Spatial Engineering and Survey Techniques

Spatial Engineering and Survey Techniques

Spatial Engineering and Survey Techniques

Rajendra Asan

Spatial Engineering and Survey Techniques

Rajendra Asan

ISBN - 9789361521775

COPYRIGHT © 2025 by Educohack Press. All rights reserved.

This work is protected by copyright, and all rights are reserved by the Publisher. This includes, but is not limited to, the rights to translate, reprint, reproduce, broadcast, electronically store or retrieve, and adapt the work using any methodology, whether currently known or developed in the future.

The use of general descriptive names, registered names, trademarks, service marks, or similar designations in this publication does not imply that such terms are exempt from applicable protective laws and regulations or that they are available for unrestricted use.

The Publisher, authors, and editors have taken great care to ensure the accuracy and reliability of the information presented in this publication at the time of its release. However, no explicit or implied guarantees are provided regarding the accuracy, completeness, or suitability of the content for any particular purpose.

If you identify any errors or omissions, please notify us promptly at educohackpress@gmail.com & sales@educohackpress.com We deeply value your feedback and will take appropriate corrective actions.

The Publisher remains neutral concerning jurisdictional claims in published maps and institutional affiliations.

Published by Educohack Press, House No. 537, Delhi- 110042, INDIA

Email: educohackpress@gmail.com & sales@educohackpress.com

Cover design by Team EDUCOHACK

Preface

The book will bring together some of the theoretical and empirical perspectives about the application of Geotechnology in the field of urban planning and design. From an integrative viewpoint on Geosimulation, Geovisualization, and Geography information system, we give readers a valuable insight into the following subjects:

•Simulation of planning policy impacts on urban land use using cellular automaton (CA) and multi-agent system (MAS) process,

•Visualization of design guideline for improving coordinative design and gaining consensus using virtual reality (VR),

•Development of planning support tools using geography information system(GIS) and integration GIS with CA, MAS and VR.

Currently, the three concepts of Geosimulation, Geovisulization and Geography information systems are not integrated to build a complete platform of Geotechnology. For example, Google Earth is an integrated platform of virtual reality and geography information system. The integrated multi-user environment

based on agent-based simulation and virtual reality is also constructed by Secondlife Inc. In this book, we discuss these three concepts and their intended effects on planning support, respectively, which imply inspirational possibilities of Geotechnology integration in planning practice. Accordingly, this book will be edited as three parts, which are Geosimulation and land use plan, Geovisualization, and urban design, Geography information system and planning support.

Table of Contents

1 Geosimulation and Land Use Plan 1

1.1 Introduction 1

1.2 What is Form Scenario Analysis (FSA)? 3

1.2.1 Cellular Automata for Simulating

Urban Growth Boundaries(UGBs) 3

1.2.2 Form Scenario for Planned Urban Growth Boundaries 5

1.3 Simulated UGBs Using Conventional Constrained CA 7

1.4 The FSA Approach for Retrieving Policy

Parameters that Fit Planned UGBs 11

1.4.1 Policy Parameters and Constraints in Constrained CA 11

1.4.2 Policy Solutions for Planning

Alternatives Using FSA 13

1.5 Experiments in the Beijing Metropolitan Area 14

1.5.1 Study Area 14

1.6 Simulated and Planned UGBs 17

1.6.1 Parameter Calibration 17

1.7 Urban Growth Simulation for 2020 19

1.8 FSA Simulation and Policy Implications 21

1.9 Planning Alternatives – Planned UGB as FSA 22

1.10 Related Policy Implications 24

1.11 Conclusions and Next Steps 28

1.12 Exercise 30

2 GeoVisualization and Urban Design 31

2.1 Review of VR Application in Digital

Urban Planning and Managing 31

2.1.1 Development of VR Technology 31

2.1.2 The Initial Concept Development Period 31

2.1.3 The Major Equipment Development Period 32

2.1.4 The System Research Development Period 33

2.1.5 The High-tech Research Development Period 34

2.2 Classes of VR Modeling Method 36

2.2.1 Visualization Modeling Method 36

2.2.2 Attribute Modeling Method 37

2.2.3 Integration Modeling Method 38

2.3 Characteristics of VR Application in

Urban Planning and Managing 39

2.3.1 Characteristics of VR Application

in the West 39

2.3.2 Characteristics of VR Application in China 40

2.4 Aspects of VR Application in Urban Planning

and Managing 41

2.4.1 VR Aided Compiling Urban Planning Scheme 42

2.5 VR Aided Representing Urban Planning Scheme 44

2.6 VR Aided Managing Urban Development Process 46

2.6.1 The perspective of VR Application in Urban Planning and Managing 48

2.7 Current Traditional Urban Planning and

Managing Needs VR to Aid 49

2.8 Future Digital Urban Planning and

Managing Needs VR to Support 50

2.9 Conclusion 51

2.10 Exercise 52

3 Automatic Generation of Virtual 3D City

Models for Urban Planning 54

3.1 Introduction 54

3.2 Literature Review 56

3.3 Research Objective 59

3.4 The approach of the Automatic Generation

for Urban Design Alternatives 60

3.5 Virtual 3D City Model Generation 62

3.5.1 Generation of 3D Building Models

for Pitched Roof Building 62

3.6 Summary of Our Work 69

3.7 Exercise 70

4 Error Types 74

4.1 Probability Distribution 74

4.2 Most Probable Value 75

4.3 Standard Deviation 75

4.4 Variance 76

4.5 Standard Error Of Mean 76

4.6 Most Probable Error 77

4.7 Confidence Limits 77

4.8 Weight 78

4.9 Precision And Accuracy 79

4.10 Propagation Of Error 79

4.10.1 Normal Distribution 80

4.11 Exercise 85

5 Distance Measurement 87

5.1 Direct Method Using A Tape 87

5.2 Correction for Absolute Length 87

5.3 Correction for Temperature 88

5.3.1 Correction for Pull or Tension 88

5.4 Correction for Sag 89

5.5 Correction for Slope 90

5.6 Correction for Alignment 91

5.7 Reduction to Mean Sea Level (M.S.L.) 92

5.8 Error In Pull Correction Due To Error In Pull 93

5.9 Error In Sag Correction Due To Error In Pull 94

5.9.1 Elongation Of A Steel Tape When Used

For Measurements In A Vertical Shaft 94

5.9.2 Tacheometric Or Optical Method 98

5.9.3 Subtense Tacheometry 99

5.9.4 Effect Of Staff Verticality 100

5.10 Exercise 102

6 Adjustment of Survey Observations 104

6.1 Adjustment Of Observations 104

6.2 Method Of Least Squares 104

6.3 Observation Equations And Condition Equations 105

6.4 Normal Equation 106

6.5 Least Squares Method Of Correlates 107

6.6 Method Of Differences 108

6.7 Method Of Variation Of Coordinates 108

6.8 General Method Of Adjusting A Polygon

With A Central Station 110

6.9 Exercise 187

Appendix 190

Glossary 192

Index 202

Chapter - 1 Geosimulation and Land Use Plan

1.1 Introduction

In planning practice, planners and policymakers frequently investigate urban forms, particularly urban growth boundaries (UGBs), using scenario analyses(SA) by regarding development policies as scenario conditions in urban simulations(i.e., Klosterman 1999; Landis 1994, 1995). Couclelis (2005), however, argued that routine land-use modeling had done little in the way of future-oriented research such as investigations of desirable or feared future conditions. This chapter uses planning alternatives, specifically UGBs, as scenarios to identify necessary spatial policies for planners. This is the inverse procedure of traditional urban growth SA.

We propose the concept of form scenario analysis (FSA), which we employ to investigate relationships between planning alternatives and corresponding spatial policies. This chapter explains an FSA approach using constrained cellular automata (CA), a tool for matching planning alternatives with necessary spatial policies. We look in particular at form scenarios in order to present the institutional implications of different spatial land-use policy options. This novel exploration of FSA can identify necessary policies as well as policy variations required for different planning alternatives. This differs from traditional applications of constrained CA.

Unlike in the West, Chinese urban planners, mostly working in government-held planning institutions, hold intrinsic notions from the planned economic system when devising alternatives, resulting in development potential factors not well be taken into account. Planners are accustomed to designing urban structures in master plans without sufficient deliberation on spatial policies that are required

to realize the desired urban form. UGBs produced by planners cannot completely conform to the land-use development plan issued by the national land resource bureau, which is dynamically influenced by social, economic, political, technological, and environmental policies such as eco-sensitive land protection, infrastructure development, and other market economy factors.

In planning practice, practical urban growth tends to depart from planned UGBs. An investigation has shown that more than 35% of urban development occurring in Beijing exceeds the urban spaces defined in the original plan (Han et al. 2009). Appropriate policy guidance by planning authorities is necessary to make planned alternatives become a reality in the process of urban development. From this point of view, the government is commonly concerned with spatial policies on spatial constraints that are consistent with planned UGBs. Therefore, FSA has significant practical promise as an approach to extract appropriate spatial policies from planning alternatives.

This chapter is organized as follows. In Sect. What Is Form Scenario Analysis(FSA)?, conventional urban growth simulation and FSA are further introduced. In Sect. Simulated UGBs Using Conventional Constrained CA, we employ conventional methods to simulate urban growth boundaries. In Sect. The FSA Approach for Retrieving Policy Parameters that Fit Planned UGBs, we elaborate in detail on our new FSA approach using constrained CA. Section Experiments in the Beijing Metropolitan Area describes a case study in which we apply the FSA

approach to four planning alternatives in the latest urban master plan for the Beijing Metropolitan Area. We also describe our research materials, including the study area, spatial constraints, and planning alternatives. The form scenario analysis results are listed in Sect. Conclusions and Next Steps. Finally, we give some discussion, a summary, and a description of the next steps of the FSA research.

1.2 What is Form Scenario Analysis (FSA)?

1.2.1 Cellular Automata for Simulating Urban Growth Boundaries(UGBs)

Recently, the process of simulating future urban forms using constrained cellular automata (CA) has attracted extensive attention. The results of such simulations, when viewed as alternative future urban forms based on specific assumptions of spatial constraints and policy environment, can be used as a basis for establishing UGBs.

Urban sprawl arising from rapid development is a great challenge in sustainable urban development. It is crucial to design appropriate methods for effective control of urban growth. Among various urban growth management policies, urban containment has been widely adopted to increase urban land-use density and protect open space. Urban containment policies usually have three components: greenbelts, UGBs, and urban service boundaries (USBs). Through zoning, land development permits and other land-use regulations and methods, UGBs demarcate urban and rural land uses and aim to contain urban development within defined boundaries.

In China, concepts resembling UGBs have just started to develop. These ideas are a precondition for land-use planning. The Urban Planning Compilation Guideline, issued by China’s State Ministry of Construction on April 1, 2006, requires that city master plans propose development exclusion areas, development control areas, and suitable development areas. Consequently, development exclusion areas and

development control areas have become important references for identifying the boundaries of urban construction and have played a dominant role in controlling urban growth. In response to this guideline, Long et al. (2006) suggested a zoning method for the three types of areas and established development exclusion and

control areas in the Beijing Metropolitan Area (BMA). Also, planned UGBs for urban growth management have become indispensable because of the People’s Republic of China Town and Country Planning Act introduced on January 1, 2008, gave planned UGBs the legal authority to curb urban growth. The urban planning administrative department issues building permits based on the UGBs. Developments within the planned UGBs are legal, whereas those outside are illegal. Therefore, how planners determine the urban growth boundaries is important.

The establishment of UGBs involves comprehensive consideration of various factors related to urban spatial development. In Chinese cities, traditional methods of establishing UGBs, mostly based on planners’ experience, often lack adequate scientific basis backed by quantitative analysis and often fail to control and regulate urban growth adequately. Han et al. (2009) examined the effectiveness of the planned UGBs using multi-temporal remote sensing images and found that more new urban construction lay outside the UGBs than inside them in the case of the area within the sixth ring of Beijing from 1983 to 1993 and from 1993 to 2005. Moreover,

Tian et al. (2008) and Xu et al. (2009) evaluated plan implementation in Guangzhou and Shanghai, respectively. Their results showed that a large number of urban developments were located outside UGBs specified in the urban master plan.

Cellular automata techniques can simulate UGBs and therefore have been widely used in modeling urban growth and as an analytical tool for complex spatiotemporal systems. Because of the complexity of urban growth, simulations of urban growth need to consider various factors that impact the urban growth process. Simple CA models only consider neighborhood effects,