wetlands and farmlands are not necessarily exclusive. Many areas that we define as wetlands are farmed during dry periods." This is an example of how wetlands may be obscured by other land cover classes. Wetlands are quite likely to be concealed by other classes BIB004 and not identifiable in remotely-sensed data. The "optical complexity" of inland water surfaces described by Palmer et al. BIB006 hampers remote sensing analyses of wetland environments, which can be considered as a subgroup of inland waters. For these reasons, the absence of wetland categories in LUC systems is likely, especially if the specific land surface condition of seasonal or permanent wetness was not a focus of the mapping effort. Darras et al.  attempt to include a wetland dataset in a global land cover classification scheme. To provide this complementary wetland inventory with the International Geosphere-Biosphere Programme (IGBP) Land Cover Dataset  , existing available wetland layers were merged BIB002 BIB003 . The outcome of this effort was a global grid map that indicated per-pixel percentages of cover by wetlands. The authors of the study emphasized that this product was considered an approximation and that contemporary global LUC systems likely underestimate the global extent of wetlands  . This product is a component of an LUC system, as well as a transition to a global wetland map and, therefore, is also included in Table 4 . Supported by the Food and Agricultural Organisation (FAO), Di Gregorio and Jansen published Version 1.0 of the Land Cover Classification System (LCCS) in the year 2000  . This LUC classification was used for the Global Land Cover 2000 project (GLC2000) BIB005 , as well as for the GlobCover Project [78] . Although the system applies a dichotomous phase that explicitly separates terrestrial and aquatic or regularly-flooded classes, this differentiation is not directly reflected in the final data product. A limited assessment comparing the segments of the GLC2000 [77] and GlobCover [78] data layers that cover the four GlobE Wetlands test sites in East Africa is shown in Figure 3 . A lack of precision regarding wetlands in the LUC classification systems is reflected in these maps. The wetlands in the regions of interest are simply not mapped in the GlobCover and GLC 2000 products. This example demonstrates that, even if a wetland class is included in the classification scheme, the area and extent of wetland classes estimated in global LUC data products still may be underestimated. GlobCover's spatial resolution is 300 m, and the classification was based on phenological metrics derived from Medium Resolution Imaging Spectrometer (MERIS) Bidirectional Reflection Distribution Function data [78] . The pixel size of the GLC2000 product is 1 km, and land cover classes were derived by multi-sensor classification. GLC2000 vegetation formations were derived from the SPOT Vegetation dataset, and flooded forests were identified using radar data [77] . The coarse resolution of the global LUC products was a limitation in wetland detection; fragmented wetland surfaces are often too small for the spatial resolution and mapping scale. This issue also becomes obvious in Figure 3 , especially in the GLC2000 dataset with its large pixel size of 1 km. Coarse-or medium-resolution LUCs provide insufficient information regarding the location and extent of wetlands and, thus, are not appropriate for use by scientists, decision makers or stakeholders responsible for wetland research, analyses, management or conservation. Wetlands therefore must be mapped separately. Such wetland maps that are relevant to the East Africa region are discussed in the following section. 