*Article* **Spatial Pattern and Factor Analyses for Forest Sustainable Development Goals within South Korea's Civilian Control Zone**

#### **Jinwoo Park 1 and Jungsoo Lee 2,\***


Received: 27 July 2018; Accepted: 26 September 2018; Published: 29 September 2018

**Abstract:** The United Nations' Sustainable Development Goals (SDGs) offer specific guidelines for improving sustainable forest management, especially Goal 15. Goal 15 protects, restores and promotes the sustainable use of land ecosystems, manages forests sustainably, prevents was against desertification, stops and reverses land degradation and prevents biodiversity loss. The Civilian Control Zone (CCZ) south of the Demilitarized Zone (DMZ) separating North and South Korea has functioned as a unique biological preserve due to traditional restrictions on human use but is now increasingly threatened by deforestation and development. We used hot spot analysis and structural equation modeling (SEM) to analyze spatial patterns of forest land use and land cover (LULC) change and variables influencing these changes, within the CCZ. Remote sensing imagery was used to develop land cover classification maps (2010 and 2016) and a GIS database was established for three change factors (topography, accessibility and socioeconomic characteristics). As a result of Hotspot analysis, Hotspots of change were distributed mainly due to agricultural activities and the development of forest and expansion of villages. Subsequent factor analysis revealed that accessibility had greater influence ( −0.635) than the other factors. Among the direct factors, change to bare land had the greatest impact ( −0.574) on forest change. These results shed light on forest change patterns and causes in the CCZ and provide practical data for efficient forest managemen<sup>t</sup> in this area with regards to the SDGs.

**Keywords:** forest land change; land change patterns; Civilian Control Zone; DMZ; sustainable development goals (SDGs); forest management; structural equation modeling (SEM); factor analysis
