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E-grāmata: GIS and Archaeological Site Location Modeling

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  • Formāts: 496 pages
  • Izdošanas datums: 21-Dec-2005
  • Izdevniecība: CRC Press
  • Valoda: eng
  • ISBN-13: 9781134375936
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GIS and Archaeological Site Location ModelingPalielināt
  • Formāts: 496 pages
  • Izdošanas datums: 21-Dec-2005
  • Izdevniecība: CRC Press
  • Valoda: eng
  • ISBN-13: 9781134375936
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Although archaeologists are using GIS technology at an accelerating rate, publication of their work has not kept pace. A state-of-the-art exploration the subject, GIS and Archaeological Site Location Modeling pulls together discussions of theory and methodology, scale, data, quantitative methods, and cultural resource management and uses location models and case studies to illustrate these concepts. This book, written by a distinguished group of international authors, reassesses the practice of predictive modeling as it now exists and examines how it has become useful in new ways.

A guide to spatial procedures used in archaeology, the book provides a comprehensive treatment of predictive modeling. It draws together theoretical models and case studies and explains how modeling may be applied to future projects. The book illustrates the various aspects of academic and practical applications of predictive modeling. It also discusses the need to assess the reliability of the results and the implications of reliability assessment on the further development of predictive models.

Of the books available on GIS, some touch on archaeological applications but few cover the topic in such depth. Both up to date and containing case studies from a wide range of geographical locations including Europe, the USA, and Australia, this book sets a baseline for future developments.
Section 1: Introduction
1 There and Back Again: Revisiting Archaeological Locational Modeling
3(38)
Kenneth L. Kvamme
1.1 Introduction
4(1)
1.2 Not So in Bongo-Bongo: Cultural Variation and Modeling
5(3)
1.3 The First Age of Modeling: A Personal Narrative
8(4)
1.4 Perspectives on "Correlative" and "Deductive" Models
12(1)
1.5 Theoretical Justification of Archaeological Location Modeling
13(4)
1.5.1 Background Concepts
13(1)
1.5.2 A Deductive Model
14(3)
1.5.3 Summary
17(1)
1.6 The Second Age of Modeling: Continuing Issues
17(4)
1.6.1 Archaeological Site Types
17(2)
1.6.2 The Paleoenvironment
19(1)
1.6.3 Sampling
20(1)
1.7 The Second Age of Modeling: Possible Improvements
21(11)
1.7.1 Independent Variables
21(1)
1.7.1.1 The Natural Environment
21(1)
1.7.1.2 The Social Environment
22(1)
1.7.2 Other Modeling Algorithms
23(1)
1.7.3 Forget Those Nonsites: Single-Class Approaches
24(1)
1.7.4 Models of Greater Specificity
25(1)
1.7.5 Measures of Model Performance
26(3)
1.7.6 Significance Tests
29(1)
1.7.7 Confidence Intervals
30(1)
1.7.8 p(S) Is Not Constant
30(1)
1.7.9 Issues of Scale: Near and Far Perspectives
31(1)
1.8 Conclusions: Direct Discovery Methods
32(1)
Acknowledgments
33(1)
Notes
34(1)
References
34(7)
Section 2: Theoretical and Methodological Issues
2 Enhancing Predictive Archaeological Modeling: Integrating Location, Landscape, and Culture
41(22)
Gary Lock and Trevor Harris
2.1 Introduction
41(1)
2.2 Identifying the Tensions: Predictive Modeling and Landscape Archaeologies
42(3)
2.3 The West Virginia Predictive Model
45(4)
2.4 Another West Virginia Predictive Model
49(2)
2.5 Humanizing the Landscape
51(2)
2.6 Moving from Data Points to Cultural Entities
53(2)
2.7 Increasing the Envirocultural Complexity
55(4)
2.8 Conclusion: The Challenge
59(1)
References
59(4)
3 One Step Beyond: Adaptive Sampling and Analysis Techniques to Increase the Value of Predictive Models
63(12)
Konnie L. Wescott
Preface
64(1)
3.1 Introduction: Current Use and Value of Predictive Models
64(2)
3.2 Testing and Improving Predictive Models
66(1)
3.3 Quantifying Uncertainty and Bayesian Statistics
67(1)
3.4 Adaptive Sampling and Analysis Programs
68(1)
3.5 ASAPS Approach to Archaeological Predictive Modeling
69(2)
3.6 Conclusions
71(1)
References
72(3)
Section 3: Issues of Scale
4 Modeling for Management in a Compliance World
75(22)
Christopher D. Dore and LuAnn Wandsnider
4.1 Introduction
76(2)
4.2 Predictive Modeling and Compliance
78(5)
4.2.1 Model Building
78(2)
4.2.2 Model Testing
80(2)
4.2.3 Theoretical Issues
82(1)
4.2.4 Summary
83(1)
4.3 Managing with Geospatial Technologies
83(9)
4.3.1 Regional Scale
84(1)
4.3.2 Site Scale
85(2)
4.3.3 Feature Scale
87(5)
4.4 Summary
92(1)
Notes
93(1)
References
94(3)
5 Problems in Paleolithic Land Evaluation: A Cautionary Tale
97(26)
Hans Kamermans
5.1 Introduction
98(1)
5.2 Land Evaluation
99(2)
5.3 The Agro Pontino Survey Project
101(1)
5.4 Land Evaluation and Archaeology
102(12)
5.4.1 Step 1: Basic Surveys
102(3)
5.4.2 Step 2: Models
105(1)
5.4.3 Step 3: Qualitative Classification
106(1)
5.4.4 Step 4: Quantitative Classification
106(3)
5.4.5 Step 5: Land Use
109(5)
5.5 Inductive Predictive Modeling
114(1)
5.6 Discussion
115(2)
5.7 Conclusions
117(1)
Acknowledgments
118(1)
References
118(5)
6 Regional Dynamics of Hunting and Gathering: An Australian Case Study Using Archaeological Predictive Modeling
123(24)
Malcolm Ridges
6.1 Introduction
123(2)
6.2 Background
125(3)
6.3 Approach
128(3)
6.4 Results
131(6)
6.5 Discussion
137(2)
6.6 Conclusions
139(1)
Notes
140(1)
References
140(7)
Section 4: Quantitative and Methodological Issues
7 Making Use of Distances: Estimating Parameters of Spatial Processes
147(20)
Christian Mayer
7.1 Introduction
148(1)
7.2. A General Model: Spatial Process
148(5)
7.2.1 Some Definitions
149(1)
7.2.2 Characterizing a Point Process
150(1)
7.2.3 Edge Correction
150(1)
7.2.4 Trend Removal
151(1)
7.2.5 K-Functions, L-Functions, Thompson Statistics
151(1)
7.2.6 Properties of a Pattern, Local Intensity Function
152(1)
7.2.7 Validation of the Model
152(1)
7.3 A Model for an Archaeological Landscape
153(2)
7.4. A Case Study: Medieval Settlement Structure
155(10)
7.4.1 The Model
155(1)
7.4.2 Basic Assumptions, Causative Elements, Direction of Analysis
155(1)
7.4.3 Data
156(1)
7.4.3.1 Data on Landuse and Crop Yield of Recent Settlements
159(1)
7.4.3.2 The Distribution of Distances
160(1)
7.4.3.3 Estimation of the Local Intensity Function of the Recent Settlement Structure
162(1)
7.4.4 Abandoned Villages
162(1)
7.4.5 Trend or Local Intensity Function?
163(2)
7.5 Discussion
165(1)
References
165(2)
8 Integrating Spatial Statistics into Archaeological Data Modeling
167(24)
Kevin R. Schwarz and Jerry Mount
8.1 Introduction
168(1)
8.2 Theory and Method of Spatial Statistics
169(2)
8.3 Tests of Spatial Autocorrelation
171(3)
8.4 Spatial Statistical Models
174(5)
8.5 Ripley's K Statistic
179(1)
8.6 Nearest-Neighbor Hierarchical Spatial Clustering
180(3)
8.7 Notes on Applications
183(2)
8.8 Discussion and Conclusion
185(2)
References
187(4)
9 Quantifying the Qualified: The Use of Multicriteria Methods and Bayesian Statistics for the Development of Archaeological Predictive Models
191
Philip Verhagen
9.1 Introduction
192(1)
9.2 Multicriteria Decision Making and Its Relevance to Predictive Modeling
193(1)
9.3 Defining Goals
194(1)
9.4 Selection of the Evaluation Criteria
195(2)
9.5 Defining Measurement Scales
197(1)
9 6 Defining Preferences
198(1)
9.7 Establishing the Decision Rules
199(1)
9.8 Bayesian Statistics and Predictive Mapping
200(3)
9.8.1 Combining Objective and Subjective Weights
200(2)
9.8.2 Formulating the Priors
202(1)
9.9 Bayesian Statistics and Inductive Learning
203(1)
9.10 Application: The Predictive Map of Ede
204(3)
9.11 Site Density
207(2)
9.12 Site-Preservation Potential
209(3)
9.13 Conclusions
212(1)
Acknowledgments
213(1)
Notes
213(1)
References
213(6)
Section 5: Large Databases and CRM
10 Points vs. Polygons: A Test Case Using a Statewide Geographic Information System
219(72)
Philip B. Mink, II, B. Jo Stokes, and David Pollack
10.1 Digitizing Site Locations and Using Polygons to Manage Archaeological Sites
220(3)
10.2 Locational Models: Points vs. Polygons
223(13)
10.2.1 Archaeological Data
223(2)
10.2.2 Points vs. Polygons
225(11)
10.3 Conclusions
236(1)
Notes
237(1)
References
237(4)
11 Relating Cultural Resources to Their Natural Environment Using the IEDROK GIS: A Cultural Resources Management Tool for the Republic of Korea
241(1)
Bruce Verhaaren, James Levenson, and James Kuiper
11.1 Introduction
242(1)
11.2 IEDROK and the Legacy Resource Management Program
243(15)
11.2.1 IEDROK Structure: The Data Layers
245(1)
11.2.1.1 Base Layers
249(1)
11.2.1.2 Cultural Resource Layers
249(1)
11.2.1.3 Natural Resource Layers
251(1)
11.2.2 Creating the Layers: Source Data
252(1)
11.2.2.1 Cultural Resource Data
254(1)
11.2.2.2 Natural Resource Data
257(1)
11.3 Using IEDROK: System Requirements
258(1)
11.4 Finding a Location of Interest
259(6)
11.4.1 Looking Up Information around a Location
260(1)
11.4.2 Examining the Distribution of a Set of Similar Features
261(4)
12 Appropriateness and Applicability of GIS and Predictive Models with Regard to Regulatory and Nonregulatory Archaeology
265(1)
Kira E. Kaufmann
12.1 Introduction
265(2)
12.1.1 Nonregulatory Archaeological Venues
266(1)
12.1.2 Regulatory Archaeology Venues
266(1)
12.2 Theoretical Issues
267(1)
12.3 Technical Issues
267(1)
12.3.1 GIS
267(1)
12.3.2 Predictive Modeling
268(1)
12.4 Linguistic Issues
268(1)
12.5 Policy Issues
269(1)
12.6 A Specific Example: Recommendations from the State of Iowa
269(1)
12.7 Predictive Modeling
270(3)
12.8 Results of Survey
273(3)
12.9 Conclusion
276(1)
12.10 Addendum
276(2)
References
278(1)
13 Archaeological GIS in Environmental Impact Assessment and Planning
279(1)
Linda S. Naunapper
13.1 Introduction
280(1)
13.2 The Environmental Impact Assessment (EIA) Process and Role of the Screening Phase
281(6)
13.2.1 The National Environmental Policy Act (NEPA) vs. the National Historic Preservation Act (NHPA)
281(4)
13.2.2 The Role of Archaeological GIS (Predictive Models) in the Screening Phase of EIA: A Case Study
285(2)
13.3 Conclusions
287(1)
References
288(3)
Section 6: Modeling Applications in Progress
14 Understanding Lines in the Roman Landscape: A Study of Ancient Roads and Field Systems Based on GIS Technology
291(170)
Frank Vermeulen
14.1 Aims, Area, and Field Methodology
292(4)
14.2 Spatial Analysis Based on GIS
296(2)
14.3 Tracing Ancient Roads
298(7)
14.4 Unraveling Field Systems
305(9)
14.5 Concluding Remarks
314(1)
Notes
315(1)
References
315(2)
15 A GIS-Based Archaeological Predictive Model and Decision Support System for the North Carolina Department of Transportation
317(1)
Scott Madry, Matthew Cole, Steve Gould, Ben Resnick, Scott Seibel, and Matt Wilkerson
15.1 Introduction
318(1)
15.2 Project Benefits
319(1)
15.3 The Example of Mn/Model
320(1)
15.4 Project Structure
320(2)
15.4.1 Initial Project Area
321(1)
15.4.2 Task 1 Work
322(1)
15.5 Existing NC Archaeology Data
322(4)
15.5.1 GIS Data
324(1)
15.5.2 TASK 2 Work
325(1)
15.6 Project Predictive Modeling
326(3)
15.7 Modeling Research Design
329(1)
15.8 Model Validation
330(3)
15.8.1 Results
331(2)
15.9 Conclusions
333(1)
15.10 Future Directions and Recommendations
334(1)
References
334(1)
16 Multicriteria/Multiobjective Predictive Modeling: A Tool for Simulating Hunter-Gatherer Decision Making and Behavior
335(1)
Frank J. Krist, Jr.
16.1 Introduction
335(3)
16.2 Decision Theory
338(1)
16.3 A Predictive Model of Hunter-Gatherer Decision Making
339(11)
16.3.1 Module One: Objectives
341(2)
16.3.2 Module Two: Decision Rule
343(1)
16.3.3 Module Three: Criteria
343(3)
16.3.4 Multicriteria/Multiobjective Evaluations
346(4)
16.4 Discussion
350(2)
References
352(3)
17 Predictive Modeling in a Homogeneous Environment: An Example from the Charleston Naval Weapons Station, South Carolina
355(1)
Thomas G. Whitley
17.1 Introduction
356(1)
17.2 Archaeological Probabilistic Modeling
357(8)
17.2.1 Data-Dependent Models
360(2)
17.2.2 Data-Independent Models
362(2)
17.2.3 Modeling in a Homogeneous Environment
364(1)
17.3 Probabilistic Modeling at NWS
365(22)
17.3.1 Previous Modeling in the Study Area
366(2)
17.3.2 Data Gathering and Extraction
368(3)
17.3.3 Creation of Probability Surfaces
371(1)
17.3.3.1 Hunting-Gathering Adaptations
372(1)
17.3.3.2 Agricultural Economies
373(1)
17.3.3.3 Historic Settlement
373(1)
17.3.4 Probabilistic Formulas
374(3)
17.3.5 Formula Evaluation
377(1)
17.3.5.1 Results
379(1)
17.3.6 Prehistoric Site Probability
379(4)
17.3.7 Historic Site Probability
383(1)
17.3.8 Field Testing the Model
384(3)
17.4 Conclusions
387(1)
References
388(5)
18 Predictive Modeling in Archaeological Location Analysis and Archaeological Resource Management: Principles and Applications
393(1)
Tatjana Veljanovski and Zoran Stancic
18.1 Background to Principles and Applications
394(5)
18.1.1 Prediction
394(1)
18.1.2 Modeling and Prediction in Archaeology
395(1)
18.1.3 Model Verification and the Methodology Transparency Problem
396(2)
18.1.4 Predictive-Modeling Techniques
398(1)
18.2 Case Studies Perspective
399(10)
18.2.1 "Academic" Applications on the Island of Brad, Croatia
399(1)
18.2.1.1 Predicting Bronze Age Hill-Fort Locations with the Boolean Overlay Technique
399(1)
18.2.1.2 Predicting Roman Settlement Sites with the Linear Regression Technique
401(1)
18.2.1.3 Modeling the Reconstruction of Roman Settlement Land Use with the Dempster-Shafer Belief Method
404(1)
18.2.2 Practical Application in Archaeological Resource Management in Pomurje, Slovenia
405(3)
18.2.3 What Can Be Learned from These Case Studies?
408(1)
18.3 Conclusions
409(1)
References
410(3)
19 The Changing Mesopotamian Landscape as Seen from Spot and Corona Images
413(1)
Carrie Ann Hritz
19.1 Introduction
413(1)
19.2 The Environmental and Archaeological Context of Mesopotamian Irrigation
414(1)
19.3 The Adams Approach
415(2)
19.4 The Belgian Approach
417(2)
19.5 Our Theoretical Approach
419(1)
19.6 The Combined GIS Methodology
420(2)
19.7 Analysis
422(7)
19.8 Abu Salabikh: A Case Study
429(5)
19.9 Conclusions
434(1)
References
435(2)
20 Quantitative Methods in Archaeological Prediction: From Binary to Fuzzy Logic
437(1)
Eugenia G. Hatzinikolaou
20.1 Introduction
437(1)
20.2 Quantitative Methods and Their Applications in the Prediction of Archaeological Site Locations
438(5)
20.2.1 Regression Analysis: Logistic Regression
439(1)
20.2.2 Multicriteria Analysis
440(1)
20.2.3 Expert Systems
441(1)
20.2.4 Supervised Classification
441(1)
20.2.5 Unsupervised Classification (Cluster Analysis)
442(1)
20.2.6 Fuzzy Logic
442(1)
20.3 An Evaluation of the Methods: From Binary to Fuzzy Logic
443(2)
References
445(2)
21 The Use of Predictive Modeling for Guiding the Archaeological Survey of Roman Pottery Kilns in the Argonne Region (Northeastern France)
447(1)
Philip Verhagen and Michiel Gazenbeek
21.1 Introduction
448(1)
21.2 Archaeological Context
449(1)
21.3 Area Description
450(4)
21.4 The First Predictive Model
454(2)
21.5 The Second Predictive Model
456(1)
21.6 The Final Model
457(1)
21.7 Conclusions
458(1)
Acknowledgments
459(1)
References
459(2)
Index 461


Mark W. Mehrer, Konnie L. Wescott
Biežāk uzdotie jautājumi par e-grāmatām Biežāk uzdotie jautājumi par e-grāmatām
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