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USPTO Patent Rankings Data through Dec 31, 2025
Home › 2016 › Cities

Top Cities for Patents 2016

Ranked by total patent count — worldwide

Showing 3,001–3,200 of 41,021 cities

Rank City Patents ↓ Inventors ↕ Per 1k pop. ↕
#3001 Grand Island, NY 38 24 —
#3002 Grand Prairie, TX 38 30 0.2
#3003 Grosse Pointe Farms, MI 38 21 3.7
#3004 Guildford, GB 38 30 —
#3005 Hawthorne, CA 38 21 0.4
#3006 Ibaraki, JP 38 9 —
#3007 Iitate, JP 38 13 —
#3008 Iselin, NJ 38 19 1.9
#3009 Kaiserslautern, DE 38 33 —
#3010 Kaminokawa, JP 38 14 —
#3011 Kanazawa, JP 38 29 —
#3012 Kiryat Motzkin, IL 38 25 —
#3013 Kitaibaraki, JP 38 21 —
#3014 Kizugawa, JP 38 22 —
#3015 La Puente, CA 38 24 1.0
#3016 L'Essart Mador, FR 38 15 —
#3017 London, GB 38 20 —
#3018 Longbeilingcun, CN 38 11 —
#3019 Marshfield, MA 38 18 8.2
#3020 McHenry, IL 38 23 1.4
#3021 Milltown, NJ 38 9 5.4
#3022 Mouans-Sartoux, FR 38 15 —
#3023 Nanuet, NY 38 22 2.0
#3024 Northampton, GB 38 19 —
#3025 Oakton, VA 38 23 1.0
#3026 Orbassano, IT 38 24 —
#3027 Peabody, MA 38 27 0.7
#3028 Phillipsburg, NJ 38 20 2.5
#3029 Pikesville, MD 38 19 1.1
#3030 Poing, DE 38 23 —
#3031 Porto Alegre, BR 38 34 —
#3032 Rosenheim, DE 38 30 —
#3033 Seeheim-Jugenheim, DE 38 25 —
#3034 Shanghai, CN 38 7 —
#3035 Shibuya, JP 38 17 —
#3036 Shiojiri, JP 38 10 —
#3037 Springfield, NJ 38 15 25.0
#3038 Steamboat Springs, CO 38 14 2.9
#3039 Taastrup, DK 38 31 —
#3040 Tajimi, JP 38 15 —
#3041 Timrå, SE 38 33 —
#3042 Uttoxeter, GB 38 21 —
#3043 Vejle, DK 38 28 —
#3044 Weisweil, DE 38 1 —
#3045 Woodbridge, CT 38 31 —
#3046 Xi'an, CN 38 8 —
#3047 Yorktown, VA 38 33 171.9
#3048 Assendelft, NL 37 4 —
#3049 Bensalem, PA 37 24 —
#3050 Blankenloch, DE 37 33 —
#3051 Brunswick, OH 37 22 1.0
#3052 Bunkyo, JP 37 23 —
#3053 Burleson, TX 37 26 0.8
#3054 Buxtehude, DE 37 26 —
#3055 Camp Hill, PA 37 14 4.5
#3056 Cassville, WI 37 1 47.6
#3057 Chantepie, FR 37 23 —
#3058 Cleveland, AU 37 24 —
#3059 Clifton, NJ 37 27 0.4
#3060 Covington, WA 37 13 1.8
#3061 Derry, NH 37 31 1.6
#3062 Duxbury, MA 37 21 19.5
#3063 Echizen, JP 37 24 —
#3064 Erfurt, DE 37 28 —
#3065 Farnborough, GB 37 19 —
#3066 Forest, VA 37 21 3.2
#3067 Fuzhou, CN 37 26 —
#3068 Grosse Ile Township, MI 37 22 —
#3069 Hauppauge, NY 37 15 1.8
#3070 Hawthorn Woods, IL 37 17 4.1
#3071 Herrenberg, DE 37 30 —
#3072 Hillsborough Township, NJ 37 29 —
#3073 Hokuto, JP 37 14 —
#3074 Hwaseong-si, KR 37 1 —
#3075 Kessel-Lo, BE 37 19 —
#3076 Kirkkonummi, FI 37 23 —
#3077 Kohler, WI 37 14 16.9
#3078 Lakewood, CA 37 25 0.5
#3079 Laufenburg (Baden), DE 37 27 —
#3080 Leighton, IA 37 3 234.2
#3081 Le Plessis-Robinson, FR 37 19 —
#3082 Liverpool, NY 37 26 16.5
#3083 Mandeville, LA 37 28 2.8
#3084 Metairie, LA 37 25 0.3
#3085 Montrouge, FR 37 28 —
#3086 Monument, CO 37 27 3.6
#3087 New Canaan, CT 37 22 6.0
#3088 North Olmsted, OH 37 25 1.1
#3089 North Royalton, OH 37 28 1.2
#3090 Oakley Park, MI 37 7 —
#3091 Ober-Ramstadt, DE 37 12 —
#3092 Oomuta, JP 37 19 —
#3093 Orsay, FR 37 29 —
#3094 Osaka, JP 37 11 —
#3095 Oss, NL 37 30 —
#3096 Palmdale, CA 37 30 0.2
#3097 Pescara, IT 37 20 —
#3098 Pully, CH 37 23 —
#3099 Radebeul, DE 37 27 —
#3100 Rifu, JP 37 17 —
#3101 River Falls, WI 37 27 2.3
#3102 Romulus, MI 37 5 1.5
#3103 Ross, CA 37 9 15.8
#3104 Sanford, MI 37 20 45.5
#3105 Seongnam-si, KR 37 3 —
#3106 Sheridan, WY 37 11 2.0
#3107 Short Hills, NJ 37 24 2.6
#3108 Sichuan, CN 37 12 —
#3109 Singapore, SG 37 14 —
#3110 Smørumnedre, DK 37 26 —
#3111 Sussex, WI 37 21 3.2
#3112 Takahama, JP 37 24 —
#3113 Teddington, GB 37 11 —
#3114 Upland, CA 37 27 0.5
#3115 Vallauris, FR 37 18 —
#3116 Waterford Township, MI 37 27 —
#3117 Yamanashi, JP 37 11 —
#3118 Yangmei District, TW 37 26 —
#3119 Zhejiang, CN 37 4 —
#3120 Amarillo, TX 36 28 0.2
#3121 Bari, IT 36 27 —
#3122 Beilstein, DE 36 17 —
#3123 Bengaluru, IN 36 18 —
#3124 Besançon, FR 36 26 —
#3125 Betton, FR 36 27 —
#3126 Bhavnagar, IN 36 27 —
#3127 Brentwood, CA 36 25 0.6
#3128 Cambridge, GB 36 13 —
#3129 Changzhou City, CN 36 29 —
#3130 Chillicothe, IL 36 26 5.9
#3131 Effingham, IL 36 7 2.9
#3132 Ewing, NJ 36 19 —
#3133 Farmington, MN 36 23 1.5
#3134 Finkenstein, AT 36 11 —
#3135 Fridley, MN 36 23 1.2
#3136 Fujian, CN 36 5 —
#3137 Geleen, NL 36 23 —
#3138 Griesheim, DE 36 24 —
#3139 Horgen, CH 36 22 —
#3140 Houma, LA 36 28 1.1
#3141 Kammi, JP 36 20 —
#3142 Kampung Bukit Kechil, MY 36 11 —
#3143 Kleinmachnow, DE 36 17 —
#3144 Kolbermoor, DE 36 5 —
#3145 Le Bouveret, CH 36 2 —
#3146 Longboat Key, FL 36 11 4.8
#3147 Moreland Hills, OH 36 15 10.4
#3148 Muncie, IN 36 14 0.6
#3149 Nanjing, CN 36 1 —
#3150 Neuilly-sur-Seine, FR 36 21 —
#3151 Neunburg vorm Wald, DE 36 22 —
#3152 New Braunfels, TX 36 22 0.4
#3153 Nieder-Olm, DE 36 12 —
#3154 North Hinksey, GB 36 22 —
#3155 Pordenone, IT 36 26 —
#3156 Princeton, IL 36 3 4.6
#3157 Redlands, CA 36 26 0.5
#3158 Sagamihara, JP 36 8 —
#3159 Saitama, JP 36 11 —
#3160 Sanjiaodian, TW 36 6 —
#3161 Savanuru, IN 36 23 —
#3162 Shorewood, MN 36 23 4.6
#3163 Sidney Place, GA 36 10 —
#3164 Sittard, NL 36 28 —
#3165 Tsukuba, JP 36 8 —
#3166 Ulsan, KR 36 8 —
#3167 Vacaville, CA 36 23 0.3
#3168 Velbert, DE 36 21 —
#3169 Vélizy-Villacoublay, FR 36 28 —
#3170 Waldkirch, DE 36 31 —
#3171 Waterbury, CT 36 21 0.3
#3172 Wels, AT 36 28 —
#3173 Wentzville, MO 36 23 0.8
#3174 West Henrietta, NY 36 23 —
#3175 Willoughby, OH 36 23 1.5
#3176 Wulfen, DE 36 34 —
#3177 Yamhill, OR 36 4 31.4
#3178 Yehud Monosson, IL 36 32 —
#3179 Yokohama, JP 36 5 —
#3180 Yongin-si, KR 36 8 —
#3181 Yongin-si, KR 36 8 —
#3182 Zwolle, NL 36 28 —
#3183 Beijing, CN 35 16 —
#3184 Berkley, MI 35 16 2.3
#3185 Bhangrola, IN 35 9 —
#3186 Big Lake, MN 35 23 3.0
#3187 Blue Ash, OH 35 12 2.6
#3188 Braintree, MA 35 20 —
#3189 Brest, FR 35 25 —
#3190 Buena Park, CA 35 24 0.4
#3191 Cadillac, MI 35 24 3.4
#3192 Cape Town, ZA 35 8 —
#3193 Chester, GB 35 23 —
#3194 Closter, NJ 35 11 4.1
#3195 Crystal, MN 35 20 1.5
#3196 Edgewood, NM 35 14 5.7
#3197 Ellington, CT 35 24 —
#3198 Foshan, CN 35 11 —
#3199 Fukuoka, JP 35 9 —
#3200 Glendora, CA 35 25 0.7

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