ESP: a tool to estimate scale parameter for multiresolution image segmentation of remotely sensed data

Abstract

The spatial resolution of imaging sensors has increased dramatically in recent years, and so too have the challenges associated with extracting meaningful information from their data products. Object-based image analysis (OBIA) is gaining rapid popularity in remote sensing science as a means of bridging very high spatial resolution (VHSR) imagery and GIS. Multiscalar image segmentation is a fundamental step in OBIA, yet there is currently no tool available to objectively guide the selection of appropriate scales for segmentation. We present a technique for estimating the scale parameter in image segmentation of remotely sensed data with Definiens Developer®. The degree of heterogeneity within an image-object is controlled by a subjective measure called the ‘scale parameter’, as implemented in the mentioned software. We propose a tool, called estimation of scale parameter (ESP), that builds on the idea of local variance (LV) of object heterogeneity within a scene. The ESP tool iteratively generates image-objects at multiple scale levels in a bottom-up approach and calculates the LV for each scale. Variation in heterogeneity is explored by evaluating LV plotted against the corresponding scale. The thresholds in rates of change of LV (ROC-LV) indicate the scale levels at which the image can be segmented in the most appropriate manner, relative to the data properties at the scene level. Our tests on different types of imagery indicated fast processing times and accurate results. The simple yet robust ESP tool enables fast and objective parametrization when performing image segmentation and holds great potential for OBIA applications.

Keywords:

• local variance
• OBIA
• tessellation
• characteristic scales
• Definiens

Acknowledgements

The work of Lucian Dragut is supported by the Austrian Science Fund through a Stand-alone project (“SCALA”, FWF-P20777-N15) and by a Marie Curie European Reintegration Grant within the 7th EC Framework Programme (Grant agreement No. 239312). The work of Shaun R. Levick is funded by the Andrew W. Mellon foundation. Clemens Eisank has contributed to test the temporary settlement area. Data for the mixed residential/forest test area has been provided by the regional government of Salzburg (SAGIS, Land Salzburg). Data for the temporary settlement area has been exchanged within the frame of the EU-funded project LIMES (Land and Sea Integrated Monitoring for European Security, EC Sixth Framework Programme, Contract No. SIP-CT-2006-031046).