Comparison of object and pixel-based classifications for land-use and land cover mapping in the mountainous Mokhotlong District of Lesotho using high spatial resolution imagery

Simple item page
dc.contributor.authorGegana, Mpho
dc.date.accessioned2017-01-18T08:30:15Z
dc.date.available2017-01-18T08:30:15Z
dc.date.issued2016
dc.descriptionResearch Report submitted in partial fulfilment for the degree of Master of Science (Geographical Information Systems and Remote Sensing) School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg. August 2016.en_ZA
dc.description.abstractThe thematic classification of land use and land cover (LULC) from remotely sensed imagery data is one of the most common research branches of applied remote sensing sciences. The performances of the pixel-based image analysis (PBIA) and object-based image analysis (OBIA) Support Vector Machine (SVM) learning algorithms were subjected to comparative assessment using WorldView-2 and SPOT-6 multispectral images of the Mokhotlong District in Lesotho covering approximately an area of 100 km2. For this purpose, four LULC classification models were developed using the combination of SVM –based image analysis approach (i.e. OBIA and/or PBIA) on high resolution images (WorldView-2 and/or SPOT-6) and the results were subjected to comparisons with one another. Of the four LULC models, the OBIA and WorldView-2 model (overall accuracy 93.2%) was found to be more appropriate and reliable for remote sensing application purposes in this environment. The OBIA-WorldView-2 LULC model was subjected to spatial overlay analysis with DEM derived topographic variables in order to evaluate the relationship between the spatial distribution of LULC types and topography, particularly for topographically-controlled patterns. It was discovered that although that there are traces of the relationship between the LULC types distributions and topography, it was significantly convoluted due to both natural and anthropogenic forces such that the topographic-induced patterns for most of the LULC types had been substantial disrupted.en_ZA
dc.description.librarianLG2017en_ZA
dc.format.extentOnline resource (64 leaves)
dc.identifier.citationGegana, Mpho (2016) Comparison of object and pixel-based classifications for land-use and land cover mapping in the mountainous Mokhotlong Distric of Lesotho using high spatial resolution imagery, University of Witwatersrand, Johannesburg, <http://wiredspace.wits.ac.za/handle/10539/21645>
dc.identifier.urihttp://hdl.handle.net/10539/21645
dc.language.isoenen_ZA
dc.subject.lcshGeospatial data--Data processing
dc.subject.lcshGeographic information systems--Data processing
dc.subject.lcshRemote sensing--Data processing
dc.subject.lcshImage processing--Digital techniques
dc.titleComparison of object and pixel-based classifications for land-use and land cover mapping in the mountainous Mokhotlong District of Lesotho using high spatial resolution imageryen_ZA
dc.typeThesisen_ZA
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Mpho_Gegana_1257041_MSc_RR.pdf
Size:
3.17 MB
Format:
Adobe Portable Document Format
Description:
Main article
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
ETD Collection