°ÇÃ൵½Ã°ø°£¿¬±¸¼Ò

Architecture & Urban Research Institute

pdf¿ø¹®º¸±â ¿¡·¯ ÇØ°á¹æ¹ý ¹Ù·Î°¡±â



¹®ÇåȨ > ¿¬±¸³í¹® > »ó¼¼

[¿ø¹®º¸±â½Ã ¼ÒºñµÇ´Â Æ÷ÀÎÆ® : 100 Æ÷ÀÎÆ®] ¹Ì¸®º¸±â Àοë

´ëÇÑÅä¸ñÇÐȸ|´ëÇÑÅä¸ñÇÐȸ³í¹®Áý 2025³â 10¿ù

³í¹®¸í ÀÚ¿¬ÀçÇØ°¡ ´ëµµ½Ã ±Ù¸° À¯Çü º¯È­¿¡ ¹ÌÄ¡´Â ¿µÇâ / Impact of Natural Hazards on Neighborhood Type Changes in Metropolitan Cities
ÀúÀÚ¸í ÀÌ´Þº°(Lee, Dalbyul)
¹ßÇà»ç ´ëÇÑÅä¸ñÇÐȸ
¼ö·Ï»çÇ× ´ëÇÑÅä¸ñÇÐȸ³í¹®Áý, v.45 n.5 (2025-10)
ÆäÀÌÁö ½ÃÀÛÆäÀÌÁö(589) ÃÑÆäÀÌÁö(11)
ISSN 10156348
ÁÖÁ¦ºÐ·ù /
ÁÖÁ¦¾î ÀÚ¿¬ÀçÇØ;±Ù¸° º¯È­;´ëµµ½Ã;·ÎÁö½ºÆ½ ȸ±ÍºÐ¼®;Áý°è±¸ ; Natural hazards;Neighborhood change;Metropolitan city;Logistic Regression analysis;Census output area
¿ä¾à1 ÀÌ ¿¬±¸´Â ¼¼Á¾À» Á¦¿ÜÇÑ 7°³ ±¤¿ª½Ã(¼­¿ï, ºÎ»ê, ´ë±¸, ÀÎõ, ±¤ÁÖ, ´ëÀü, ¿ï»ê)¸¦ ´ë»óÀ¸·Î ÀÚ¿¬ÀçÇØ ÇÇÇØ°¡ ±Ù¸° À¯Çü º¯È­¿¡ ¹ÌÄ¡´Â ¿µÇâÀ» ºÐ¼®ÇÏ¿´´Ù. Áý°è±¸¸¦ ºÐ¼®´ÜÀ§·Î ·ÎÁö½ºÆ½ ȸ±ÍºÐ¼®À» ÀÌ¿ëÇÏ¿© 2010³âºÎÅÍ 2023³â±îÁöÀÇ ±Ù¸° º¯È­¸¦ ÃßÀûÇÏ¿´´Ù. ¸ÕÀú k-Æò±Õ ±ºÁýºÐ¼®À» ÅëÇØ ¼¼ °¡Áö ±Ù¸° À¯Çü(È¥ÇÕ, ½ÅÃࡤ¾ÆÆÄÆ®, ³ëÈÄ¡¤´Üµ¶ÁÖÅÃ)À» µµÃâÇϰí, 2010³â°ú 2023³â »çÀÌÀÇ ±Ù¸° À¯Çü º¯È­¸¦ »êÁ¤ÇÏ¿´´Ù. ·ÎÁö½ºÆ½ ȸ±ÍºÐ¼® °á°ú, ¿¬Æò±Õ ÀÚ¿¬ÀçÇØ ÇÇÇØ¾×ÀÌ Áõ°¡ÇÔ¿¡ µû¶ó ±Ù¸°ÀÌ º¯È­ÇÒ °¡´É¼ºÀÌ 18.0 % °¨¼ÒÇÏ¿´´Ù. ÀÚ¿¬ÀçÇØ°¡ ¹ÌÄ£ ±Ù¸° º¯È­ °¡´É¼ºÀº µµ½Ã ¹× ±Ù¸° À¯Çü¿¡ µû¶ó Â÷À̰¡ ÀÖ¾ú´Ù. ÇÇÇØ°¡ Áõ°¡ÇÒ¼ö·Ï È¥ÇÕ ¹× ½ÅÃࡤ¾ÆÆÄÆ® À¯ÇüÀÇ º¯È­ °¡´É¼ºÀº 8.5 % °¨¼ÒÇÑ ¹Ý¸é, ³ëÈÄ¡¤´Üµ¶ÁÖÅà À¯ÇüÀÇ º¯È­ °¡´É¼ºÀº 35.9 % °¨¼ÒÇÏ¿©, ÀÚ¿¬ÀçÇØ·Î ÀÎÇØ ±Ù¸°ÀÇ Ãë¾à¼ºÀÌ ´õ¿í ½ÉÈ­ÇÏ´Â °ÍÀ¸·Î ³ªÅ¸³µ´Ù. ´ë±¸¿¡¼­´Â ÇÇÇØ Áõ°¡ÀÇ ¿µÇâÀ¸·Î º¯È­°¡ ÃËÁøµÇ¾úÀ¸³ª ÀÎõ, ¿ï»ê¿¡¼­´Â »ó´ëÀûÀ¸·Î º¯È­°¡ ¾ïÁ¦µÇ¾ú´Ù. ÀÚ¿¬ÀçÇØ´Â ±Ù¸° º¯È­ Ư¼º¿¡µµ ¿µÇâÀ» ¹ÌÃÆ´Âµ¥, ÇÇÇØ Áõ°¡´Â ±Ù¸° °³¼±°ú ¼èÅð °¡´É¼ºÀ» °¢°¢ 17.6 %, 13.2 % °¨¼Ò½ÃÄ×´Ù. ÀÌ·¯ÇÑ °á°ú´Â ÀÚ¿¬ÀçÇØ°¡ ´ëµµ½ÃÀÇ ±Ù¸° º¯È­ °¡´É¼ºÀ» Àü¹ÝÀûÀ¸·Î À§Ãà½Ã۰í ƯÈ÷ Ãë¾àÇÑ ±Ù¸° À¯Çü°ú ƯÁ¤ µµ½ÃÀÇ ±Ù¸°¿¡¼­ º¯È­ °¡´É¼ºÀ» ¾ïÁ¦ÇÔÀ¸·Î½á ȸº¹·ÂÀ» ¾àÈ­ÇÒ ¼ö ÀÖÀ½À» ½ÇÁõÀûÀ¸·Î ±Ô¸íÇÏ¿´´Ù. ¶ÇÇÑ ±Ù¸° À¯Çü¡¤Áö¿ªº° Ư¼º¿¡ ÀûÇÕÇÑ Àç³­´ëÀÀ ¹× Àç»ýÀü·« ¼ö¸³ Çʿ伺À» Á¦±âÇÑ´Ù.
¿ä¾à2 This study analyzed the impact of natural hazards damage on neighborhood type changes in seven metropolitan cities (Seoul, Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan) excluding Sejong. Neighborhood changes from 2010 to 2023 were tracked using logistic regression analysis as an analysis unit for the census output area. First, three neighborhood types(Struggling, New¡¤High, and Old¡¤Single) were derived through k-means cluster analysis, and the change in neighborhood types between 2010 and 2023 was
calculated. As a result of logistic regression analysis, the likelihood of neighborhood change decreased by 18.0 % as the average annual
damage from natural disasters increased. The possibility of neighborhood changes affected by natural disasters differed according to
city and neighborhood type. As the damage increased, the likelihood of change in Struggling and High¡¤New type decreased by 8.5 %,
while the likelihood of change in Old¡¤Single type decreased by 35.9 %, further intensifying the vulnerability of neighborhoods due to
natural hazards. Neighborhood changes were promoted in Daegu due to increased damage, but changes were relatively suppressed in
Incheon and Ulsan. Natural hazards also affected neighborhood change characteristics, and increased damage reduced the likelihood
of neighborhood improvement and decline by 17.6 % and 13.2 %, respectively. These results empirically demonstrated that natural
hazards can reduce the likelihood of neighborhood change in large cities overall and weaken resilience by suppressing the likelihood
of change, especially in vulnerable neighborhood types and neighborhoods in certain cities. It also raises the need to establish disaster
response and regeneration strategies suitable for neighborhood type and regional characteristics.
¼ÒÀåó ´ëÇÑÅä¸ñÇÐȸ
¾ð¾î Çѱ¹¾î
DOI https://doi.org/10.12652/Ksce.2025.45.5.0589