Proceedings, XXth congress: Proceedings, XXth congress

Altan, M. Orhan

Bibliographic data

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

ınbul 2004 [area are excluded. er bodies. preted by additional ze data in associated he data is e of use of ye critical sery is the ary data is id. class is 'xceeded a nt suitable th human rardless of parameters | from the ambiguous ation class to support mation. are: (1) this point, rangelands y different rangeland. igh it may n schemes nce of this ur classes; pectral data supervised | selected. information distribution res, 1998). nonly used tter results et al., 1992; mation into particular hodological International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B-YF. Istanbul 2004 framework was proposed for developing a procedure for the integration (Figure 1). GROUND TRUTH PRIMARY DATA ANCILLARY DATA RS Pancomatie LANDSAT bands Topographical parameters Land Es map — d Aerial Photo Field Observation geometric correction of minor data geometric correction of topographical map : I. i {oem of | ;| Digital Terrain Mode! (DTM) || i |derivation of| derivation o | i ASPECT SLOPE | | 1 geometric correction of band 1.2,3,4,5,7 1st Level Classification Classes: Agriculture, Forest, Range-shrub, Range-herb Classification method: Maximum Likelihood selection of class spectral signatures Ti spectral PREPROCESSING BASIC DEFINITIONS Pi No «a correlation Correlation w a correlation _ el] e DTM and SLOPE remained «| c En E selection of class 7. topographical signatures < Ti topographical » selection of T1 selection of T2 | CLASSIFICATION | CLASSIFICATION | us ! Input bands: Input bands: | 12,34,5,7, | a | DTM SLOPE | | | | - mea © Jy | zu Ol = zi test with SIG Ground truth data con à «x Figure 1: General Framework of the Study First phase: Procedures involved basically involves understanding class spectral characteristics. A certain time was devoted to understanding visual components of land cover classes in the study area making use of particular band combinations and other reference data. Training samples were selected for all classes overall the image, ensuring that they are good representatives of each information class. Selected training set was tested both for seperability and representativity, if not satisfied with the results; it was modified and tested again. This procedure continued since a balance between sample size and sample error was supplied. A Training Set Dendogram is used to obtain the results of a hierarchical analysis of the class signatures in graphic form (Figure 2). The spectral seperability of signatures were tested by "Transformed Divergence". Separability 9.00 9.50 0.99 1.43 1.98 []11 (36.63x) 2 2 (24,423) EN SET TES M 4 4 « 6.74%) Training Class Figure 2: Seperability of Initial Training set by means of Transverse Divergence measurement (1) Agriculture, (2) Range-shrub, (3) Range- herb, (4) Forest Class spectral signatures compose the initial training set for thc multispectral image data. However, this set is not used for training the classification procedure, rather it serves as prior information for the later redefinition of training data. Second phase: Quantification of the relationship between land cover classes and topographical parameters; elevation, slope and aspect is involved. Dependening on the significant relationships, ancillary topographical data that may contribute to improvement of classification accuracy is determined. Four land cover classes and the topographical parameters were tested for correlation. Land cover data involves training samples of land cover classes; agricultural land, range-shrub, range-herb., and forest. Those samples have been collected randomly from all over the study area and are spectrally good representatives of their associated classes, so, they formed an adequate test set. Topographical data merely involves the pixel values spatially corresponding to spectral training samples. Point Biserial Analysis is performed for quantifying the correlation between topographical parameters (interval scale) and land cover classes (dichotomous scale). The correlation coefficients obtained ranged between minimum of 0.02 to maximum positive of 0.65, and maximum negative of 0.41 (Table 1); where 0 denotes there is no correlation, 1 is perfect correlation and -1 is perfect negative correlation. Topographic Land cover Correllation Parameter class Coefficient Elevation agriculture 0.62 Slope agriculture 0.65 Aspect agriculture 0.02 Elevation range-shrub -0.34 Slope range-shrub 0.48 Aspect range-shrub -0.11 Elevation range-herb. -0.41 Slope range-herb. 0.08 Aspect range-herb. 0.06 Elevation forest 0.1 Slope forest -0.5 Aspect forest 0.24 Table 1: Point Biserial Correlation coefficients for four land cover classes and topographical data The result of the point biserial correlation analysis indicated the relation between specific land cover classes and the topographic parameters. The significance test verified that correlation coefficients greater than approximately 0.30 are significant. Significance level, often called the p value is the probability that a statistical result as extreme as the one observed would occur if the null hypothesis were true. As a consequence of the point biserial correlation analysis; aspect parameter with very low correlation coefficient was incidentally excluded from the remaining part of the study. Elevation and slope data were quantified for use as ancillary input for classification. Third phase: Ancillary topographical data; elevation and slope were examined for topographical signatures selection. A procedure similar to that performed in the first phase was carried on. However, this time the aim 1s to define the representative sets

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