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USPTO Patent Rankings Data through Dec 31, 2025
Home › 2017 › Cities

Top Cities for Patents 2017

Ranked by total patent count — worldwide

Showing 3,201–3,400 of 42,209 cities

Rank City Patents ↓ Inventors ↕ Per 1k pop. ↕
#3201 La Crosse, WI 37 22 0.7
#3202 Latrobe, PA 37 20 4.6
#3203 Levittown, NY 37 21 0.7
#3204 Lindome, SE 37 30 —
#3205 Lone Tree, CO 37 21 2.6
#3206 Ludvika, SE 37 32 —
#3207 Middelfart, DK 37 29 —
#3208 Mobile, AL 37 27 0.2
#3209 Mont-Laurier, CA 37 20 —
#3210 Nacka, SE 37 25 —
#3211 Nanhu, CN 37 17 —
#3212 Oak Brook, IL 37 20 4.5
#3213 Owings Mills, MD 37 23 1.0
#3214 Parma, OH 37 28 0.5
#3215 Payson, UT 37 17 1.8
#3216 Ried im Innkreis, AT 37 21 —
#3217 Romulus, MI 37 4 1.5
#3218 Rötteln, DE 37 14 —
#3219 Royersford, PA 37 20 7.5
#3220 Sauerlach, DE 37 12 —
#3221 Seligenstadt, DE 37 15 —
#3222 Sichuan, CN 37 19 —
#3223 Söderhamn, SE 37 20 —
#3224 Sussex, WI 37 24 3.2
#3225 Taastrup, DK 37 22 —
#3226 Teddington, GB 37 17 —
#3227 Tequesta, FL 37 10 6.0
#3228 Traunstein, DE 37 20 —
#3229 Truckee, CA 37 19 2.2
#3230 Umka, RS 37 28 —
#3231 Wakefield, RI 37 17 —
#3232 Waldkraiburg, DE 37 16 —
#3233 Wyoming, OH 37 19 4.2
#3234 Adelaide, AU 36 4 —
#3235 Alhambra, CA 36 26 0.4
#3236 Barrington Hills, IL 36 4 8.8
#3237 Berkley, MI 36 21 2.4
#3238 Bonneville, FR 36 19 —
#3239 Brest, FR 36 31 —
#3240 Buena Park, CA 36 20 0.4
#3241 Burghausen, DE 36 27 —
#3242 Busan, KR 36 16 —
#3243 Butler, PA 36 29 2.7
#3244 Catonsville, MD 36 27 0.8
#3245 Clarksburg, MD 36 22 1.2
#3246 College Park, MD 36 26 1.0
#3247 Elder Mountain, TN 36 19 —
#3248 Fairfield, CA 36 25 0.3
#3249 Felton, CA 36 15 8.0
#3250 Galveston, TX 36 27 0.7
#3251 Glendale, WI 36 27 2.7
#3252 Granville, OH 36 24 6.0
#3253 Greater Noida, IN 36 27 —
#3254 Greenfield, IN 36 19 1.5
#3255 Guildford, GB 36 27 —
#3256 Gyeongsan-si, KR 36 31 —
#3257 Hanam-si, KR 36 24 —
#3258 Hangzhou City, CN 36 16 —
#3259 Harrisburg, NC 36 21 1.9
#3260 Harrison, MI 36 20 16.7
#3261 Holzminden, DE 36 26 —
#3262 Huzhou City, CN 36 26 —
#3263 Icheon-si, KR 36 2 —
#3264 Johnson City, TN 36 25 0.5
#3265 Joinville, BR 36 31 —
#3266 Kaohsiung, TW 36 15 —
#3267 Leesburg, IN 36 12 64.9
#3268 Leimen, DE 36 23 —
#3269 Locke, NY 36 4 —
#3270 Macon, GA 36 24 —
#3271 Manhattan, NY 36 17 —
#3272 Mishawaka, IN 36 24 0.7
#3273 Mölnlycke, SE 36 21 —
#3274 Monterey, CA 36 26 1.2
#3275 Nagaokakyo, JP 36 7 —
#3276 Newcastle upon Tyne, GB 36 26 —
#3277 Noida, IN 36 15 —
#3278 Oakton, VA 36 23 1.0
#3279 Oxford, NC 36 7 4.2
#3280 Pembroke, MA 36 11 —
#3281 Prosper, TX 36 21 1.2
#3282 Quakertown, PA 36 30 3.9
#3283 Ravensburg, DE 36 31 —
#3284 Red Wing, MN 36 20 2.2
#3285 Reims, FR 36 30 —
#3286 Romeo, MI 36 19 9.6
#3287 Saint-Avertin, FR 36 21 —
#3288 Saint-Jean, FR 36 20 —
#3289 Saint-Julien-en-Genevois, FR 36 17 —
#3290 San Joaquin Hills, CA 36 9 —
#3291 Seongju-eup, KR 36 18 —
#3292 Shiwen, TW 36 5 —
#3293 Shunan, JP 36 25 —
#3294 Steinheim, DE 36 21 —
#3295 Tokyo, JP 36 9 —
#3296 Topsfield, MA 36 18 12.6
#3297 Van Buren Township, MI 36 6 —
#3298 Viken, SE 36 6 —
#3299 West Allis, WI 36 21 0.6
#3300 West Fargo, ND 36 21 0.9
#3301 Willmar, MN 36 12 1.7
#3302 Willoughby, OH 36 22 1.5
#3303 Wunstorf, DE 36 18 —
#3304 Yeadon, PA 36 23 3.0
#3305 Al Khobar, SA 35 23 —
#3306 Baiersdorf, DE 35 19 —
#3307 Balamban, PH 35 28 —
#3308 Bartlett, TN 35 28 0.6
#3309 Bengaluru, IN 35 22 —
#3310 Bergen op Zoom, NL 35 22 —
#3311 Brewster, NY 35 17 14.0
#3312 Brno, CZ 35 4 —
#3313 Buffalo, MN 35 21 2.2
#3314 Byron Center, MI 35 19 4.7
#3315 Chiba, JP 35 8 —
#3316 Chichibu, JP 35 22 —
#3317 Chico, CA 35 26 0.3
#3318 Columbus, GA 35 20 0.2
#3319 Concord, NH 35 20 0.8
#3320 Coopersburg, PA 35 20 14.3
#3321 Coventry, CT 35 24 —
#3322 Cukeng, TW 35 3 —
#3323 Eagle Mountain, UT 35 24 0.8
#3324 East Lyme, CT 35 18 —
#3325 Glen Mills, PA 35 19 —
#3326 Granada, ES 35 15 —
#3327 Grosse Pointe Farms, MI 35 22 3.5
#3328 Grosse Pointe Woods, MI 35 16 2.1
#3329 Hawthorne, NY 35 11 7.5
#3330 Hawthorn Woods, IL 35 22 3.9
#3331 Hendersonville, TN 35 23 0.6
#3332 Hickory Corner, NJ 35 8 —
#3333 Hod HaSharon, IL 35 10 —
#3334 Houma, LA 35 21 1.1
#3335 Hwaseong-si, KR 35 6 —
#3336 Kiryat Bialik, IL 35 24 —
#3337 Kwai Chung, CN 35 25 —
#3338 Lakeway, TX 35 18 1.8
#3339 Lannion, FR 35 27 —
#3340 Lindenhurst, NY 35 21 1.3
#3341 Lynn, MA 35 24 0.3
#3342 Maidstone, GB 35 18 —
#3343 Marlborough, CT 35 16 —
#3344 Mazkeret Batya, IL 35 25 —
#3345 McFarland, WI 35 22 3.9
#3346 Milton, WI 35 10 6.1
#3347 Mission Hills, KS 35 4 9.7
#3348 Monroe, MI 35 21 1.7
#3349 Montara, CA 35 16 12.3
#3350 Morrow, OH 35 15 17.1
#3351 Neutraubling, DE 35 27 —
#3352 New Hope, MN 35 20 1.6
#3353 New Kensington, PA 35 20 2.9
#3354 Newtown, CT 35 26 18.3
#3355 Nicholasville, KY 35 22 1.1
#3356 North Salem, NY 35 6 —
#3357 Osaka, JP 35 12 —
#3358 Pacific Grove, CA 35 20 2.3
#3359 Paramus, NJ 35 17 1.3
#3360 Raynham, MA 35 27 —
#3361 Rifu, JP 35 13 —
#3362 Ringoes, NJ 35 17 41.2
#3363 River Edge, NJ 35 16 2.9
#3364 Scotland, GB 35 16 —
#3365 Seongnam-si, KR 35 10 —
#3366 Snowville, NH 35 1 —
#3367 Stafford, GB 35 21 —
#3368 St. George, UT 35 27 0.4
#3369 Stockton, CA 35 26 0.1
#3370 Taizhou City, CN 35 24 —
#3371 Taunton, MA 35 20 0.6
#3372 Tyngsborough, MA 35 22 —
#3373 Upton, MA 35 20 11.3
#3374 Urayasu, JP 35 14 —
#3375 Veenendaal, NL 35 17 —
#3376 Vejle, DK 35 27 —
#3377 Verona, IT 35 32 —
#3378 Wenzenbach, DE 35 15 —
#3379 Yamanashi, JP 35 12 —
#3380 Ansan-si, KR 34 11 —
#3381 Ashland, OR 34 24 1.6
#3382 Baofeng County, CN 34 26 —
#3383 Bernardsville, NJ 34 16 4.3
#3384 Caledonia, MI 34 19 21.0
#3385 Cassville, WI 34 1 43.8
#3386 Cedar Hills, UT 34 19 3.4
#3387 Clovis, CA 34 23 0.3
#3388 Colmar, FR 34 20 —
#3389 DeLand, FL 34 22 0.9
#3390 Detmold, DE 34 25 —
#3391 Detroit Lakes, MN 34 15 3.5
#3392 Dongjin-myeon, KR 34 33 —
#3393 Eckental, DE 34 15 —
#3394 Edgewater, NJ 34 18 2.4
#3395 Eijsden, NL 34 22 —
#3396 Euless, TX 34 25 0.6
#3397 Farmington, MN 34 28 1.4
#3398 Forest Grove, OR 34 23 1.3
#3399 Forest Park, PA 34 15 —
#3400 Fujian, CN 34 7 —

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