**5. Conclusion**

in each group. Demography and vegetation are the two most influential factors with positive contribution, followed by vegetation and topography. The other factors

Recall that the refined suitability map was recategorized into the three classes of "not suitable," "less suitable," and "highly suitable," These classes reflect the degree of urban development suitability in the study area. The categorized suitability map can be validated accurately through each class. The continuous refined is suitability map ranging from 0 to 1. The most suitable areas that range from 0.751 to 1 fall into high suitable class, while the moderate suitable areas for urban development were extracted from 0.401 to 0.751 from the continuous refined suitability map.

**Class ROC area PRC area** Not suitable 0.934 0.884 Less suitable 0.799 0.60 High suitable 0.852 0.673 Average 0.861 0.719

**Accuracy metric Value** Correctly classified instances 1178 (78.5%) Incorrectly classified instances 322 (21.4%) Kappa statistic 0.67

have negative contribution.

*Sustainability in Urban Planning and Design*

**4.2 Accuracy assessment**

*Overall accuracy assessment of SVM modeling.*

*Accuracy assessment of SVM modeling based on ROC.*

**Table 5.**

**Table 6.**

**Figure 8.** *AUC for the SVM.*

**254**

An automated geospatial solution for selecting and ranking cities in Libya for urban development is proposed in this chapter. The suitability map showed that most areas indicated to be suitable are in the northern part of Libya. The results indicate that land use, distance to primary route, distance to large city, rainfall, NPP, and NO2 have negative effects on the level of suitability for the selection process, whereas the other factors have positive effects with population density taking the lead. It is revealed that SVM model accurately classifies 1178 samples, about 78.5% of the total samples tested which produced kappa statistic of 0.67. The high-priority city was selected as Benghazi that is followed by Al Jabal Al Akhdar. The results suggest that demography and vegetation are the two most influential factors contributing to the selection of city for development in Libya. This study is limited to analysis of six cities; the procedure developed through this study can be extended to other cities. It is of the opinion that evaluated criteria can be adjusted according to the environment and the current development of the cities.


**C1**

TOPSIS 2

**257**

44.40

44.28

N=

 0.00 44.66

44.77

44.49

Normal

TOPSIS 3

**C1**

0.445

0.444

0 0.448

0.449

0.446

 0.42

 0.241

 0.470

 0.485

 0.629

 0.537

 0.434

 0.348

0.45

 0

 0

 0.442

 0.31

 0.535

 0.57

 0.069

 0.207

 0.374

 0.393

 0.563

 0.698

 0.352

0.57

 0.22

 0

 0

 0

 0.322

 0.4

 0.297

 0.518

 0.332

 0.576

 0.278

 0.496

 0.473

0.33

 0.38

 0

 0.392

 0.39

 0.196

0.21

 0.838

 0.143

 0.300

 0.017

 0.562

 0

0

0.11

 0.07

 1

 0.589

 0.69

 0.700

 0.41

 0.328

 0.540

 0.343

 0.302

 0.05

 0.278

 0.526

0.37

 0.55

 0

 0.372

 0.46

 0

 0.36

 0.192

 0.393

 0.552

 0.154

 0

0

 0.505

0.47

 0.71

 0

 0.403

 0.25

 0.282

 **C2**

 **C3**

 **C4**

 **C5**

 **C6**

 **C7**

 **C8**

 **C9**

 **C10**

 **C11**

 **C12**

 **C13**

 **C14**

 **C15**

 99.55

 10.3

 681594.73

 363626.55

 1232.02

 2302576.25

 0.88

 796219.68

 60.05

 0.90

 4.25

 170

 746988.97

 6.28

 408.49

 4.31

 164855.00

 170954.00

 598.51

 1449880.00

 0.48

 346141.00

 20.87

0.41

 0.00

 0.00

 330901.00

 1.93

 218.72

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

 5.83

 47112.30

 75610.90

 461.25

 906233.00

 0.50

 555787.00

 21.11

0.52

 0.95

 0.00

 0.00

 0.00

 131.93

 4.12

 202732.00

 188407.00

 409.90

 1328530.00

 0.25

 395212.00

 28.42

0.30

 1.60

 0.00

 293142.00

 2.43

 80.38

 2.18

 571466.00

 52346.60

 370.37

 41068.40

 0.50

 27.63

 0.00

0.10

 0.28

 170.00

 440481.04

 4.33

 286.06

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

 4.20

 224171.00

 196505.00

 422.65

 696167.00

 0.04

 221496.00

 31.56

0.34

 2.35

 0.00

 278509.00

 2.92

 0.00

 3.68

 131333.00

 142935.00

 680.50

 356539.00

 0.00

 0.00

 30.35

0.42

 3.00

 0.00

 301619.00

 1.60

 115.49

 **C2**

 **C3**

**C4**

 **C5**

 **C6**

 **C7**

 **C8**

 **C9**

 **C10**

 **C11**

 **C12**

 **C13**

 **C14**

 **C15**

**A. Appendix**

TOPSIS 1


0

#### *Urban Planning Using a Geospatial Approach: A Case Study of Libya DOI: http://dx.doi.org/10.5772/intechopen.86355*

TOPSIS 2

**City**

**A.** 

**256**

**Appendix**

TOPSIS 1 **Percent**

**NPP Population**

 **Primary**

**Rainfall**

 **Secondary**

**Slope**

 **Trail**

**NO NDVI LST**

 **land**

**Distance to**

**CO Altitude**

*Sustainability in Urban Planning and Design*

**cover**

**Benghazi**

**route**

**route**

**route**

**urban**

**C1**

Darnah Al Jabal Al

Akhdar

Benghazi

Al Marj Al Qubbah Al Hizam Al

Akhdar

Criteria sign

11

 1

 1

 1

 1

1

 1

1

 1

1

1

1

1

1

range

W(Lambda)

Ideal The worst

0.00

44.77

 2.18 47112.30

 52346.60

 370.37

 41068.40

 0.86

 0.00

 148.66

0.52 17.47 200.00

 5.83 571466.00

 196505.00

 680.50

 1449880.00

 0.36 555787.00

 117.11

0.10 14.46

 30.00

 541.96

 441023.00

 82.69 341.61

 78.36

 55.55

0.36

 0.98

 2.15

 0.60

 0.96

2.35

 0.74

 0.27

0.62

 4.88

1.17

 0.23

0.10

 1.23

1.18

44.77

0.11

0.00

0.28

 4.31 164855.00

 170954.00

 598.51

 1449880.00

 0.39 346141.00

 127.79

0.41 17.47

 200

 110122.00

 80.76 122.89

 5.83 47112.30

 75610.90

 461.25

 906233.00

 0.36 555787.00

 127.56

0.52 16.51

 200

 441023.00

 82.69 209.68

 4.12 202732.00

 188407.00

 409.90

 1328530.00

 0.62 395212.00

 120.24

0.30 15.86

 200

 147881.00

 80.26 261.23

 2.18 571466.00

 52346.60

 370.37

 41068.40

 0.36

 27.63

 148.66

0.10 17.19

 30

 541.96

 78.36

 55.55

0.37

0.49

 4.20 224171.00

 196505.00

 422.65

 696167.00

 0.82 221496.00

 117.11

0.34 15.11

 200

 162514.00

 79.77 341.61

 3.68 131333.00

 142935.00

 680.50

 356539.00

 0.86

 0.00

 118.32

0.42 14.46

 200

 139404.00

 81.09 226.11

 **C2**

 **C3**

 **C4**

 **C5**

 **C6**

 **C7**

 **C8**

 **C9**

 **C10 C11**

 **C12**

**C13**

 **C14**

 **C15**



**Author details**

Bahareh Kalantar<sup>1</sup>

Shattri Mansor<sup>3</sup>

**259**

Maruwan S.A.B. Amazeeq<sup>3</sup>

Malaysia, Serdang, Selangor, Malaysia

provided the original work is properly cited.

\*, Husam A.H. Al-najjar<sup>2</sup>

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

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

Research Group, Disaster Resilience Science Team, Tokyo, Japan

, Mohammed Oludare Idrees<sup>3</sup>

2 Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, NSW, Australia

1 RIKEN Center for Advanced Intelligence Project, Goal-Oriented Technology

3 Department of Civil Engineering, Faculty of Engineering, Universiti Putra

4 Department of Multimedia, Faculty of Computer Science and Information

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

Technology, Universiti Putra Malaysia, Serdang, Selangor, Malaysia

\*Address all correspondence to: bahareh.kalantar@riken.jp

, Hossein Mojaddadi Rizeei<sup>2</sup>

,

, Alfian Abdul Halin<sup>4</sup> and

#### *Sustainability in Urban Planning and Design*

TOPSIS 4 *Urban Planning Using a Geospatial Approach: A Case Study of Libya DOI: http://dx.doi.org/10.5772/intechopen.86355*
