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Geographic Information Systems (GIS) are computer-based systems used to store and manipulate geographical data, and perform spatial analysis. These systems serve to reveal the patterns, relationships, and anomalies, or sometimes invisible characteristics of the geographical data in various applications. While the term "GIS" indicates an object or tool, GIScience, the acronym for Geographic Information Science, covers a broader context of methodologies behind spatial data analysis. Among different application areas of GIS, "environmental monitoring and modeling" plays a significant role in the development of the very first GIS in the world-The Canada Geographic Information Systems (CGIS) in the mid-1960s. After almost 40 years of history, significant changes and challenges took place in the geographic information research agenda. This chapter will point out some of the vital tools and methods used in GIScience (including GIS, remote sensing and 3D modeling) to grasp issues of our urban environments. With recent technological advances that facilitate our understanding of the environment; it is more evident that the vision of more "livable" cities is not too far but not easy as well.

The empirical evidence from literature has disclosed that the extensive share of world’s population continues to live in informal settlements due to extensive economic, social, and welfare disparities. These informal settlements possess the attributes of poor infrastructure and utilities services. In reality, due to excessive housing prices, economic incapacity, and insufficient technical abilities among poor people, they are forced to live in such dilapidated settlements. However, over the times, governmental institutes have adopted several distinct strategies to enhance the quality of life (QOL) of inhabitants living in informal settlement. Therefore, this research study intends to examine the contemporary living conditions in informal settlement using multi-indicator analysis. To assess the QOL, five leading indicators including building density, utilities services, road infrastructure, urban furniture, and social services and their associated 29 sub-indicators was identified and Bao wala as informal settlement in Lahore, Pakistan has been selected as case study area. A semi structured questionnaire was formed and sample size of 99 was calculated to perform socio-economic surveys. In the surveys, proportionate and random sampling technique was used to gain diverse outcomes. In the data analysis, descriptive analysis technique was used to examine the public perceptions regarding contemporary utilities services and regression analysis techniques was used to explore the relation between perceived and dependent variables. The results outcomes have shown that majority of the population of Bao wala settlement express extreme dissatisfaction regarding all the perceived indicators based on the provision, maintenance, and operation quality; however, the regression analysis indicates that all the five leading indicators have strong and significant relation with the dependent variable.

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