Knowledge

Proximity analysis

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All proximity analysis tools are based on a measure of distance between two locations. This may seen as a simplistic geometric measurement, but the nature of geographic phenomena and geographic activity requires several candidate methods to measure and express distance and distance-related measures.
219:, a set of algorithms and tools for solving a number of distance routing problems when travel is constrained to a network of one-dimensional lines, such as roads and utility networks. For example, the common task of finding the shortest route from point A to point B, which is typically solved using 203:, an array containing the distances (Euclidean or otherwise) between any two points in a set. This is frequently used as the independent variable in statistical tests of whether the strength of a relationship is correlated with distance, such as the volume of trade between cities. 208: 193:, a set of (usually heuristic) algorithms for finding the optimal locations of a limited set of points (e.g., store locations) that minimize the aggregate distance to another set of points (e.g., customer locations). A commonly used example is 173:, also known as Thiessen polygons, an algorithm for partitioning continuous space into a set of regions based on a set of point locations, such that each region consists of locations that are closer to one of the points than any others. 136:
because it generally serves as an undesirable quantity to be minimized. Travel time is the most common cost measurement, but other costs include carbon emissions, fuel consumption, environmental impacts, and construction
78:, the distance between two locations in a cartesian (planar) coordinate system along a path that only follows the x and y axes (thus appearing similar to a path through a grid street network such as that of 132:, a measurement along a route (in any of the above spaces) in which geometric distance is replaced by some other quantity that accumulates along the route (and is thus proportional to distance), called a 42:, which are incorporated into analytical tools. Proximity methods are thus used in a variety of applications, especially those that involve movement and interaction. 64:, the straight-line geometric distance measured on a planar surface. In geographic information systems, this can be easily calculated from locations in a cartesian 126:. Although these are not inherently geographic, projecting them into an abstract space allows geographic tools such as proximity analysis to be used to study them. 244: 114:
Abstract distance, a measurement of distance in a space that is only indirectly related to geographic space, or only metaphorically spatial. Examples include
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There are a variety of tools, models, and algorithms that incorporate geographic distance, due to the variety of relevant problems and tasks.
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as a central principle. Distance is fundamental to geographic inquiry and spatial analysis, due to principles such as the
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Network distance, a measurement between two locations along a route within a constrained linear space, such as a
346: 101: 220: 39: 164: 129: 161:, a tool for determining the region that is within a specified distance of a set of geographic features. 97: 85: 194: 72:. While it is the simplest method to measure distance, it rarely reflects actual geographic movement. 31: 69: 180: 119: 75: 61: 296: 23: 265: 149: 248: 200: 170: 352:
Geospatial Analysis: A Comprehensive Guide to Principles, Techniques, and Software Tools
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Illustration of Dijkstra's Algorithm, a core element of Network Analysis
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de Smith, Michael J.; Goodchild, Michael F.; Longley, Paul A. (2018).
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Self-organizing maps: Applications in geographic information science
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of related concepts, and the hypertext network of the
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Blinn, Charles R., Lloyd P. Queen, and Les W. Maki,
314: 312: 242:"Geographic Information Systems: A Glossary." 8: 26:tools and algorithms that employ geographic 16:Geospatial methods for analyzing distance 259: 257: 291:Agarwal, Pragya; Skupin, André (2008). 232: 7: 14: 36:Tobler's first law of geography 320:"How cost distance tools work" 118:of interpersonal connections, 1: 367:"25.1.18.81 Voronoi polygons" 266:"FC-42 - Distance Operations" 270:GIS&T Body of Knowledge 66:Projected coordinate system 467: 217:Transport network analysis 49: 393:"Network Analyst solvers" 347:"4.4 Distance Operations" 397:ArcGIS Pro Documentation 324:ArcGIS Pro Documentation 102:spherical law of cosines 431:OGC ST_DWithin function 371:QGIS 3.22 Documentation 100:, the formula uses the 40:Spatial autocorrelation 212: 165:Cost distance analysis 154: 210: 152: 221:Dijkstra's algorithm 32:friction of distance 187:is a similar model. 111:or utility network. 70:Pythagorean theorem 247:2010-03-22 at the 213: 181:Inverse square law 155: 120:information spaces 76:Manhattan distance 62:Euclidean distance 20:Proximity analysis 195:Lloyd's algorithm 191:Location analysis 153:A Voronoi diagram 86:Geodesic distance 46:Distance measures 458: 451:Spatial analysis 409: 408: 406: 404: 389: 383: 382: 380: 378: 363: 357: 356: 342: 336: 335: 333: 331: 316: 307: 306: 288: 282: 281: 279: 277: 261: 252: 237: 24:spatial analysis 466: 465: 461: 460: 459: 457: 456: 455: 441: 440: 437:implementation) 422:Proximity tools 418: 413: 412: 402: 400: 391: 390: 386: 376: 374: 365: 364: 360: 355:(6th ed.). 344: 343: 339: 329: 327: 318: 317: 310: 303: 290: 289: 285: 275: 273: 263: 262: 255: 249:Wayback Machine 238: 234: 229: 201:Distance matrix 179:, based on the 171:Voronoi diagram 144: 116:social networks 54: 48: 17: 12: 11: 5: 464: 462: 454: 453: 443: 442: 439: 438: 428: 417: 416:External links 414: 411: 410: 384: 358: 337: 308: 301: 283: 253: 231: 230: 228: 225: 224: 223: 205: 204: 198: 188: 177:Distance decay 174: 168: 162: 143: 140: 139: 138: 127: 124:World Wide Web 112: 105: 92:, following a 83: 73: 50:Main article: 47: 44: 22:is a class of 15: 13: 10: 9: 6: 4: 3: 2: 463: 452: 449: 448: 446: 436: 432: 429: 427: 423: 420: 419: 415: 398: 394: 388: 385: 372: 368: 362: 359: 354: 353: 348: 341: 338: 325: 321: 315: 313: 309: 304: 302:9780470021675 298: 294: 287: 284: 271: 267: 260: 258: 254: 251: 250: 246: 243: 236: 233: 226: 222: 218: 215: 214: 209: 202: 199: 196: 192: 189: 186: 185:Gravity model 182: 178: 175: 172: 169: 166: 163: 160: 157: 156: 151: 147: 141: 135: 131: 130:Cost distance 128: 125: 121: 117: 113: 110: 106: 103: 99: 95: 91: 87: 84: 81: 77: 74: 71: 67: 63: 60: 59: 58: 53: 45: 43: 41: 37: 33: 29: 25: 21: 401:. Retrieved 396: 387: 375:. Retrieved 370: 361: 351: 340: 328:. Retrieved 323: 292: 286: 274:. Retrieved 269: 240: 235: 145: 133: 94:great circle 55: 19: 18: 264:Sarkar, D. 227:References 142:Techniques 68:using the 403:5 January 377:5 January 330:5 January 295:. Wiley. 276:5 January 80:Manhattan 445:Category 424:in Esri 245:Archived 52:Distance 28:distance 435:PostGIS 373:. OSGEO 272:. UCGIS 159:Buffers 96:. On a 426:ArcGIS 399:. Esri 326:. Esri 299:  137:costs. 98:sphere 38:, and 90:Earth 405:2023 379:2023 332:2023 297:ISBN 278:2023 134:cost 109:road 447:: 395:. 369:. 349:. 322:. 311:^ 268:. 256:^ 82:). 34:, 433:( 407:. 381:. 334:. 305:. 280:. 197:.

Index

spatial analysis
distance
friction of distance
Tobler's first law of geography
Spatial autocorrelation
Distance
Euclidean distance
Projected coordinate system
Pythagorean theorem
Manhattan distance
Manhattan
Geodesic distance
Earth
great circle
sphere
spherical law of cosines
road
social networks
information spaces
World Wide Web
Cost distance

Buffers
Cost distance analysis
Voronoi diagram
Distance decay
Inverse square law
Gravity model
Location analysis
Lloyd's algorithm

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