Proceedings, XXth congress: Proceedings, XXth congress

Altan, M. Orhan

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Multivolume work

Persistent identifier:: 1663674213

Title:: Proceedings, XXth congress

Sub title:: Istanbul, 12 - 23 July 2004

Year of publication:: 2004

Place of publication:: Istanbul

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 1663674213

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist aus dem Copyrightjahr ermittelt.; Auch bezeichnet als XXth International Congress for Photogrammetry and Remote Sensing

Editor:: Altan, M. Orhan

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Document type:: Multivolume work

Volume

Persistent identifier:: 166368779X

Title:: Proceedings, XXth congress

Scope:: IV, 226 Seiten

Year of publication:: 2004

Place of publication:: Istanbul

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 166368779X

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(35,B8)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist aus dem Copyrightjahr ermittelt.

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Altan, M. Orhan

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: IMPROVEMENT OF IMAGE CLASSIFICATION WITH THE INTEGRATION OF TOPOGRAPHICAL DATA Deniz Gerçek

Document type:: Multivolume work

Structure type:: Chapter

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B-YF. Istanbul 2004 In this study, a method based on logical channel approach is presented. Limitations introduced by logical channel method are relieved through adjustment of training set so as to provide additional sensitivity to ancillary data. Method is applied on a selected rural land to extract land cover information. Data and Study Area A region that shows variety both in morphology and land cover is selected near Ankara in central Anatolia. Morphological structure is uneven dominated by volcanic mountainous terrain with dissected stream valleys; besides there also exist flat regions. Superior land cover classes in the region belong to the typical continental environment of central Anatolia. Native vegetation is mainly rangelands (Anderson et al. 1976), they are composed of common steppe vegetation species in central Anatolian regions where typical continental climate is prevalent. The native shrubs and brushes of the study area are steppe species of maximum 2- meter height, distributed densely in the terrain. Herbaceous rangelands of the study area are poorly vegetated lands with herbaceous plants of maximum 20-30 cm height. In some areas, herbaceous rangelands are mixed with the native shrubs and brushes of the study area. Moving through north, particular areas are dominated with trees composed mainly of coniferous and partially of deciduous tree species. Apart from the natural land cover, particular land use classes are present in the study area; those are primarily agricultural, residential, industrial and transportational. A subscene of Landsat 7 ETM of May 2000 including bands 1.2.3,4,5,7 is the primary source of the data analysis. Ancillary data is composed of Digital Terrain Model (DTM), slope and aspect of the study region. A group of data is set apart from the classification and used for obtaining ground truth information only. Those data are; IRS panchromatic image with 5 m resolution, forest map form General Directorate of Forest, digital land cover and land use map from General Directorate of Rural Affairs, aerial photograph stereo pairs and field observation data. Preliminary Data Processing 1/25000-scaled topographical map served as a basis to georeference all available data. Remotely sensed data used in the study are free of systematic errors but they have unsystematic errors due to alterations in altitude and attitude. Geometric correction is made via Ground Control Points (GCPs) obtained from topographical map. This procedure is followed by image rectification. A 30x30 meter DTM was produced from 10-meter interval contours digitized from 1/25000-scaled topographical map. Consequently, derivatives of DTM; slope and aspect map with 30x30 meter cell size were generated. Classes Classification level denotes the level of thematic detail for classification. Since the level of classification is dependent on the sensor system and image spatial resolution, the level of classification for the study was set taking the image's information capability into account. Primary data source for the study; Landsat 7 ETM with 30x30 meters resolution is appropriate for performing a first level classification (Jensen, 1996). 54 The land cover and land use categories in the study area are composed of five Level I classes which are; e Urban and Built-up Land e Agricultural Land e Range Land e Forest e Water Bodies From the five Level I classes in the study area, two were excluded. These classes are Urban or built-up land and water bodies. Whereas land cover information can be directly interpreted by means of spectral characteristics of an image, additional information sources are needed to reinforce the image data in order to identify whether the area mentioned is an area associated with human activities (Lillesand and Kiefer, 1994). The data is usually a thematic map or information regarding the type of use of a specific area or construction and often becomes more critical than the spectral data. Since the remotely sensed imagery is the primary data source for this study, surpass of an ancillary data is unacceptable. Other reason for excluding built-up land class is related to artificial human effect. Human factor when exceeded a trade-off between required development area and present suitable area, is often challenging. Land use associated with human activities can be practiced anywhere even unusual, regardless of the topographical restrictions, but dependent on other parameters instead. The reason why water bodies were excluded from the analysis is; clear water bodies with distinct and unambiguous spectral signatures are the most easily extracted information class within a multispectral image, hence there is no need to support classification of such water bodies with additional information. As a consequence, land cover classes remained are; (1) Agriculture, (2) Range Land and (3) Forest. At this point, rangelands in the study area were reevaluated, because; rangelands of the area obviously consist of two contextually different categories, which are herbaceous rangeland and shrub rangeland. A subdivision for rangeland category is made although it may violate Level I of generally acknowledged classification schemes (Anderson et al., 1976; CORINE, 1993). As a consequence of this subdivision; ultimate list of land cover ended up with four classes; e Agriculture e Rangeland-shrub (Range-shrub) e Rangeland-herbaceous (Range-herb) e Forest METHOD Image classification for this study aims to convert spectral data into four land cover classes. A conventional supervised classification algorithm; maximum likelihood is selected. Maximum likelihood classifier clusters pixels into information classes by means of training data based on probability distribution models for the cases of interest. (Favela and Torres, 1998). Maximum Likelihood classifier is the most commonly used supervised method and is supposed to provide better results compared to the other supervised methods (Foody et al., 1992; Maselli et al., 1995). This study attempts to integrate topographical information into conventional supervised classification through particular adjustment on the training data. A five-phased methodological Ini fr PREPROCKESSINC BASIC ANAL YVYSES ACCURACY

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