Application of kompsat II imagery for carbon emmission inventory map

E. M. Chang; J. R. Kim; Y. S. Choi; I. H. Lee; G. S. Kim

Application of kompsat II imagery for carbon emmission inventory map

E. M. Chang, J. R. Kim, Y. S. Choi, I. H. Lee, G. S. Kim

Department of Geoinformatics

Research output: Contribution to journal › Conference article › peer-review

Abstract

Various approaches have been tried to estimate carbon emission model from leaf to globe. Satellite imagery is one of the sources to make land cover and land use data, usually in national or continental levels. Efforts to reduce carbon dioxide have started to be made in local governments. We tried to get LULC data for City of Boryong, Chungnam Province, using KOrean Multi-Purpose Satellite II, 1 meter resolution data and other GIS data. Training vectors are selected from data of Korean Land Information System, supervised and unsupervised classifications were mixed to get the 5 classes and 18 classes. The more classes we get, the more error were turned out. To convert to carbon inventory, greenhouses and other point source data were digitized and weighted to make carbon emission maps. Natural ambient carbon sink can be added into policy for carbon emission inventory map, on the base of satellite images.

Original language	English
Pages (from-to)	113-116
Number of pages	4
Journal	International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume	38
State	Published - 2010
Event	ISPRS Technical Commission VII Symposium on Advancing Remote Sensing Science - Vienna, Austria Duration: 5 Jul 2010 → 7 Jul 2010

Keywords

Carbon emission
Classification
Kompsat ii images

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

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title = "Application of kompsat II imagery for carbon emmission inventory map",

abstract = "Various approaches have been tried to estimate carbon emission model from leaf to globe. Satellite imagery is one of the sources to make land cover and land use data, usually in national or continental levels. Efforts to reduce carbon dioxide have started to be made in local governments. We tried to get LULC data for City of Boryong, Chungnam Province, using KOrean Multi-Purpose Satellite II, 1 meter resolution data and other GIS data. Training vectors are selected from data of Korean Land Information System, supervised and unsupervised classifications were mixed to get the 5 classes and 18 classes. The more classes we get, the more error were turned out. To convert to carbon inventory, greenhouses and other point source data were digitized and weighted to make carbon emission maps. Natural ambient carbon sink can be added into policy for carbon emission inventory map, on the base of satellite images.",

keywords = "Carbon emission, Classification, Kompsat ii images",

author = "Chang, {E. M.} and Kim, {J. R.} and Choi, {Y. S.} and Lee, {I. H.} and Kim, {G. S.}",

year = "2010",

language = "English",

volume = "38",

pages = "113--116",

journal = "International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives",

issn = "1682-1750",

publisher = "International Society for Photogrammetry and Remote Sensing",

note = "ISPRS Technical Commission VII Symposium on Advancing Remote Sensing Science ; Conference date: 05-07-2010 Through 07-07-2010",

}

TY - JOUR

T1 - Application of kompsat II imagery for carbon emmission inventory map

AU - Chang, E. M.

AU - Kim, J. R.

AU - Choi, Y. S.

AU - Lee, I. H.

AU - Kim, G. S.

PY - 2010

Y1 - 2010

N2 - Various approaches have been tried to estimate carbon emission model from leaf to globe. Satellite imagery is one of the sources to make land cover and land use data, usually in national or continental levels. Efforts to reduce carbon dioxide have started to be made in local governments. We tried to get LULC data for City of Boryong, Chungnam Province, using KOrean Multi-Purpose Satellite II, 1 meter resolution data and other GIS data. Training vectors are selected from data of Korean Land Information System, supervised and unsupervised classifications were mixed to get the 5 classes and 18 classes. The more classes we get, the more error were turned out. To convert to carbon inventory, greenhouses and other point source data were digitized and weighted to make carbon emission maps. Natural ambient carbon sink can be added into policy for carbon emission inventory map, on the base of satellite images.

AB - Various approaches have been tried to estimate carbon emission model from leaf to globe. Satellite imagery is one of the sources to make land cover and land use data, usually in national or continental levels. Efforts to reduce carbon dioxide have started to be made in local governments. We tried to get LULC data for City of Boryong, Chungnam Province, using KOrean Multi-Purpose Satellite II, 1 meter resolution data and other GIS data. Training vectors are selected from data of Korean Land Information System, supervised and unsupervised classifications were mixed to get the 5 classes and 18 classes. The more classes we get, the more error were turned out. To convert to carbon inventory, greenhouses and other point source data were digitized and weighted to make carbon emission maps. Natural ambient carbon sink can be added into policy for carbon emission inventory map, on the base of satellite images.

KW - Carbon emission

KW - Classification

KW - Kompsat ii images

UR - http://www.scopus.com/inward/record.url?scp=84924050053&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:84924050053

SN - 1682-1750

VL - 38

SP - 113

EP - 116

JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

T2 - ISPRS Technical Commission VII Symposium on Advancing Remote Sensing Science

Y2 - 5 July 2010 through 7 July 2010

ER -

Application of kompsat II imagery for carbon emmission inventory map

Abstract

Keywords

UN SDGs

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