Digital processing of landsat thematic mapper satellite data for land cover classification using statistical methods for accuracy assessment: a case study of Ngerengere watershed
| dc.contributor.author | Mahuha, Fares Enock | |
| dc.date.accessioned | 2023-09-20T07:01:40Z | |
| dc.date.available | 2023-09-20T07:01:40Z | |
| dc.date.issued | 1998 | |
| dc.description | PhD Thesis | en_US |
| dc.description.abstract | This study involved primarily digital image processing and interpretation land for classification . cover Part of Ngerengere watershed covering about 300 km2 was taken as a case study Land cover which relates to the type of feature present on the surface of the Earth of the study area was elaborated. The procedures involved were reconnaissance survey to acquire 'a priori' knowledge about the u n s u pe r v i s e d area, classi f icat ion, field work classification, for rectification and restoration, ground supervised truthing, image ultimately producing and a land cover map of Ngerengere watershed. ERDAS 7.5 was the remote sensing (RS) software applied. The elaborated accuracy, land using cover map statistical was assessed packages. foric.s Overall classification accuracy (OCA) was about 70% which was below the recommended minimum level of interpretation accuracy value of 85%. It was however, revealed that the low OCA was substantially attributed by low producer's accuracy for the class of built-up areas which was only 22%. Although the produced land cover map had relatively low OCA, it had agood correlation with the present land use and vegetation. Further statistical analysis, by use of KHAT (K) statistics gave a value of 0.65 which is above 0.5 and approaches 1.0, hence acceptance of the land cover map produced from thatiii classification as primary data for land use planning. It percentage of also indicated extent the which to correct values of an error matrix used are due to true agreement and not by chance agreement. Chi-square (X2)distribution to test the goodness of fit of the land cover map elaborated, concluded absence of significant difference between the obtained and recommended OCA at significance level reject of and hence absence of enough evidence to 0.01, the classification for various applications like proposal for land use planning. In order to come up with a sustainable land use planning of the area, category other data are required. needed its own ancillary Every land cover data which are site specific to come up with. a proposal or alternatives for land use planning of an area. For instance, agricultural lands and rangelands classes needed much more ancillary data due to their spectral similarity and inseparability characteristics revealed during this study. Finally it is recommended for continuation of the study so as to come up with a sustainable land use planning of an area because thereis a problem already and timely intervention is imperative operation for the betterment of future generation. | en_US |
| dc.description.sponsorship | The GTZ/SACCAR | en_US |
| dc.identifier.uri | http://www.suaire.sua.ac.tz/handle/123456789/5749 | |
| dc.language.iso | en | en_US |
| dc.publisher | Sokoine University of Agriculture | en_US |
| dc.subject | Land Cover Classification | en_US |
| dc.subject | Digital Processing | en_US |
| dc.subject | Landsat Thematic Mapper Satellite Data | en_US |
| dc.subject | Ngerengere Watershed | en_US |
| dc.title | Digital processing of landsat thematic mapper satellite data for land cover classification using statistical methods for accuracy assessment: a case study of Ngerengere watershed | en_US |
| dc.type | Thesis | en_US |