PROPOSAL

Comparison pixel-based and object oriented classification for Informal settlements using SPOT-5 imagery

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Abstract

In this study we try to explore the concept of Comparison pixel-based and object oriented classification for Informal settlements using SPOT-5 imagery. The main focus of the research is on remote sensing techniques and its relation with the urban features. The research also analyzes many aspects of the identified topic and intends to explore the informal settlements in Abu Arish city. Finally the research describes various factors which are responsible for the procedures which tend to enable the transfer of knowledge. Moreover, this study also focuses on the rise of informal settlements in many regions of the Kingdom of Saudi Arabia. For example, we find a high density of informal settlements areas in the province of Jeddah and in the holy city of Mecca. The informal settlements in the western and central regions of Saudi Arabia are already undergoing amelioration through appropriate plans to resolve the problem. This study tends to take into fold the tools such as documentation, Quality assessment, classification and pre-processing to under the different classification techniques and underlying notions. During the course of the study Two SPOT-5 images will be used in order to understand the nomenclature of the identified topic. It would be safe to state the fact this study tends to provide a clear picture regarding the limitations of the pixel based and object oriented method to meet the pretext of the paper.

Table of Contents

ABSTRACTii

CHAPTER 1: INTRODUCTION1

Aims and Objectives2

Study Area3

Methodology4

Pre-processing4

Classification5

Pixel-based classification5

Object-oriented Classification5

Material6

CHAPTER 2: LITERATURE REVIEW7

“Object-Oriented” Classification Techniques7

Image Segmentation Phase8

“Object-Oriented” Classification Phase9

Multi Resolution Segmentation Technique10

Informal settlements areas and remote sensing11

CHAPTER 3: CLASSIFICATION15

Pixel-based Classification15

Advantages of Unsupervised Classification16

Disadvantages of Unsupervised Classification16

CONCLUSION22

REFERENCES26

CHAPTER 1: INTRODUCTION

In 2003, almost one billion people, or 32% of the world's population, lived in informal settlements in the developing countries (UN-HABITAT 2003). More recently, more than half of the population of the earth has been identified as living in informal residences in urban areas. These informal residential buildings were the result of many causes, for example some cities lack urban planning and are facing rapid growth in population. The 2003 United Nations Human Settlements Programme (UN-HABITAT 2003) report pointed out that 90% of future population growth would be in cities and most of this growth would exist in the developing countries. In fact, unplanned rapid growth threatens both society and the environment in these cities. One problem is the absence of infrastructure in the cities, especially in informal settlements, resulting in unhealthy living conditions (Andrea & Eva, 2005).

Remote sensing techniques are gaining ground as satellite imagery becomes the most important data source for urban change study, as well as providing information on land cover for subsequent classification or analysis. Remote sensing techniques now provide information of high resolution which is regularly updated. Large collections of remote sensing imagery have provided a solid foundation for spatial-temporal analysis of the environment and the impact of human activities (Zhou et al., 2004). These data provide a 'freeze-frame' view of the spatial-temporal patterns associated with urban change, ...