Long-term landuse map update using satellite imagery for mesoscale environmental assessment

Fuan Tsai; En Kai Lin; Tang Huang Lin; Gin Rong Liu

Long-term landuse map update using satellite imagery for mesoscale environmental assessment

Fuan Tsai, En Kai Lin, Tang Huang Lin, Gin Rong Liu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This study developed an image integration and classification system in order to provide necessary spatial parameters for an integrated mesoscale environmental assessment system (IMEAS). The lack of complete and up-to-date coverage of landcover/landuse information has reduced the reliability of IMEAS modeling results, especially for the emission model. Therefore, the developed data providing system continuously collects, processes and analyzes images from multiple sources with different spatial and spectral resolutions. The classification results are used to update landuse maps of entire Taiwan. The system also aggregates the generated landcover/landuse information into gridformat data layers of different scales for direct input of modeling systems.

Original language	English
Title of host publication	28th Asian Conference on Remote Sensing 2007, ACRS 2007
Pages	696-701
Number of pages	6
State	Published - 2007
Event	28th Asian Conference on Remote Sensing 2007, ACRS 2007 - Kuala Lumpur, Malaysia Duration: 12 Nov 2007 → 16 Nov 2007

Publication series

Name	28th Asian Conference on Remote Sensing 2007, ACRS 2007
Volume	1

Conference

Conference	28th Asian Conference on Remote Sensing 2007, ACRS 2007
Country/Territory	Malaysia
City	Kuala Lumpur
Period	12/11/07 → 16/11/07

Keywords

Classification
Data integration
Environmental monitoring
Landuse

Cite this

@inproceedings{5624ede56c734cebbc01ef2d9158ace2,

title = "Long-term landuse map update using satellite imagery for mesoscale environmental assessment",

abstract = "This study developed an image integration and classification system in order to provide necessary spatial parameters for an integrated mesoscale environmental assessment system (IMEAS). The lack of complete and up-to-date coverage of landcover/landuse information has reduced the reliability of IMEAS modeling results, especially for the emission model. Therefore, the developed data providing system continuously collects, processes and analyzes images from multiple sources with different spatial and spectral resolutions. The classification results are used to update landuse maps of entire Taiwan. The system also aggregates the generated landcover/landuse information into gridformat data layers of different scales for direct input of modeling systems.",

keywords = "Classification, Data integration, Environmental monitoring, Landuse",

author = "Fuan Tsai and Lin, {En Kai} and Lin, {Tang Huang} and Liu, {Gin Rong}",

year = "2007",

language = "???core.languages.en_GB???",

isbn = "9781615673650",

series = "28th Asian Conference on Remote Sensing 2007, ACRS 2007",

pages = "696--701",

booktitle = "28th Asian Conference on Remote Sensing 2007, ACRS 2007",

note = "28th Asian Conference on Remote Sensing 2007, ACRS 2007 ; Conference date: 12-11-2007 Through 16-11-2007",

}

Long-term landuse map update using satellite imagery for mesoscale environmental assessment. / Tsai, Fuan; Lin, En Kai; Lin, Tang Huang et al.
28th Asian Conference on Remote Sensing 2007, ACRS 2007. 2007. p. 696-701 (28th Asian Conference on Remote Sensing 2007, ACRS 2007; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Long-term landuse map update using satellite imagery for mesoscale environmental assessment

AU - Tsai, Fuan

AU - Lin, En Kai

AU - Lin, Tang Huang

AU - Liu, Gin Rong

PY - 2007

Y1 - 2007

N2 - This study developed an image integration and classification system in order to provide necessary spatial parameters for an integrated mesoscale environmental assessment system (IMEAS). The lack of complete and up-to-date coverage of landcover/landuse information has reduced the reliability of IMEAS modeling results, especially for the emission model. Therefore, the developed data providing system continuously collects, processes and analyzes images from multiple sources with different spatial and spectral resolutions. The classification results are used to update landuse maps of entire Taiwan. The system also aggregates the generated landcover/landuse information into gridformat data layers of different scales for direct input of modeling systems.

AB - This study developed an image integration and classification system in order to provide necessary spatial parameters for an integrated mesoscale environmental assessment system (IMEAS). The lack of complete and up-to-date coverage of landcover/landuse information has reduced the reliability of IMEAS modeling results, especially for the emission model. Therefore, the developed data providing system continuously collects, processes and analyzes images from multiple sources with different spatial and spectral resolutions. The classification results are used to update landuse maps of entire Taiwan. The system also aggregates the generated landcover/landuse information into gridformat data layers of different scales for direct input of modeling systems.

KW - Classification

KW - Data integration

KW - Environmental monitoring

KW - Landuse

UR - http://www.scopus.com/inward/record.url?scp=84865623777&partnerID=8YFLogxK

M3 - 會議論文篇章

AN - SCOPUS:84865623777

SN - 9781615673650

T3 - 28th Asian Conference on Remote Sensing 2007, ACRS 2007

SP - 696

EP - 701

BT - 28th Asian Conference on Remote Sensing 2007, ACRS 2007

T2 - 28th Asian Conference on Remote Sensing 2007, ACRS 2007

Y2 - 12 November 2007 through 16 November 2007

ER -

Long-term landuse map update using satellite imagery for mesoscale environmental assessment

Abstract

Publication series

Conference

Keywords

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