Table 6

SOUTH DAKOTA

Offenses Known to Law Enforcement

by City, 2016

City Population Violent
crime
Murder and
nonnegligent
manslaughter
Rape
(revised
definition)1
Rape
(legacy
definition)2
Robbery Aggravated
assault
Property
crime
Burglary Larceny-
theft
Motor
vehicle
theft
Arson
Aberdeen 28,498 134 0 29 5 100 621 117 467 37 4
Alcester 752 5 0 1 0 4 8 4 4 0 0
Avon 567 0 0 0 0 0 0 0 0 0 0
Belle Fourche 5,714 13 0 1 0 12 76 19 57 0 0
Beresford 1,969 4 0 1 0 3 13 1 12 0 0
Box Elder 9,607 30 0 6 2 22 168 30 127 11 1
Brandon 10,042 0 0 0 0 0 38 4 33 1 0
Brookings 23,971 35 0 12 1 22 374 44 294 36 2
Burke 586 0 0 0 0 0 0 0 0 0 0
Canton 3,380 7 0 1 0 6 27 11 14 2 0
Chamberlain 2,383 18 0 2 1 15 71 10 61 0 0
Clark 1,033 2 0 0 0 2 23 5 16 2 0
Deadwood 1,255 5 0 0 0 5 6 0 6 0 0
Eagle Butte 1,355 0 0 0 0 0 2 0 2 0 0
Flandreau 2,296 14 0 1 2 11 57 10 41 6 0
Freeman 1,284 0 0 0 0 0 0 0 0 0 0
Hermosa 390 0 0 0 0 0 0 0 0 0 0
Hot Springs 3,507 9 0 1 0 8 40 11 29 0 0
Huron 13,459 35 0 10 0 25 257 39 201 17 1
Kadoka 718 1 0 0 0 1 5 1 4 0 0
Lead 2,974 1 0 0 0 1 15 0 15 0 0
Lennox 2,304 2 0 1 0 1 9 1 7 1 0
Leola 437 0 0 0 0 0 0 0 0 0 0
Madison 7,411 4 0 0 0 4 76 15 57 4 0
Martin 1,059 17 1 1 2 13 65 16 46 3 1
Menno 593 0 0 0 0 0 0 0 0 0 0
Miller 1,427 0 0 0 0 0 14 8 6 0 0
Mitchell 15,749 90 0 8 5 77 579 88 443 48 2
Mobridge 3,465 15 0 2 0 13 45 2 35 8 0
North Sioux City 2,772 0 0 0 0 0 52 0 49 3 0
Parkston 1,483 3 0 1 0 2 0 0 0 0 0
Philip 747 0 0 0 0 0 0 0 0 0 0
Pierre 14,068 63 0 7 1 55 642 85 529 28 0
Rapid City 74,573 536 2 88 80 366 2,966 480 2,236 250 2
Rosholt 428 0 0 0 0 0 1 1 0 0 0
Scotland 816 0 0 0 0 0 0 0 0 0 0
Sioux Falls 175,152 897 6 142 121 628 5,563 869 4,076 618 45
Sisseton 2,451 3 0 0 0 3 10 3 7 0 0
Spearfish 11,429 28 0 9 2 17 377 43 321 13 0
Springfield 1,947 0 0 0 0 0 0 0 0 0 0
Sturgis 6,699 10 0 0 0 10 124 12 105 7 1
Summerset 2,329 0 0 0 0 0 20 2 17 1 1
Tea 5,064 9 0 1 1 7 67 16 48 3 0
Tripp 627 0 0 0 0 0 3 3 0 0 0
Tyndall 1,046 0 0 0 0 0 0 0 0 0 0
Vermillion 10,774 20 0 4 0 16 212 25 170 17 0
Viborg 758 2 0 0 0 2 1 0 1 0 0
Wagner 1,593 10 0 2 0 8 19 0 18 1 0
Watertown 22,186 89 0 13 8 68 596 73 489 34 2
Whitewood 916 1 0 0 0 1 3 0 2 1 0
Winner 2,805 9 0 1 1 7 18 2 13 3 0
Worthing 955 0 0 0 0 0 0 0 0 0 0
Yankton 14,575 48 0 10 4 34 453 57 384 12 0
  • 1 The figures shown in this column for the offense of rape were reported using the revised Uniform Crime Reporting (UCR) definition of rape. See the data declaration for further explanation.
  • 2 The figures shown in this column for the offense of rape were reported using the legacy UCR definition of rape. See the data declaration for further explanation.

Data Declaration

Provides the methodology used in constructing this table and other pertinent information about this table.