Mapping the Dabus Wetlands, Ethiopia, Using Random Forest Classification of Landsat, PALSAR and Topographic Data

Pierre Dubeau, Douglas King, Dikaso Unbushe, Lisa-Maria Rebelo
2017 Remote Sensing  
The Dabus Wetland complex in the highlands of Ethiopia is within the headwaters of the Nile Basin and is home to significant ecological communities and rare or endangered species. Its many interrelated wetland types undergo seasonal and longer-term changes due to weather and climate variations as well as anthropogenic land use such as grazing and burning. Mapping and monitoring of these wetlands has not been previously undertaken due primarily to their relative isolation and lack of resources.
more » ... lack of resources. This study investigated the potential of remote sensing based classification for mapping the primary vegetation groups in the Dabus Wetlands using a combination of dry and wet season data, including optical (Landsat spectral bands and derived vegetation and wetness indices), radar (ALOS PALSAR L-band backscatter), and elevation (SRTM derived DEM and other terrain metrics) as inputs to the non-parametric Random Forest (RF) classifier. Eight wetland types and three terrestrial/upland classes were mapped using field samples of observed plant community composition and structure groupings as reference information. Various tests to compare results using different RF input parameters and data types were conducted. A combination of multispectral optical, radar and topographic variables provided the best overall classification accuracy, 94.4% and 92.9% for the dry and wet season, respectively. Spectral and topographic data (radar data excluded) performed nearly as well, while accuracies using only radar and topographic data were 82-89%. Relatively homogeneous classes such as Papyrus Swamps, Forested Wetland, and Wet Meadow yielded the highest accuracies while spatially complex classes such as Emergent Marsh were more difficult to accurately classify. The methods and results presented in this paper can serve as a basis for development of long-term mapping and monitoring of these and other non-forested wetlands in Ethiopia and other similar environmental settings. Global assessment of wetlands shows that their extent, composition, and condition are still poorly understood [1, [5] [6] [7] . In the Ethiopian highlands where access to water is generally limited, particularly during the dry season, wetlands play a key role in regulating the hydrologic cycle and improving water availability and quality [8, 9] . The establishment of a national inventory and information on the extent, distribution, and characteristics of wetland ecosystems is still in its infancy as there is a paucity of information about some of the country's key wetlands, including the Dabus wetlands, which are the focus of this study. Until recently, knowledge about the significance of the Dabus wetlands was lacking, despite the fact that they include large papyrus swamps supporting a rich biodiversity [10, 11] , while farmers and pastoralists benefit from their provision of water during the dry season. Remote sensing technologies can provide up-to-date spatial and temporal information about wetlands [12] , thereby contributing to sustainable wetland management [13] . Multispectral optical and synthetic aperture radar (SAR) data have been used extensively, either independently or in combination with topographic variables, to map and characterize wetland vegetation in many regions of the world for a variety of goals and applications [12, [14] [15] [16] [17] [18] [19] [20] [21] [22] . Vegetation spectral reflectance in the visible, near-infrared (NIR) and mid-or short-wave infrared (SWIR) is a function of chlorophyll absorption for photosynthesis, structure, biomass and moisture [23, 24] , while SAR backscatter is dependent on surface roughness and moisture. SAR can detect smooth open water surfaces and discriminate different wetland plant and canopy structures [25, 26] . The ability of radar to penetrate clouds, and to some extent, rain, as well as day and night operability are some of the key features that provide a distinct advantage over optical sensors, especially in tropical environments where frequent cloud cover prevails, especially during the rainy season [23, 27] . Wetland plant community distributions are also generally dependent on hydrologic characteristics, which in turn depend to a large degree on topography. Local terrain attributes (e.g., slope and topographic wetness indices) [28, 29] can be readily extracted from existing DEMs and combined with remote sensing data in wetland mapping and analysis. The overall goal of this study was to demonstrate how the Dabus Wetlands, which are important ecosystems that are very challenging to access, can be effectively characterized and mapped using remote sensing and topographic data from multiple sources. This study builds on remote sensing wetland research examples drawn from tropical regions in the Congo Basin [30], South Africa [31, 32] , and the Amazon basin [33, 34] . Emphasis was placed on a need to have free or relatively easy access to data and processing software. The specific research objectives were: (1) determine the relative importance of Landsat, PALSAR and topographic variables in thematic mapping of Dabus wetland classes; and (2) given marked differences between the dry and wet seasons, determine if data from one or both seasons is best for such classification. Materials and Methods Study Area This research focuses on the headwater wetland ecosystems associated with the Dabus River, a large tributary of the Abay-Blue Nile River. The Dabus wetland complex is located in the central western region of Ethiopia (centered on 34 • 55 0 E, 9 • 15 0 N) in the administrative zones of West Wellega (Figure 1) , which is part of the Sudano-Guinea zone [35] . It covers an area of approximately 80,000 ha and lies at an altitude of about 1300 m above sea level. The regional landscape surrounding the Dabus River is comprised of green vegetated hills dominated by cultivated fields. A protracted rainy season starts in March or April and can last to October, while peak rainfalls generally occur from June to September [36] . The mean annual rainfall reported for the study region is approximately 1414 mm; mean annual, minimum and maximum temperatures are 19.8 • C, 11.8 • C and 30.9 • C, respectively [37] . The upstream areas are waterlogged for most of the year while downstream areas are seasonally inundated but remain dry during the dry season. These wetlands present a rich Remote Sens. 2017, 9, 1056 3 of 23 biodiversity, particularly in the generally inaccessible upstream areas as they have been least impacted by anthropogenic pressures. These upstream areas represent relatively pristine habitat that includes large perennially saturated papyrus swamps forming dense (3 to 5 m tall) canopies [38] . They also harbor a large population of common hippopotamus (Hippopotamus amphibius) estimated at several hundred individuals, as well as several rare bird species such as the Shoebill Stork (Balaeniceps rex) and the vulnerable Wattled Crane (Bugeranus carunculatus [39]) during the dry season field survey. Remote Sens. 2017Sens. , 9, 1056 3 of 23 includes large perennially saturated papyrus swamps forming dense (3 to 5 m tall) canopies [38] . They also harbor a large population of common hippopotamus (Hippopotamus amphibius) estimated at several hundred individuals, as well as several rare bird species such as the Shoebill Stork (Balaeniceps rex) and the vulnerable Wattled Crane (Bugeranus carunculatus [39]) during the dry season field survey. and was supported in part by a Natural Sciences and Engineering Council of Canada (NSERC) grant to D. King. The authors would like to express their sincere gratitude to Takeo Tadono at the Japanese Aerospace Exploration Agency (JAXA) for his support and for providing access to ALOS-PALSAR data. We are also indebted to Professor Sebsebe Demissew from Addis Ababa University for his invaluable support to this project, his guidance, and above all for his inspiration. We would also like to thank Koreen Millard and Murray Richardson for providing valuable suggestions and inputs to the analyses. Many thanks to Demiss Mamo Demoz for his indispensable assistance in the field. Author Contributions: Pierre Dubeau developed the original research concept and field survey plan, with the assistance of Dikaso Gojamme Unbushe and Lisa-Maria Rebelo. Douglas J. King advised on the research design, implementation, and analysis as the academic supervisor. Pierre Dubeau wrote the R scripts (adapted from a script provided by Millard and Richardson]) and analyzed the results. Pierre Dubeau wrote the first drafts of the paper and Douglas J. King contributed the main edits and advice on the content. Dikaso Gojamme Unbushe and Lisa-Maria Rebelo provided additional edits and inputs to the content. Conflicts of Interest: The authors declare no conflict of interest.
doi:10.3390/rs9101056 fatcat:fxkhkdrl3vfu3k4xa3eoy5p464