Browsing by Author "Misana, Salome"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Detection of Small Wetlands with Multi Sensor Data in East Africa
    (2012-12) Mwita, Emiliana; Menz, Gunter; Misana, Salome; Nienkemper, Pamela
    The 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.
  • Thumbnail Image
    Item
    Seasonal Vegetation Changes in the Malinda Wetland Using Bi-Temporal, Multi-Sensor, Very High Resolution Remote Sensing Data Sets
    (2014-03) Kuria, David N.; Menz, Gunter; Misana, Salome; Mwita, Emiliana; Thamm, Hans P.; Alvarez, Miguel; Mogha, Neema; Becker, M.; Oyieke, Helida
    Small wetlands in East Africa have grown in prominence driven by the unreliable and diminished rains and the increasing population pressure. Due to their size (less than 500 Ha), these wetlands have not been studied extensively using satellite remote sensing approaches. High spatial resolu-tion remote sensing approaches overcome this limitation allowing detailed inventorying and re-search on such small wetlands. For understanding the seasonal variations in land cover within the Malinda Wetland in Tanzania (350 Ha), two periods were considered, May 2012 coinciding with the wet period (rainy season) and August 2012 coinciding with a fairly rain depressed period (substantially dry but generally cooler season). The wetland was studied using very high spatial resolution orthophotos derived from Unmanned Aerial Vehicle (UAV) photography fused with TerraSAR-X Spotlight mode dual polarized radar data. Using these fused datasets, five main classes were identified that were used to firstly delineate seasonal changes in land use activities and secondly used in determining phenology changes. Combining fuzzy maximum likelihood classification, knowledge classifier and Change Vector Analysis (CVA), land cover classification was undertaken for both seasons. From the results, manifold anthropogenic activities are taking place between the seasons as evidenced by the high conversion rates (63.01 Ha). The phenological change was also highest within the human influence class due to the growing process of cropped land (26.60 Ha). Much of the changes in both cover and phenology are occurring in the mid upper portion of the wetland, attributed to the presence of springs in this portion of the wetland along the banks of River Mkomazi. There is thus seasonality in the observed anthropogenic influence between the wetland and its periphery.