Journal of Korean Society for Geospatial Information Science (대한공간정보학회지)

Korea Spatial Information Society (대한공간정보학회)
권호 표지
DOI QR코드

DOI QR Code

Vegetation Classification using KOMPSAT-2 Imagery and High-resolution airborne imagery in Urban Area

KOMPSAT-2 영상 및 고해상도 항공영상을 이용한 도심지역 식생분류

  • Park, Jeong Gi (Dept. of Civil Engineering, Chonbuk National University) ;
  • Go, Shin Young (Dept. of Civil Engineering, Chonbuk National University) ;
  • Cho, Gi Sung (Dept. of Civil Engineering, Chonbuk National University)
  • Received : 2013.08.07
  • Accepted : 2013.11.22
  • Published : 2013.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Recently, It is increasing that importance of systematic management by carbon sinks in forest resources. Especially, in terms of social, Forest resources in urban areas are important role as well as carbon sinks, and improvement of the natural environment of the city. In this study, through ANOVA analysis that a total of nine different vegetation index from rearranged NIR band of images to Forest tree species classified in urban areas using high-resolution aerial images and satellite images of KOMPSAT-2. And various vegetation indices such as NDVI are divided a species by forest units through statistical analysis. Also, separated species are compared to forest type map by the Forest Service. As a result, it is built as basis for vegetation management in urban areas.

최근 탄소 흡수원으로 산림자원의 체계적인 관리의 중요성이 높아지고 있다. 특히 도심지역에서의 산림자원은 탄소 흡수원 뿐만 아니라 도시자연의 환경개선 기능은 물론 사회적 정서적 측면에서도 중요한 역할을 한다. 따라서 본 연구에서는 고해상도 항공영상과 KOMPSAT-2 위성영상의 이용하여 도심지역내 산림 영역의 수종 분류를 수행하기 위하여 고해상도의 항공영상과 위성영상의 NIR밴드의 영상재배열을 수행하였으며 NDVI 등 9개의 다양한 식생지수를 분산분석을 통해 임상단위로 수종을 구분하였다. 또한 산림청에서 제공하는 임상도를 이용하여 본 연구에서 구분된 수종과 비교 분석을 수행하였다. 이와 같은 식생분류 결과를 바탕으로 도시지역 내 식생관리를 위한 기초자료를 구축하고자 하였다.

Keywords

References

  1. Bae, Jun Hee, 2003, Use of satellite data for forest type classification in warm, Honam University.
  2. Hwang, Soo Min, 2003, A study on ANOVA using a cDANA microarray analysis of experimental data and homoscedasticity assumption, Ewha Womans University.
  3. Kim, Cheon, 1997, A study on spectral reflectance characteristics of the timber and forestry grouping , Kookmin University.
  4. Kim, Ki Tae, 2011, Estimation of carbon absorption of urban area using high resolution satellite images, Gyeongsang National University.
  5. Kim, So Ra, Lee, Woo Kyun, Kwak, Han Bin, Choi, Sung Ho, 2009, Estimating carbon sequestration in forest using KOMPSAT-2 imagery, Journal of Korean Forest Society, Vol. 99, No. 3, pp. 324-330.
  6. Kim, Woon Soo, Jeon, Han Na, Jeong, Nam Sook, 2011, A study on monitoring performance management for meeting GHG emission reduction target in Seoul, Seoul Development Institute, pp. 1-205.
  7. Park, Eun Joo, 2002, A study on drought susceptibility using Landsat ETM+ imagery, Kyung hee University.
  8. Park, Eun Jin, Jwa, Sung Hee, 2009, Quantification of $CO_2$ Uptake by urban trees and greenspace management for C sequestration, Gyeonggi Research Institute, Vol. 2009, No. 11, pp. 1-1.
  9. Park, Ok Jun, 2000, A study on distribution and change of NDVI with land-cover in city of sungnam, Journal of GIS Association of Korea, Vol. 8, No. 2, pp. 275-288.
  10. Ruiliang Pu., Shawn Landry., 2011, A comparative analysis of high spatial resolution IKONOS and WorldView-2 imagery for mapping urban tree species, Elsevier, Vol. 124, pp. 516-533.
  11. Seo, Moon Hyo, 2000, A study for cluster analysis algorithm by trmmed k-means method, Dongguk University.
  12. Woo, Hee Sook, 2009, Quality assessment of mosaic image of airborn digital frame camera image, Inha University.
  13. Yang, Y.H., Buckley, M.J, 2000, Comparison of methods for image anlysis on cDNA microarray data, Technical report 584, Department of Stastistics, University of California, Berkely.

Cited by

  1. Development of a Classification Method for Forest Vegetation on the Stand Level, Using KOMPSAT-3A Imagery and Land Coverage Map vol.32, pp.6, 2018, https://doi.org/10.13047/KJEE.2018.32.6.686
  2. UAV 기반 식생지수를 활용한 상록수 분포면적 분석 vol.47, pp.1, 2017, https://doi.org/10.22640/lxsiri.2017.47.1.15