150:
56:
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
319:
146:
There are a variety of tools, models, and algorithms that incorporate geographic distance, due to the variety of relevant problems and tasks.
421:
366:
35:
300:
392:
167:, algorithms for finding optimal routes through continuous space that minimize distance and/or other location dependent costs.
183:, a mathematical model of how the influence of a phenomenon tends to be inversely proportional to the distance from it. A
30:
as a central principle. Distance is fundamental to geographic inquiry and spatial analysis, due to principles such as the
241:
65:
216:
450:
190:
107:
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
176:
123:
115:
108:
444:
184:
158:
93:
207:
88:, the shortest distance between two locations that stays on the surface of the
430:
79:
51:
27:
211:
Illustration of
Dijkstra's Algorithm, a core element of Network Analysis
434:
345:
de Smith, Michael J.; Goodchild, Michael F.; Longley, Paul A. (2018).
425:
350:
293:
Self-organizing maps: Applications in geographic information science
206:
148:
89:
104:, but the method is significantly more difficult on an ellipsoid.
122:
of related concepts, and the hypertext network of the
239:
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:.
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.