ILMSimage Software Guide

Contents 1 ILMSImage for QuantumGIS 1.1 Introduction 1.2 Installation and Activation of ILMSimage 1.2.1 Installation 1.2.2 Activation of ILMSimage 1.3 ILMSImage Process Chain 1.3.1 ILMSImage Project Settings 1.3.2 ILMSImage Cell Creation 1.3.3 ILMSImage Feature Calculation 1.3.4 ILMSImage Classification 1.3.5 ILMSImage Example Application

ILMSImage for QuantumGIS

Introduction

ILMSimage for QuantumGIS software makes functions of the image analysis software ILMSImage available in the context of the user interface of QuantumGIS. ILMSImage for QuantumGIS provides a guided progress along the essential steps in the process chain. The chain starts with the selection of image data and ends with classified image areas. Stepping back in the chain is possible but each step needs its predecessor. Image data and intermediate results are gathered in projects with a common project name as filename. The work on each project can be interrupted at any state of the workflow and resumed later.

ILMSImage has been developed to process extensive amounts of image data of remote sensing in an effective and purposeful way and to be able to thematically analyze the data. The software relies on the concept of object-oriented image analysis, i.e. image elements (pixels) of a data set are not treated separately but in the context of neighboring elements which are spectrally similar. This concept manifests itself in the typical ILMSImage process chain which usually consists of three steps:

1. First, an analysis of separate pixels is carried out on the basis of spectral similarity and spatial proximity. This results in a summary of adjacent image elements to bigger groups with similar spectral characteristics. This process is often called segmentation in the context of object-oriented image analysis and cell creation in the context of ILMSImage.
2. In a second step, cell-based attributes or features are created. These features can be generated from the geometry of the grid cells or from their link to the original image data or additional data sources. All further processing is carried out on the basis of generated cells and the derived attributes. The original data are not taken into account in the remaining course of processing.
3. The third step comprises the actual thematic classification. ILMSImage is based on a two-step concept which links an unsupervised classification of cells and their attributes to an supervised classification according to reference data. According to the classification schema which has been provided by the user the designation of thematic areas within the study area is carried out.

Installation and Activation of ILMSimage

Installation

We recommend ILMSimage to be installed "out of the box" using the ILMS Installation Package. It is also possible to install ILMSimage manually, the necessary steps are described in detail at Individual Installation of ILMSimage.

Activation of ILMSimage

ILMSimage has to be activated after installation using the QuantumGIS plugin manager. For this purpose choose [ Plugins | Manage Plugins... ] from the QuantumGIS main menue bar.

The window of the appearing QuantumGIS Plugin Manager contains a set of plug-ins which are available and the source code of which - in case of their implementation in Python - is also already in the described directory. The entry called ILMSImage is the ILMSImage plug-in:

File:ILMSimage Plugin Activate.png

After the activation of the checkbox close the plugin manager with the [ OK ] button. The ILMSImage guide is now available under the menu item [ Plugins | ILMSimage ] for further use. By clicking on the menu item ILMSImage or the icon in the toolbar the ILMSimage guide appears. If the guide starts for the first time, the project section is empty. Under Select Image Data for Cell Creation the filenames of raster layers loaded to the QuantumGIS canvas are visible. To proceed, first of all a new project has to be created.

ILMSImage Process Chain

If the plug-in is activated as described above the ILMSimage guide is available by selecting the menue item ILMSimage in the [Plugins|ILMSimage] submenue or the corresponding symbol in the toolbar. Then the guide appears which makes all functions of ILMSimage available. In order to process a project the guide comprises eight sub-panels which can be grouped to four steps in the project chain:

ILMSImage Project Settings

ILMSImage Project Settings (panel Project) are used to create new projects and choose suitable input data layers or to resume working on an existing project. Interim results and temporary data are stored using the selected project name and project folder.

ILMSImage Cell Creation

ILMSImage Cell Creation 2.4 (panel Cells) combines areas with similar colored pixels to form cells, i.e. image regions with somewhat identical features. The resulting cell index can be influenced and controlled by the user by a couple of parameters.

ILMSImage Feature Calculation

ILMSImage Feature Calculation (panel Features) creates cell-based attributes or features and allows the integration of additional data layers for further feature generation. All classification work depends on cell shape and cell features.

ILMSImage Classification

ILMSimage classifies in two steps (ILMSImage Classification 2.4). The first step (panel Cluster) combines cells with broadly similiar image features by means of an unsupervised classification approach (clustering). The secons step introduces reference areas (panel Reference) and supervised classification (panel Classes) including spatial combinations of the previously generated clusters.

ILMSImage Example Application

To illustrate the application of the ILMSImage software an example application is prepared which examines the catchment area of the Rot in Thuringia. All necessary input data are available to download ILMSimage Example Application.