Definitions and Mapping of East African Wetlands: A Review <s> Research Outlook <s> The Okavango inland Delta in Botswana is characterized by a high spatial and temporal variation in vegetation patches and flooding. Predicting the effects of escalating development projects in this pristine wildlife area is hampered by a lack of accurate maps. Efforts using traditional statistical methods have been futile. The processes forming this highly dynamic environment, however, give rise to a well-documented consistency in the land cover pattern at scales ranging from single island architecture to an overall gradient in wetland, flood plain and island occurrence. We conducted a classification in a two-step process starting with statistical methods, and then refining using indices and flooding data. The indices and flooding data were created and selected to make possible the inferring of knowledge about the patterns at different scales through declarative IF ... THEN ... statements. The initial statistical classification achieved a best result of 46% accuracy for 10 classes, whereas the rule-based classification achieved an accuracy of 63%. Application of the derived classification for mapping islands and topography shows a surprisingly high accuracy. <s> BIB001 </s> Definitions and Mapping of East African Wetlands: A Review <s> Research Outlook <s> Over one hundred wetland specialists and Earth Observation experts from around the world gathered at the European Space Agency's 'GlobWetland Symposium: Looking at wetlands from space' in Frascati, Italy, from 19 to 20 October, 2006. The aim of the Symposium was to stimulate discussion between the two communities by reviewing the latest developments in Earth Observation (EO) for the inventory, assessment and monitoring of wetlands and identify key scientific, technical and policy-relevant challenges for the future. The results provide an overview of the key areas of current research in the use of EO for mapping and managing wetlands, while also pointing out gaps that could hinder global inventory, assessment and monitoring of wetlands. This paper provides a summary of the main outputs with a focus on the role of EO technologies in supporting the implementation of the Ramsar Convention on Wetlands. The summary contains a qualitative analysis of the state of the art and considers possible directions and priorities for future research, development and application of EO-based technologies in wetland management. In this context we: 1) highlight those applications where EO technologies are ready for wider uptake by wetland managers, and provide suggestions for supporting such uptake; 2) indicate where EO technologies and applications currently in the research and development stages could potentially be useful in wetland management; and 3) provide recommendations for new research and development of EO technologies, that can be utilized to address aspects of wetland management not covered by the range of current EO applications. <s> BIB002 </s> Definitions and Mapping of East African Wetlands: A Review <s> Research Outlook <s> Summary A map of temporary small water bodies (TSWB) at 1 km resolution was derived for the arid, semi-arid and dry sub-humid regions of sub-Saharan western Africa where the spatio-temporal distribution of actual surface water occurrence exhibits high inter- and intra-annual variability. Water bodies and humid areas have been mapped and characterized by the analysis of 10 daily small water bodies (SWB) maps based on SPOT VEGETATION (VGT) data spanning the period January 1999–September 2007. Further analysis of the SWB time series provided additional information about the seasonal recurrence of water bodies as well as their hydrological function. A map derived from a continuous time series assures the inclusion of temporary features, a clear advantage compared to other datasets, which are based on several single date observations. The method described in this paper targets at a rapid creation of TSWB maps based on the SWB time series for different time intervals and regions. An accuracy assessment has been carried out with a stratified random sampling approach and a one-stage cluster analysis that relies on high-resolution satellite data to verify the detected water bodies. The overall accuracy, considering only the commission error, is 95.4% for the whole study region, with best results in the arid and semi-arid climate zone. The method to map water bodies delivers satisfactory results, particularly for sparsely vegetated areas as well as flat areas of the study region. In more humid, more vegetated areas and in mountainous areas, the possibility of false detections increases due to surface characteristics. <s> BIB003 </s> Definitions and Mapping of East African Wetlands: A Review <s> Research Outlook <s> The spatial resolution of Landsat imagery has proven to be well suited for the analysis of vegetation patterns and dynamics at regional scale; however, the low temporal frequency is often a limitation for the quantification of vegetation dynamics. The spatial and temporal adaptive reflectance fusion model (STARFM) combines moderate resolution imaging spectrometer (MODIS) and Landsat thematic mapper/enhanced thematic mapper plus (TM/ETM+) imagery to a high spatiotemporal resolution dataset. A time series of 333 STARFM images was generated between February 2000 and September 2007 (8-day interval) at Landsat spatial and spectral resolution for a 12×10 km heterogeneous test area within the North Queensland Savannas. Time series of observed Landsat and predicted STARFM images correlated high for each spectral band (0.89 to 0.99). The STARFM algorithm was tested in a regionalization study where sudden change events were analyzed for a pallustrine wetland. A MODIS subpixel analysis showed a very close relationship between STARFM normalized difference vegetation index (NDVI) data and MODIS NDVI data (root mean square error of 0.027). A phenological description of the major vegetation classes within the region revealed distinct differences and lag times within the ecosystem. The 2004 dry season NDVI minimum-map correlated highly with the validated 2004 foliage projective cover product (r2 = 0.92) from the Queensland Department of Environment and Resource Management. <s> BIB004
The ability to extend findings from local-level studies requires consistent knowledge about regional wetland distribution. For example, to improve international implementation of the Ramsar Convention, remote sensing experts cite the need for a "…better collaboration between…countries in a region…to harmonise…classification systems, build shared spectral libraries (and) strengthen mechanisms to share information for inventory and monitoring" BIB002 . To overcome the existing shortages in East African wetland mapping that were analysed and described in detail in this review, our proposition is to use a multisensor, multitemporal data analysis approach. The East African region extends over approximately 180 million ha  . This large size, along with the limited accessibility of most wetland areas, their remoteness and dynamic seasonal extent, make comprehensive ground-based mapping impossible. Utilizing remote sensing techniques can overcome these limitations. Repeated sequential data acquisitions with a given sensor system enable automated analyses of surface dynamics at regular temporal intervals. Through the application of remotely-sensed data, wetland surfaces can be operationally mapped and monitored on an objective, systematic and synoptic basis  at comparatively low cost. Though hindered by a number of factors BIB001 , regular and ongoing monitoring of wetland sites in large and remote areas is most efficiently implemented by non-intrusive remote sensing data collection and analysis. Multisensor remote sensing data and analyses constitute the most promising approach for creating regional wetlands maps that are cross-boundary, continuous, comprehensive, quality controlled and accuracy validated. Multiple sensors acquire data independently [24] , which eliminates cross-dependencies among systems. Extensive satellite data time series are now available without restriction from the archives of NOAA-AVHRR, MODIS Terra and Aqua, SPOT Vegetation and Landsat systems. The low to medium spatial resolution of these systems might cause systematic mapping errors due to the fragmented nature of many wetlands and their small size. These limitations can be overcome by the additional application of high-resolution sensors, as was successfully applied to an Australian wetland by Schmidt et al. BIB004 , or, in the future, the European Space Agency's (ESA) Sentinel system. Nevertheless, due to the strong seasonal variation in wetland extent, a multitemporal approach is promising for wetland detection over a large areal extent. ESA's Sentinel satellite program, which is currently initiating its operational phase, has significant potential utility for wetland research. The Sentinel-1 satellite includes a radar system with the capability of collecting cloud-free water-and moisture-specific data. Sentinel-2 incorporates a fine spatial resolution 10-meter multispectral sensor and will orbit with a short, five-day revisit time. The combination of these radar and optical systems holds great promise for wetland mapping [116] . These sensors will also provide data for the GlobWetland III Africa project, which aims to enhance wetland management in line with the Ramsar Convention  . GlobWetland III Africa could also benefit from regional maps, as current project objectives focus solely on individual wetlands and do not include the objective of providing an overview of the distribution and extent of existing wetlands. A region-wide wetland map will be created within the GlobE Wetlands project using multitemporal remote sensing data and techniques. This approach will take advantage of the discrete set of wetland temporal surface reflectance signatures that can be measured against the surrounding uplands. Haas et al. BIB003 have used coarse-resolution optical satellite data in time series to successfully map ephemeral ponds and wetlands in arid and semi-arid Sub-Saharan West Africa. To derive the wetland map layer for the GlobE Wetlands project region, a suite of active and passive satellite data will be integrated with medium-resolution satellite time series data. This approach of combining sensors over a time range is promising in overcoming the problem of frequent cloud coverage in (sub) tropical regions, like East Africa. A decision tree classifier will be implemented to derive phenological indicators for primary wetland identification. In situ ancillary data will also be collected from four field test sites by researchers from a number of disciplines. This collection of field data will be representative of typical regional wetlands and will significantly contribute to the project by improving the accuracy validation of the final data product. In addition to the comparison to existing wetland datasets, we are able to collect ground truth data extensively and therefore expect to be able to reach a high level of mapping accuracy. Due to the fact that this study will cover the East African region, which is rich in environmental gradients that host a wide range of wetland types, we also expect that this effort will benefit future global wetland mapping efforts. The processing could serve as a prototype for larger studies, especially as it will rely on freely accessible datasets and, therefore, will represent a low-cost mapping approach. In keeping with fundamental project objectives, the results from this mapping effort will be publicly available to researchers and all those participating in the field of sustainable wetland management.