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Spatial Anaylsis of Agro-Environment of North Korea Using Remote Sensing I. Landcover Classification from Landsat TM imagery and Topography Analysis in North Korea

위성영상을 이용한 북한의 농업환경 분석 I. Landsat TM 영상을 이용한 북한의 지형과 토지피복분류

  • Hong, Suk-Young (Soil Management Division, Department of Agricultural Environment, National Institute of Agricultural Science and Technology, RDA) ;
  • Rim, Sang-Kyu (Soil Management Division, Department of Agricultural Environment, National Institute of Agricultural Science and Technology, RDA) ;
  • Lee, Seung-Ho (Korea Forest Research Institute) ;
  • Lee, Jeong-Cheol (Korea Rural Community & Agriculture Corporation) ;
  • Kim, Yi-Hyun (Soil Management Division, Department of Agricultural Environment, National Institute of Agricultural Science and Technology, RDA)
  • 홍석영 (농촌진흥청 농업과학기술원 농업환경부 토양관리과) ;
  • 임상규 (농촌진흥청 농업과학기술원 농업환경부 토양관리과) ;
  • 이승호 (국립산림과학원 산림경영부 산림정보과) ;
  • 이정철 (한국농촌공사 해외사업처 해외사업팀) ;
  • 김이현 (농촌진흥청 농업과학기술원 농업환경부 토양관리과)
  • Published : 2008.06.30

Abstract

Remotely sensed images from a satellite can be applied for detecting and quantifying spatial and temporal variations in terms of landuse & landcover, crop growth, and disaster for agricultural applications. The purposes of this study were to analyze topography using DEM(digital elevation model) and classify landuse & landcover into 10 classes-paddy field, dry field, forest, bare land, grass & bush, water body, reclaimed land, salt farm, residence & building, and others-using Landsat TM images in North Korea. Elevation was greater than 1,000 meters in the eastern part of North Korea around Ranggang-do where Kaemagowon was located. Pyeongnam and Hwangnam in the western part of North Korea were low in elevation. Topography of North Korea showed typical 'east-high and west-low' landform characteristics. Landcover classification of North Korea using spectral reflectance of multi-temporal Landsat TM images was performed and the statistics of each landcover by administrative district, slope, and agroclimatic zone were calculated in terms of area. Forest areas accounted for 69.6 percent of the whole area while the areas of dry fields and paddy fields were 15.7 percent and 4.2 percent, respectively. Bare land and water body occupied 6.6 percent and 1.6 percent, respectively. Residence & building reached less than 1 percent of the country. Paddy field areas concentrated in the A slope ranged from 0 to 2 percent(greater than 80 percent). The dry field areas were shown in the A slope the most, followed by D, E, C, B, and F slopes. According to the statistics by agroclimatic zone, paddy and dry fields were mainly distributed in the North plain region(N-6) and North western coastal region(N-7). Forest areas were evenly distributed all over the agroclimatic regions. Periodic landcover analysis of North Korea based on remote sensing technique using satellite imagery can produce spatial and temporal statistics information for future landuse management and planning of North Korea.

직접 조사가 힘든 비접근 지역인 북한 전역을 대상으로 DEM을 이용하여 표고 및 경사별 분포 현황을 분석하였고, Landsat TM 위성영상을 이용하여 논, 밭, 산림, 나지, 초지, 물, 간척지, 염전, 건물. 주거지, 기타10개의 분류 항목에 대한 토지피복도를 작성하였다. DEM을 이용한 지형분석 결과 개마고원이 위치한 량강도를 중심으로 동쪽 지역의 표고가 1,000 m 이상으로 높게 나타났고, 평안남도와 황해남도 지역이 낮게 나타났다. 산악지로 구분되는 심한 경사인 E 등급이 전체 면적 대비 38.2%로 가장 넓게 분포하는 것으로 나타났다. 편평한 A 경사는 주로 북한 서해안 지역에 넓게 분포하고 E 경사는 동북부 산악지형에서 높은 비율을 보이고 있어 북한의 전형적인 동고서저의 지형특성을 잘 반영하였다. 위성영상을 이용하여 분류한 북한의 토지피복 항목을 살펴보면 전체 면적 중 산림이 69.6%로 가장 넓게 분포하고 있고, 밭이 15.7%, 나지가 6.6%, 논이 4.2%, 하천과 저수지 등을 포함한 물이 1.6%, 초지가 1.1%, 도시와 주거지가 0.9%인 것으로 나타났다. 행정구역별 지표면 피복을 살펴보면 황해남도와 평안남도 등 서쪽에 위치한 해안가 저위평탄지에 주로 논이 넓게 분포하는 것으로 나타났다. 밭의 분포는 논과 같이 서쪽 지역에 많이 분포하는 경향이었으나 북동쪽에 위치한 함경도와 자강도 및 량강도에도 비교적 고르게 분포하는 것으로 나타났다. 경사등급별로 농경지의 분포를 살펴보면, $0{\sim}2%$인 A 경사에 약 80% 이상 논이 분포하고 있고, 반면 밭은 A, B, C, D, E 등급에 비교적 고르게 분포하고 있는 것으로 나타났다. 농업기후지대별 토지피복 현황을 살펴보면, 논과 밭은 북부 평야지대와 북부 서해안지대에 전체의 약 79%와 45%가 분포하였고 산림은 비교적 모든 농업기후지대별로 고르게 분포하였다. 위성영상을 이용한 원격탐사 기술은 접근이 힘든 지역에 대한 농업기반 및 농경지 정보를 주기적으로 파악할 수 있고, 넓은 지역에 대한 정보 수집이 가능한 장점이 있어, 3년$\sim$5년 주기로 영상분류를 통한 토지피복도를 작성하여 토지이용 및 분류에 대한 시간적 공간적인 변화를 분석한다면 농경지와 산림에 대한 이용 현황 자료를 제공할 수 있고 앞으로의 이용계획 수립에 효율적으로 사용될 수 있을 것으로 생각된다.

Keywords

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