A Technical Approach of Image Segmentation in ENVI GIS to Identify Thematic Clusters for Visualization of Urban Transformations

Polina Lemenkova (1)

1 OUC - Ocean University of China

The technical study objective is to apply segmentation techniques for clustering image into thematic areas. The data used in this research included Landsat TM and ETM+ multi-band imagery covering chosen research area. The image processing was performed using supervised classification in GIS software. The technical aim of the research is image classification which consists in automatic assignation of all pixels on an image into land cover classes that are typical for this study area. The logical algorithmic approach of clustering segmentation was applied to identify clusters for thematic mapping of land cover types in the selected study area. While using data for spatial modelling and mapping, specific study objectives should always be evaluated, hence the model may have certain limitations and dependencies on the scale and resolution. the satellite scenes of Landsat TM with middle-sized resolution and open distribution have been taken for the research as available and appropriate images for current objective. The data pre-processing include image contrast stretching, which is useful as by default, ENVI displays images with a 2% linear contrast stretch. For better contrast the histogram equalization contrast stretch was applied to the image in order to enhance the visual quality. The number of clusters was assigned to 15, which responds to the selected land cover types in the study area. These cluster centers were then located within the study area. During clustering procedure, each digital pixel on the image is categorized to the respecting cluster, to which the mean DN value of the given pixel is the closest. Upon classification of all pixels in such a way, the revised mean vectors for each of the clusters were computed. The process has been repeated in an iterative way until optimal values of the class groups are received and pixels are assigned to the corresponding classes.

Mots clés: Mapping Modeling; GIS & Spatial Analyses; Image segmentation; Land cover mapping; Landsat Imagery; Landsat TM and ETM data; Satellite image interpretation; Image classification

Mots clés: SIG et modélisation spatiale; SIG Raster; SIG Systèmes d'information géographique

Domaines: Traitement des images [eess.IV]; Traitement du signal et de l'image [eess.SP]; Arithmétique des ordinateurs; Vision par ordinateur et reconnaissance de formes [cs.CV]; Calcul parallèle, distribué et partagé [cs.DC]; Interface homme-machine [cs.HC]; Synthèse d'image et réalité virtuelle [cs.GR]; Recherche d'information [cs.IR]

Polina Lemenkova. A Technical Approach of Image Segmentation in ENVI GIS to Identify Thematic Clusters for Visualization of Urban Transformations. Reality - the Sum of Information Technologies, South West State University (YuZGU), Dec 2015, Kursk, Russia. pp.100-104, ⟨10.6084/m9.figshare.7210346⟩. ⟨hal-01974739⟩