Detection of Small Wetlands with Multi Sensor Data in East Africa

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dc.contributor.authorMwita, Emiliana
dc.contributor.authorMenz, Gunter
dc.contributor.authorMisana, Salome
dc.contributor.authorNienkemper, Pamela
dc.date.accessioned2016-09-21T13:20:49Z
dc.date.available2016-09-21T13:20:49Z
dc.date.issued2012-12
dc.description.abstractThe dynamic nature and inaccessibility of wetland ecosystems restricts in situ data collection and promote the use of various remote sensing platforms. This is because of their ability to record large areas in comparatively short time peri-ods and map physically unreachable areas. Sensors in the optical and microwave range of the electromagnetic spectrum play a critical role in wetlands detection and delineation, as they complement each other in data collection. This study examined the potential of optical and microwave remote sensing in detecting the diversity of small wetlands (<500 ha) in the semi-arid and sub humid parts of Laikipia and Pangani plains and the humid parts of Mt. Kenya and Usambara highlands in Kenya and Tanzania, respectively. An intensive field survey was conducted to supplement the remotely sensed data. Decision tree, supervised and unsupervised classification techniques, facilitated the detection of floodplains and inland valley wetlands within the study sites. The results reveal that although optical and microwave data work ef-fectively in the detection of wetlands the latter would be more effective in larger wetlands than those in the scope of this study.en_US
dc.identifier.citationMwita, E., Menz, G., Misana, S. and Nienkemper, P., 2012. Detection of small wetlands with multi sensor data in East Africa.en_US
dc.identifier.doi10.4236/ars.2012.13007
dc.identifier.urihttp://hdl.handle.net/20.500.11810/3925
dc.language.isoenen_US
dc.subjectWetlands Delineationen_US
dc.subjectMicrowaveen_US
dc.subjectOpticalen_US
dc.subjectKenyaen_US
dc.subjectTanzaniaen_US
dc.titleDetection of Small Wetlands with Multi Sensor Data in East Africaen_US
dc.typeJournal Article, Peer Revieweden_US
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