**1. Introduction**

Rapid population growth and urbanization have caused many problems in the implementation of developmental projects in cities. Haphazard infrastructural project execution that includes disregard in prioritizing city (or cities) selection is also a factor hampering sustainable development practices. Development projects that rely on selected organizations, which in turn rely on human judgment, can lead to unrealistic criteria evaluation, causing delays in project execution [1]. However, the fact remains that continued infrastructure development is unavoidable, especially since urban cities constantly need to evolve and grow to keep up with the times [2].

The selection of a city (or a group of cities) is one of the most important steps for sustainable development. The selection criteria must ensure that the city (cities) has high priority for development and is (are) in line with the needs of the local citizens. Moreover, timely selection requires effective planning and analysis and must consider multiple conflicting and disproportionate factors (such as those that have critical socioeconomic and environmental implications to different stakeholders). Urban planning application using remote sensing (RS) and geographical information systems (GIS) is one of the many areas that can be explored for city selection. Such applications would not only eliminate human bias but would also be able to make more objective decisions based on data.

the analytical process [6]. In the context of GIS, this refers to the spatial decisionmaking process based on GIS data with geolocation tags. Spatial decision-making techniques have been used to solve many GIS problems such as locating solar plants, urban planning, and project construction optimization [7]. Advanced MCDM methods include simple additive weighting (SAW) [8], analytic hierarchy process (AHP) [9], and TOPSIS [10]. Fuzzy set theory and random set theory are also MCDM techniques that incorporate sophisticated algorithms to resolve uncertainty

*Urban Planning Using a Geospatial Approach: A Case Study of Libya*

*DOI: http://dx.doi.org/10.5772/intechopen.86355*

TOPSIS is a MCDM technique that deals with real-world problems. It basically ranks criteria on the basis of the shortest distance from the positive ideal solution (PIS) and the farthest distance from the negative ideal solution (NIS) [15]. The work in [2] illustrates the application of a GIS-based MCDM tool for urban infrastructural planning. Awasthi et al. [16] presented a fuzzy TOPSIS method for selecting the best location for an urban distribution center in Canada. Uysal and Tosun [17] proposed a fuzzy TOPSIS-based maintenance management system using 17 criteria categorized under 5 contending parameters. The criteria were deduced from questionnaire feedbacks and interviews administered to company maintenance managers. In addition, Momeni et al. [18] presented a fuzzy TOPSIS-based method for maintenance strategy selection. Baysal et al. [19] developed a two-stage fuzzy method to determine the best sub-municipal projects among a set of proposed projects. The method simplifies the selection process and provides an objective decision outcome for stakeholders. Shelton and Medina [20] presented an integrated method to prioritize transportation projects in Wilmington Area, USA, based on multi-criteria decision support systems, AHP and TOPSIS methods. The process optimally selects the important routes that best serve the interest of the general

Based on the literature, TOPSIS has been successfully applied in many fields, producing reasonably accurate results. This study proposes an automated TOPSISbased solution for prioritizing urban projects based on criteria that meet sustainable development. Specifically, this work addresses the following questions on the value

1. Which remotely sensed dataset(s) is (are) useful for urban planning?

3.What are the major factors that need to be considered in urban developments?

From these questions, this study further looks at the automated prioritization of urban projects based on criteria that meet sustainable development practices. The specific objectives are (i) to identify factors that play major roles in urban development and (ii) to develop a geospatial solution based on TOPSIS for prioritizing

This study focuses on Libya, a country in the Maghreb region of North Africa (**Figure 1**). Libya borders the Mediterranean Sea to the north and Egypt to the east. Along the southeast of Libya is Sudan, Chad. To the south is Niger. Algeria and Tunisia constitute the western border. Libya is the 17th largest nation in the world with a

six districts, namely, Darnah, Al Jabal Al Akhdar, Benghazi, Al Marj, Al Qubbah, and

. The study area in the northern part of Libya covers

2.Which criteria can be derived from remotely sensed data?

**2. Study area and preparation of the conditioning factors**

of remote sensing (and GIS) to urban planning:

projects for urban development.

landmass of over 1,759,540 km2

**241**

in data [11–14].

public.
