Mapping small wetlands of Kenya and Tanzania using remote sensing techniques

Mwita, Emiliana; Menz, Gunter; Misana, Salome; Becker, M.; Kisanga, Danielson; Boehme, B.

doi:10.1016/j.jag.2012.08.010

Cited by 55 publications

(34 citation statements)

References 18 publications

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“…Table 1 shows the IDs, paths, and rows of Landsat images utilized in this study. To delineate the wetland, a SRTM digital elevation model was processed using the standard pit-filling algorithms to allow unique determination of downslope flow paths [17], and the resultant raster was utilized to derive the flow direction map that was later used to compute the local slope in degrees, using the slope function in ArcGIS 10.2 (provided by ESRI, California, USA) [18]. Different threshold values were tested for the delineation of the wetland and its fringe areas.…”

Section: Datasetsmentioning

confidence: 99%

“…Using July 2015 image data, unsupervised image clustering was conducted using the iterative self-organizing data analysis (ISODATA) algorithm [23]; after which, a number of natural clusters were generated following 100 iterations in a self-organizing way [18]. Since the target wetland subset images were used, only 5 clusters were produced.…”

Section: Image Processing and Analysismentioning

confidence: 99%

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Mapping and Monitoring the Akagera Wetland in Rwanda

et al. 2017

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Wetland maps are a prerequisite for wetland development planning, protection, and restoration. The present study aimed at mapping and monitoring Rwanda's Akagera Complex Wetland by means of remote sensing and geographic information systems (GIS). Landsat data, spanning from 1987 to 2015, were acquired from different sensor instruments, considering a 5-year interval during the dry season and the shuttle radar topographic mission (SRTM) digital elevation model (30-m resolution) was used to delineate the wetland. The mapping and delineation results showed that the wetland narrowly extends along the Rwanda-Tanzania border from north to south, following the course of Akagera River and the total area can be estimated at 100,229.76 ha. After waterbodies that occupy 30% of the wetland's surface area, hippo grass and Cyperus papyrus are also predominant, representing 29.8% and 29%, respectively. Floodplain and swamp forest have also been inventoried in smaller proportions. While the wetland extent has apparently remained stable, the inhabiting waterbodies have been subject to enormous instability due to invasive species. Lakes, such as Mihindi, Ihema, Hago and Kivumba have been shrinking in extent, while Lake Rwanyakizinga has experienced a certain degree of expansion. This study represents a consistent decision support tool for Akagera wetland management in Rwanda.

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Section: Datasetsmentioning

confidence: 99%

Section: Image Processing and Analysismentioning

confidence: 99%

Mapping and Monitoring the Akagera Wetland in Rwanda

et al. 2017

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“…Thus, future HR hyperspectral satellite sensors, beside the only existing coarser resolution Hyperion, would highly benefit timely wetland monitoring. Airborne optical cameras have been used for upland swamp (Lechner et al 2012) and wetland (Mwita et al 2013) mapping, coarser resolution Landsat data being insufficient if used alone, for the latter application. Super-resolution techniques have been proposed to improve mapping by increasing the spatial resolution of satellite images, while preserving their spectral properties, e.g.…”

Section: Aquatic Mappingmentioning

confidence: 99%

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

2015

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Recognizing the imperative need for biodiversity protection, the Convention on Biological Diversity (CBD) has recently established new targets towards 2020, the so-called Aichi targets, and updated proposed sets of indicators to quantitatively monitor the progress towards these targets. Remote sensing has been increasingly contributing to timely, accurate, and cost-effective assessment of biodiversity-related characteristics and functions during the last years. However, most relevant studies constitute individual research efforts, rarely related with the extraction of widely adopted CBD biodiversity indicators. Furthermore, systematic operational use of remote sensing data by managing authorities has still been limited. In this study, the Aichi targets and the related CBD indicators whose monitoring can be facilitated by remote sensing are identified. For each headline indicator a number of recent remote sensing approaches able for the extraction of related properties are reviewed. Methods cover a wide range of fields, including: habitat extent and condition monitoring; species distribution; pressures from unsustainable management, pollution and climate change; ecosystem service monitoring; and conservation status assessment of protected areas. The advantages and limitations of different remote sensing data and algorithms are discussed. Sorting of the methods based on their reported accuracies is attempted, when possible. The extensive literature survey aims at reviewing highly performing methods that can be used for large-area, effective, and timely biodiversity assessment, to encourage the more systematic use of remote sensing solutions in monitoring progress towards the Aichi targets, and to decrease the gaps between the remote sensing and management communities.

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“…During the first phase of this project, 51 wetlands smaller in size than 500 ha were identified within Kenya and Tanzania [111]. Mwita et al [112,113] mapped a number of these in detail by applying TerraSAR-X and RapidEye high spatial resolution remotely-sensed data.…”

Section: Synthesis: the Need For A Regional Wetland Mapmentioning

confidence: 99%

Definitions and Mapping of East African Wetlands: A Review

Amler

Schmidt²,

Menz

2015

Remote Sensing

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Wetlands provide invaluable ecosystem services and contribute significantly to food security around the world. To maintain these functions, wetlands need to be protected from rapid transformation and overuse. Spatially-explicit information is required for sustainable wetland management. Development of wetland maps based on remote sensing requires a clear-cut definition of wetlands. This review was undertaken to improve the understanding of these habitats from a remote sensing perspective and to determine available wetland map layers for the East African countries of Kenya, Rwanda, Tanzania and Uganda. This study includes three components: (1) a review of the availability and types of wetland definitions from the scientific literature record (including 245 separate references); (2) a systematic analysis of land use/land cover classifications and the conceptual approaches and spatial coverages of wetland classes for each system; and (3) a depiction of wetland layers and a discussion of their suitability for use in regional inventories. Our literature review shows that a standard definition of wetlands is not in use, and a specific definition of wetlands is not given in more than 40% of the reviewed remote sensing publications. Spatial information on East African wetlands is currently insufficient for use in regional wetland management. OPEN ACCESS

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Mapping small wetlands of Kenya and Tanzania using remote sensing techniques

Cited by 55 publications

References 18 publications

Mapping and Monitoring the Akagera Wetland in Rwanda

Mapping and Monitoring the Akagera Wetland in Rwanda

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

Definitions and Mapping of East African Wetlands: A Review

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