Seasonal Vegetation Changes in the Malinda Wetland Using Bi-Temporal, Multi-Sensor, Very High Resolution Remote Sensing Data Sets

Simple item page
dc.contributor.authorKuria, David N.
dc.contributor.authorMenz, Gunter
dc.contributor.authorMisana, Salome
dc.contributor.authorMwita, Emiliana
dc.contributor.authorThamm, Hans P.
dc.contributor.authorAlvarez, Miguel
dc.contributor.authorMogha, Neema
dc.contributor.authorBecker, M.
dc.contributor.authorOyieke, Helida
dc.date.accessioned2016-09-21T13:13:49Z
dc.date.available2016-09-21T13:13:49Z
dc.date.issued2014-03
dc.description.abstractSmall 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.en_US
dc.identifier.citationKuria, D.N., Menz, G., Misana, S., Mwita, E., Thamm, H.P., Alvarez, M., Mogha, N., Becker, M. and Oyieke, H., 2014. Seasonal vegetation changes in the Malinda Wetland using bi-temporal, multi-sensor, very high resolution remote sensing data sets. Advances in Remote Sensing, 3(01), p.33.en_US
dc.identifier.doi10.4236/ars.2014.31004
dc.identifier.urihttp://hdl.handle.net/20.500.11810/3906
dc.language.isoenen_US
dc.subjectImage Fusionen_US
dc.subjectLand Cover Classificationen_US
dc.subjectUnmanned Aerial Vehicleen_US
dc.subjectChange Vector Analysisen_US
dc.subjectLand Cover Changeen_US
dc.subjectVegetation Phenologyen_US
dc.titleSeasonal Vegetation Changes in the Malinda Wetland Using Bi-Temporal, Multi-Sensor, Very High Resolution Remote Sensing Data Setsen_US
dc.typeJournal Article, Peer Revieweden_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Seasonal Vegetation Changes in the Malinda Wetland Using Bi-Temporal, Multi-Sensor, Very High Resolution Remote Sensing Data Sets.pdf
Size:
7.53 MB
Format:
Adobe Portable Document Format
Description:
Full text
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Department of Geography